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Reviews in Chemical Engineering

Editor-in-Chief: Luss, Dan / Brauner, Neima

Editorial Board: Agar, David / Davis, Mark E. / Edgar, Thomas F. / Giorno, Lidietta / Joshi, J. B. / Khinast, Johannes / Kost, Joseph / Leal, L. Gary / Li, Jinghai / Mills, Patrick / Morbidelli, Massimo / Ng, Ka Ming / Schouten, Jaap C. / Seinfeld, John / Stitt, E. Hugh / Tronconi, Enrico / Vayenas, Constantinos G. / Zagoruiko, Andrey / Zondervan, Edwin


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Volume 34, Issue 2

Issues

Process intensification

Frerich J. Keil
  • Corresponding author
  • Institute of Chemical Reaction Engineering, Hamburg University of Technology, 21073 Hamburg, Germany
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Published Online: 2017-12-19 | DOI: https://doi.org/10.1515/revce-2017-0085

Abstract

Process intensification (PI) is a rapidly growing field of research and industrial development that has already created many innovations in chemical process industry. PI is directed toward substantially smaller, cleaner, more energy-efficient technology. Furthermore, PI aims at safer and sustainable technological developments. Its tools are reduction of the number of devices (integration of several functionalities in one apparatus), improving heat and mass transfer by advanced mixing technologies and shorter diffusion pathways, miniaturization, novel energy techniques, new separation approaches, integrated optimization and control strategies. This review discusses many of the recent developments in PI. Starting from fundamental definitions, microfluidic technology, mixing, modern distillation techniques, membrane separation, continuous chromatography, and application of gravitational, electric, and magnetic fields will be described.

Keywords: centrifugal fields; electric fields; magnetic fields; process intensification; separation processes

Dedicated to:

Professor Rüdiger Lange (University of Dresden) on the occasion of his 65th birthday.

1 Introduction

To the best of the author’s knowledge, the term “process intensification” (PI) was used for the first time in a polish journal (Leszczynski 1973). PI saw a boost at imperial chemical industries (ICI) in the eighties by Prof. Ramshaw’s group (Ramshaw 1983, Law et al. 2017). Their work has been continued at the University of Newcastle (homepage: www.pinet-work.org). As yet, there is no clear definition of PI that all agree on. Various definitions have been proposed in the literature, which are quite diverse (Ramshaw and Arkley 1983, Cross and Ramshaw 1986, Stankiewicz and Moulijn 2000, Touris and Porcelli 2003, Charpentier 2007, Becht et al. 2009, Van Gerven and Stankiewicz 2009, Reay et al. 2013, Klemes et al. 2014, Portha et al. 2014, Baldea 2015, Gallucci and Van Sint Annaland 2015) (see also Table 1).

Table 1:

Selected definitions of process intensification over the last 25 years (Van Gerven and Stankiewicz 2009, Kim et al. (2017).

Another problem is a clear differentiation of PI from other terms used in chemical engineering, like conceptual process synthesis (Li and Kraslawski 2004), superstructure optimization (Yeomans and Grossmann 1999), and process system engineering (PSE) (Grossmann and Westerberg 2000, Moulijn et al. 2008). The European Roadmap of Process Intensification (2007) presents the following definition: “Process Intensification (PI): a set of often radically innovative principles (“paradigm shift”) in process and equipment design, which can bring significant (more than factor 2) benefits in terms of process and chain efficiency, capital and operating expenses, quality, wastes, process safety”. Van Gerven and Stankiewicz (2009) provide four guiding principles for PI:

  • Maximize the effectiveness of intramolecular and intermolecular events (example: dynamically changing conditions to attain kinetic regimes with higher conversion and selectivity).

  • Provide all molecules the same process experience (example: plug flow reaction with uniform, gradientless heating).

  • Optimize driving forces at all scales and maximize the specific surface areas to which they apply (example: increase transfer surface area through microchannel designs).

  • Maximize synergistic effects from partial processes (example: multifunctional reactors).

Van Gerven and Stankiewicz (2009) regard the first item presented above as the most important one in the future, although it has received the least attention within the PI community. On the molecular scale, one can modify the chemical routes, chemical kinetics, topological structure of the catalyst supports (shape-selective structures, functionalized surfaces, optimized pore radii distributions, and pore connectivities). These items are closely connected to catalysis.

Giving the same processing experience to the molecules may be achieved, for example, by static mixers, which offer an almost ideal plug-flow with very intensive mixing and enhancing the specific interfacial area for mass transfer. Structured packings in reactors, such as monoliths, gauzes, foams, and various designs of micromixers, can also improve local mixing. Local volumetric gradientless heating in a plug-flow reactor may be obtained, for example, by microwave heating.

The third point mentioned above deals with improved transport of mass and heat (diffusion and convective transport). Forced flow in membrane reactors (MRs) and multiphase flow reactors of phase-transfer catalysis supported by ultrasound may improve mass transfer conditions. Shorter diffusion paths in micro-reactors and pore structures optimized with respect to transport also result in higher mass transfer rates (Keil 2007, 2012, Trogadas et al. 2016). Micro-reactors and micro-heat exchangers allow a close control of local temperatures. A particular mode of operation is the periodic forcing of mass flow in bubble columns, trickle-flow reactors, or reverse flow of mass and/or heat in plug-flow reactors. These oscillating modes of operation, in some cases, can increase rates of catalytic reactions and improve the surface wetting of catalyst particles in trickle-flow reactors, which gives higher reaction rates.

Synergistic effects may be achieved by multifunctional devices on the macroscale. Reactive distillation (RD) is a prominent example, which combines reactions and separation into a single column equipped with a catalytic packing. Equilibrium-limited reactions are driven toward higher yields by separating the reactants from the products. This process is not suitable for any liquid/liquid separation: the conditions for temperatures and pressures have to match.

PI applies the common scientific areas of chemical process engineering: mathematics, physics, and chemistry, in particular quantum chemical approaches, classical molecular simulations (molecular dynamics and Monte Carlo), thermodynamics (classical and statistical), transport phenomena (fluid flow, diffusion, and heat and mass transfer), classical mechanics, electrodynamics, chemical kinetics, and numerical mathematics. Van Gerven and Stankiewicz (2009) have presented a compilation of the most relevant issues addressed by PI (Table 2).

Table 2:

Generic areas of PI (Van Gerven and Stankiewicz 2009).

Stankiewicz and Moulijn (2000) and Stankiewicz and Drinkenburg (2004) (see in Stankiewicz and Moulijn 2004) introduced a somewhat different definition of PI: PI comprises novel equipment, processing techniques, and process development methods that, compared to conventional ones, offer substantial improvements in (bio) chemical manufacturing and processing. The authors presented a PI toolbox, ordered along two dimensions: equipment and processing methods (Table 3).

With regard to PI in industry, the goal is clearly to increase productivity as defined by the relationship between production of an output and all of the resource inputs used in accomplishing the assigned task. This includes the capital value-based assessment already at the development stage. Only if a robust economic advantage can be derived will implementation and positive perception in the industry take place (Becht et al. 2009, Raghavan and Reddy 2014). Gourdon et al. (2015) state that in spite of its attractive and promising results, the PI methodology exhibits a major default. Indeed, this methodology imposes a considerable effort of basic data acquisition and, furthermore, of simulation. According to these authors, this could be considered as a killer for the process development because there is a crucial requirement for time-to-market reduction, particularly in the frame of process innovation in a very competitive world. It implicitly means that not only the process has to be intensified but also the way for intensifying it.

There is a considerable overlap between PI and PSE (Moulijn et al. 2008). The authors assign to PI research fields like chemical reaction pathways and stoichiometry opened up by new catalysts, as well as of physical “forces and fields”, which drive rate processes. These include ways by which energy is brought into and utilized within the process or by which mass transfer is enhanced. Another PI area involves the selection and testing of materials to create structures (internals, particles, walls, and coagulates) suitable to support the process functions (e.g. mixing, (bio) reactions, and heat transfer). Both PI and PSE are involved in selecting and ordering of processing methods (i.e. choice of species, reactions, and thermodynamic phases for reactions) as well as staging and connectivity of compartments or units. PSE is predominantly responsible for operations and control of the plant and the supply chain. Tables 4 and 5 summarize the aims and skills in PI, PSE, and optimization.

Table 4:

Basic features of three areas of chemical and process engineering.

Table 5:

Comparison of current PI and PSE skill areas (Moulijn et al. 2008).

Table 6:

PI technologies with high and medium potential for energy saving.

Arizmendi-Sánchez and Sharratt (2008) have presented a framework in which the process models are based on physicochemical phenomena arranged into abstract (i.e. equipment independent) functional, structural, and behavioral modules. This modularization framework has been used in a methodology to encourage the generation of intensive design strategies. Topological representations are first generated from qualitative knowledge and then mapped into mathematical models. Causal graphs have been introduced by these authors to allow the designer to identify the relationships between variables relevant to the process. The equation based models have been implemented in object-oriented software to quantify the net effect of selected design variables or to quantify equipment requirements. Phenomena-based building blocks have been implemented in the form of a library in order to facilitate the construction and reuse of models. These building blocks have been created on the basis of the balance equations, which enables the consistent generation of mathematical models from phenomenological descriptions. This approach has been proposed to increase the flexibility, customization, and reusability of models in order to encourage the implementation and assessment of novel intensified and multifunctional process options.

Lutze et al. (2010) present a concept of a general systematic framework for the synthesis and design of PI options in hierarchical steps through analyzing an existing process, generating PI options in a superstructure and evaluating intensified process options. For each step, different tools and methods are needed. A knowledge base tool storing and retrieving necessary information data about intensified processes/equipments has been highlighted, including metrics for performance evaluation. The large search space has been reduced stepwise through constraints, performance evaluations, and objective functions. The set of PI metrics for evaluation has been classified into four groups: economic, environmental, safety, and intrinsified. Due to the multiobjective character of PI, all metrics have to be compared and weighted with each other in order to evaluate different PI and to find the option that gives the best overall improvement. Alternatively, the Institution of Chemical Engineers (IChemE, UK) published sustainability metrics. The metrics are presented in three groups: environmental indicators, economic indicators, and social indicators. Detailed worksheets, related to the various metrics, for usage in process industries are presented.

Process safety is also for PI of paramount importance, and the sustainability of the chemical and energy industry is highly dependent on improved process safety performance. However, the complexities and continuing changes of processing plants make the application of engineering for sustainable development a challenging task. In an overview of trends and challenges in process safety, Mannan et al. (2015, 2016) state that process safety engineering is the science of implementing into everyday engineering procedures a broad-based understanding of the complex interaction of chemical process technology, mechanical and process design, process control, and process safety management systems. The authors point to the fact that most of the catastrophic process safety incidents in the past could have been avoided through a better understanding of the fundamental science and engineering behind the process at hand. This includes understanding all of the possibilities by which a process can derail and the probability and consequence of each scenario. Some books (Bahr 1997, Kumamoto and Henley 2000, Crowl and Louvar 2002, Ericson 2005, Mannan 2012) and reviews (Venkatasubramanian et al. 2003a,b, among others) have been published on process safety.

Portha et al. (2014) proposed a complementary view of PI based on the concepts of local intensification and global intensification. Local intensification is defined here as the classical approach of PI based on the use of techniques and methods for the drastic improvement of efficiency of a single unit or device (reactors, separators, hybrid separators, etc.). When PI focuses on single units, the strong interactions among all units within the process are ignored, and the impact of local intensification of a single unit can be very limited, resulting in weak improvement of the whole process. A great deal of PI is linked with the sequence of the unit operations. Therefore, a holistic (global) overall PI is advantageous, which leads to a two-step approach. First, a global intensification approach can be performed of the whole performance of the global process. Second, local intensification by classical techniques, such as microstructuring to avoid heat and mass transfer limitations, and use of innovative driving forces or multifunctional systems can be employed. Local and global intensifications complement each other. This paper presents several examples of this approach. A similar method has been developed by Ponce-Ortega et al. (2012). A general mathematical formulation for each intensification process (unit intensification and plant intensification) has been proposed in their paper. Multiobjective optimization techniques have been used (Rangaiah and Bonilla-Petriciolet 2013). The authors have also presented a further definition of PI that comprised five points: smaller equipment for a given throughput, a higher throughput for a given equipment size or given process, less holdup for equipment or less inventory for processing of certain material for the same throughput, less usage of utility materials and feedstock for a given throughput and given equipment size, and higher performance for a given unit size.

Carvalho et al. (2013) described the development of a software tool (SustainPro) and its application to chemical processes, based on the implementation of an extended systematic methodology for sustainable process design.

Freund and Sundmacher (2008) have decomposed the chemical process into so-called functional modules that fulfill specific tasks in the course of the process. The functional modules themselves can be further decomposed and represented by a linear combination of elementary process functions and specific generalized flux vectors. When a volume element is passing such a functional module, its state is changed as a result of the fluxes that occur. For the analysis of the process, one has to consider elementary steps in the thermodynamic state space. Therefore, the whole process route can be designed from the starting point to the final point by selectively adjusting the respective ideal values of the fluxes at each point. This approach allows for detailed analysis and design of chemical processes, which helps to systematically identify and investigate suitable measures for PI.

As yet, many unit operations are already mature technology, while others still require much research. The European Roadmap for PI (2007) has presented a table (see Table 6) of PI technologies with high and medium potential for energy savings (see also EUROPIC).

American Institute of Chemical Engineers, through its RAPID Institute, initiated a research program with six fields of investigation (AIChE 2017) (see Table 7).

Table 7:

Rapid advancement in process intensification deployment (DOE, AIChE) (see also US Dept. of Energy 2015).

In the following, equipment for PI and chemical plants will be presented.

2 Equipment for PI

2.1 Microfluidic technology

Utilization of miniaturized equipment was pioneered by Prof. Ramshaw (Ramshaw 1983, Ramshaw and Arkley 1983). Reducing costs owing to smaller equipment, low energy consumption, high safety, less waste, etc., has been the main objective. The relative heat and mass transfer performance of micro-structured reactors with respect to conventional reactors is shown in Figure 1 (Jensen 2001, Kashid et al. 2015).

Benchmarking of microstructured reactors (Kashid et al. 2015).
Figure 1:

Benchmarking of microstructured reactors (Kashid et al. 2015).

This figure demonstrates that microreactors offer superior performance regarding heat and mass transfer. Heat transfer becomes more efficient as reaction volumes shrink. Therefore, the amount of energy consumed per unit temperature rise can be made extremely small. As reaction kinetics does, in general, not rely on large-scale diffusion, the intrinsic rate of rate-limited reactions will not increase in microfluidic devices compared to corresponding bulk reactions unless a wall-mediated mechanism is invoked. As in mass-transfer-limited systems, diffusion of reactants has a significant effect on the overall reaction rate, and microfluidic equipment will increase the rate. Another striking feature of microfluidic reactors or other microfluidic equipment is the high degree of control over local conditions such that it is often possible to select one product over another with high precision. Increased yields and selectivities result from optimal mixing (correct stoichiometry over time and space), heat exchange (exact energy provision with no overshooting to induce side reactions with higher activation energy), and residence time distribution (RTD) (no overexposure to concentration and temperature to induce follow-up reactions and decomposition) (Ehrfeld et al. 2000, Hessel et al. 2000, 2004, 2005, 2009, 2012, Hessel 2009). The intrinsic kinetics may be accelerated by a drastic increase in the temperature and/or pressure. Microreactors allow novel operating windows under unusual high temperatures and pressures. The pressure can be increased to several 100 bars because of the small reaction volumes. This may reduce the reaction times by an order of magnitude, which requires a precise setting of residence time down to seconds or below. The precise timing of reactions, determined by kinetic needs, can further enhance selectivity as consecutive reactions can be reduced. Operation at the kinetic limit allows also high space-time yields. Whether a microreactor or a flask should be used has been discussed by Hartman et al. (2011), Newman and Jensen (2013), and Jensen (2017). These authors list some questions to be answered. Is the mixing rate expected to be important relative to the reaction rate? Here, the Damköhler number (Da) is of importance. In synthesis with multiple reactions, maximizing yield or selectivity of the desired product is best accomplished when transport limitations are eliminated, i.e. Da<1. The next question is, what is the magnitude of the heat generation rate from the reaction compared to the heat removal rate capabilities of the flask reactor? If the ratio of the heat generated to the heat removed is far smaller than one, there is no incentive to use a microreactor for enhanced heat transfer. For microreactors, heat transfer coefficients up to 20,000 W/cm2·K were measured.

Several reviews on progress in microfluidic technology have been published over the last few years (Jensen 1999, Gavriilidis et al. 2002, Guettel and Turek 2010, Marre and Jensen 2010, Wiles and Watts 2011, Anderson 2012, Hessel et al. 2012, 2013a,b, 2015, Burkle-Vitzthum et al. 2015, among others). Applications in chemical synthesis of organic chemical (Sahoo et al. 2007, Calabrese and Pissavani 2011, Hartman et al. 2011, Baxendale 2013, Elvira et al. 2013, Jensen et al. 2014, Ley et al. 2015a,b) and natural products and pharmaceutical (Mascia et al. 2013, Pastre et al. 2013, Baumann and Baxendale 2015, Ierapetritou et al. 2016) were also reviewed. The supplement in Elvira et al. (2013) presents a comprehensive list of microfluidic reactors applied to organic chemistry.

Before a reaction between two or more components can occur, the molecules involved must come into close contact. Therefore, mixing is of importance in microreactors as it is in any chemical reactor. At first, one has to answer the question whether conventional macroscopic fluid flow equations may be used for describing flow in microdevices. The same holds for heat and mass transfer correlations. Fortunately, it turns out that in many cases, macroscopic description can be applied, except for some gases that do not fulfill the continuum hypothesis, and not the assumption of local thermal equilibrium. An important quantity determining the flow regime of gases and deviations from continuum description is the Knudsen number, defined as

Kn=λL[](1)

λ=mean free path length of the gas molecules [m]

L=characteristic length scale of the flow domain, for example, the channel diameter [m]

The Knudsen number may be used to identify four flow regimes:

  • Kn≤10−2: continuum flow with no-slip boundary conditions

  • 10−2<Kn≤10−1: continuum flow with slip boundary condition

  • 10−1<Kn≤10: transition flow

  • Kn>10: free molecular flow.

For the first two cases, the Navier-Stokes equation can be applied, whereby slip boundary conditions are employed in the second case. The slip boundary conditions introduce a slip length, Lsl, which relates the local shear strain to the relative flow velocity at the wall:

ugasuwall=Lslugasy|wall[m/s].(2)

The x-coordinate is directed toward the fluid flow direction, while the y-coordinate is perpendicular to the wall. The slip length is an empirical parameter that describes the interactions of the gas molecules with the wall. The third case is calculated by the direct simulation Monte Carlo (DSMC) approach (Bird 1994). This method is based on tracking the trajectories and interactions of gas molecules directly. The DSMC method models fluid flows employing “molecules” that represent a large number of real molecules in a probabilistic simulation to solve the Boltzmann equation (see e.g. Reif 1965, Reichl 1998). The fundamental assumption of the DSMC approach is that the molecular movement and collision phases can be decoupled over time periods that are smaller than the mean collision time. Several open-source codes of the DSMC have been published, for example, dsmcFoam in the open-source CFD package OpenFoam. Some DSMC simulations of flows in microchannels have been published (see, for example, Cai et al. 2000, Wang and Zhixin 2006, Yang et al. 2010, White et al. 2013, Kulakarni 2014). A book on flow in microchannels has been issued by Kandlikar et al. (2014) (see also Kockmann 2010). Flow in microchannels with diameters between 10 and 500 μm is mostly laminar and has a parabolic velocity profile. A consequence is that molecular diffusion in axial and radial direction plays a significant role in the RTD. The axial molecular diffusion increases the dispersion, while the radial dispersion reduces the spreading of the parabolic velocity profile. The Taylor-Aris correlation (Taylor 1953, Aris 1956) may be used for calculating the axial distribution:

Dax=Dmol+χu2d2Dm[m2/s](3)

Dmol=molecular diffusion coefficient [m2/s]

χ=1/119 for a square channel

χ=1/192 for a channel with a circular cross-section

u=superficial fluid flow velocity [m/s]

d=hydraulic diameter of the channel [m]

As can be realized from Eq. (3), owing to convection, a concentration tracer is usually dispersed much faster than it would have been by diffusion alone. It should be noticed that Eq. (3) is independent of any initial condition. Irrespective of how the tracer was distributed over the channel cross-section and along the channel initially, the description given by Taylor and Aris is valid for t→∞. Experimentally determined RTDs are often much more narrow than calculated by the Taylor-Aris correlation.

Dax is often calculated in its nondimensional form as the Bodenstein number, representing the ratio of convective transport to dispersion with the characteristic length l as

Bo=ulDax[](4)

u=≡superficial fluid flow velocity

An ideal plug flow reactor has an infinite value for Bo, and Bo=0 corresponds to an ideal mixed reactor.

The diffusive mixing efficiency may be described by the Fourier number, Fo, defined as follows:

Fo=Dtl2[](5)

D=diffusion coefficient [m2/s]

t=contact time [s]

l=characteristic length over which diffusion takes place [s]

The Fourier number can be regarded as a dimensionless time coordinate that compares the actual time with the time a molecule needs to sample the cross-sectional area of the tube. The validity of the Taylor-Aris relation may be related to Fourier numbers, which should be of order 1 or higher (Hessel et al. 2004). An extensively used method to characterize continuous micromixers is the iodide/iodate chemical test reaction (Villermaux-Dushman method). Commenge and Falk (2011) published a detailed protocol of the iodide/iodate test method, with different concentration sets and a general protocol to determine mixing times in such a way that reliable measurements of those values are possible.

Axial dispersion can be neglected if the space time is at least two times the radial diffusion time. This holds for gases in microchannels if their diameters are less than 500 μm and the space time is longer than 0.1 s. As, in general, many channels are used in parallel to obtain sufficient product per unit time, a careful design of the inlet gas distributor is indispensable. The influence of the gas distributor design on the RTD is presented by Wibel et al. (2013). These authors investigated the RTD for gas flows in microstructured reactors by CFD and experiments using a device as presented in Figure 2.

Microstructured device (Wibel et al. 2013).
Figure 2:

Microstructured device (Wibel et al. 2013).

The influence of the inlet and outlet regions of the devices and uneven flow distribution inside the microstructure on the RTD were discussed. The main impact factors for the flow distribution to an array of microchannels were found to be the following:

  • Geometry of the distribution section

  • Geometry of the microchannels

  • Flow profile in the outlet section

  • Nonconstant fluid properties (e.g. changing viscosity owing to temperature changes)

  • Tolerances of channel geometry

The shape of the distribution section as presented in Figure 3 (Commenge et al. 2002, see also Amador et al. 2008, Renault et al. 2012) improves the homogeneity of the flow distribution.

Microstructured plate with (1) inlet tube, (2) inlet chamber, (3) channels, (4) outlet chamber and (5) outlet tube (Commenge et al. 2002).
Figure 3:

Microstructured plate with (1) inlet tube, (2) inlet chamber, (3) channels, (4) outlet chamber and (5) outlet tube (Commenge et al. 2002).

The design principle for most flow distributors relies on controlling the hydraulic flow resistances in the device. This is described by the pressure drop in each of the parallel channels. In microfluidic devices, the resistive network model is often used to predict the influence of these resistances, which holds for a very low Reynolds number in the laminar flow range (Commenge et al. 2002, Amador et al. 2004, Al-Rawashdeh et al. 2014). An even distribution of the flow to the microchannels can be achieved by high-pressure losses owing to long microchannels. To include effects caused by uneven flow distribution and inlet and outlet sections, a modified Bodenstein number Bo* was proposed by Wibel et al. (2013), which describes the complete microdevice:

Bo=geu/nBoTA(6)

BoTA=Bodenstein number for a single micro channel by the Taylor-Aris correlation [Eqs. (3) and (4)] [–]

g=empirical factor representing deviation due to uneven flow distribution [–]

n=empirical factor [m/s]

u=mean flow velocity [m/s]

The factors g and n may be determined by means of CFD calculations. For example, the authors used a catalytically coated gas phase reactor that consisted of 36 stapled stainless steel foils carrying 60 etched elliptical microchannels on each. The passage was composed of 24 foils (1440 microchannels; cross-section: 0.5×0.325 mm2; length: 125 mm; gas flow rate: 0.5 l/s). The Bodenstein number for the entire device was 78.5, while BoTA=77.9. The factors g and n were 0.508 and 0.079, respectively. The difference between Bo* and BoTA was far larger for other examples.

The product distribution is strongly affected by the characteristic mixing time, which is defined as the time required for two fluids to be homogeneously mixed on the molecular scale. This time should be at least 10 times shorter than the characteristic reaction time, which is defined by the intrinsic kinetics to avoid a loss in yield and selectivity. For gases, the radial diffusion times in microchannels are in the order of 10−2 s, whereas the radial diffusion time for liquids is in the order of seconds in microchannels with diameters of 100 μm. Radial mixing is important to obtain a narrow RTD. Various micromixing devices were suggested, some of which are presented in Figure 4.

Examples of micromixers: (A) high-energy collision, (B) decrease of diffusion path, (C) T-square mixer, (D) Y-rectangular and (E) cylindrical mixer.
Figure 4:

Examples of micromixers: (A) high-energy collision, (B) decrease of diffusion path, (C) T-square mixer, (D) Y-rectangular and (E) cylindrical mixer.

Many more are discussed in detail by Kashid et al. (2015), Capretto et al. (2011), Kumar et al. (2011a,b), and Lee et al. (2011). Nagy et al. (2012) provide an overview of both dispersive and mixing effects in flow systems and present simple relationships for determining whether mixing or dispersion is important for a given flow system. These results are summarized in convenient charts to enable the experimentalist to identify conditions with potential mixing or dispersion problems. The information also expedites design changes, such as inclusion or changes of mixers and changes in reaction tube diameters (see also Schwolow et al. 2012). Based on the different mixing principles, micromixers are classified in mainly two categories (Kumar et al. 2011a,b):

  • Active mixers: generate disturbances with an external field or energy sources such as pressure disturbances, electro-kinetic instabilities, magneto-hydrodynamic action, electro-wetting-induced merging of droplets, acoustic disturbances, piezo-electric vibrating membranes, small impellers, integrated microvalves/pumps, thermal disturbances and others

  • Passive mixers: use of the flow energy to create multilamellae structures, which are stretched and recombined to promote mixing by molecular diffusion, such as parallel lamination, serial lamination, injection, chaotic advection, droplet turbulent mixing by means of collision of jets and specialty flow configurations (e.g. Coanda effect, relying on a microstructure for redirecting the flow), etc. In passive micromixers, no external power is supplied for stirring. Therefore, the mixing relies mainly on molecular diffusion and chaotic advection. The molecular diffusion is expedited by increasing the contact surface and decreasing the diffusion path between different fluids. For example, splitting and recombining the feed streams or injection of streams can break the laminar profile, which improves mixing. Dong et al. (2016) employed ultrasonic devices to improve mixing in microreactors. Cavitation bubbles were generated in the microchannel, which undergo vigorous translational motion and surface oscillation. It was found that the mixing time was reduced from 24–32 s to 0.2–1.0 s by ultrasound according to a quantitative analysis of the fluorescent image. The vigorous cavitation phenomena significantly improve the radial mixing and reduce the axial dispersion, resulting in a linear increasing of the Bodenstein number with ultrasound power. Kumar et al. (2011a,b) present an extensive literature survey of all types of mixers mentioned above and discuss their specific features in detail. Fundamentals of microfluidic flow are presented in the book written by Bruus (2007), Kirby (2013), and Karniadakis et al. (2005).

Heat transfer in microchannels is composed of heat conduction through the walls and the convective heat transfer from the wall into the fluid inside microchannels. Inside the microchannels, temperature changes and phase changes may occur. Various correlations for the pressure drop are presented in Kashid et al. (2015), Kirby (2013), and Karniadakis et al. (2005), among others. The pressure drop in a microchannel is the product of the hydraulic resistance, R, and the flow rate, v˙:

Δp=Rv˙[kg/(m×s2)](7)

The hydraulic resistance for single-phase flow is given to the Hagen-Poiseuille equation as

R=32μLλNCd2A[kg/(m2×s)](8)

μ=dynamic viscosity of the fluid [kg/(m·s)]

L=channel length [m]

λNC=noncircularity factor that depends on the channel geometry [–]

d=channel diameter [m]

A=channel cross-sectional area [m2]

The temperature of the cooling medium, Tc, is generally kept constant. The heat flux in convective heat transfer is described by the relation

Q˙=UA(TcT) [W](9)

Tc=coolant temperature [K]

T=temperature of the reacting fluid [K]

U=overall heat transfer coefficient [W/(m2·K)]

A=heat exchange area [m2]

1[W]=1[kgm2s3]=1[Js]

The overall heat transfer coefficient comprises all resistances:

1U=1hR+1hwall+1hcool[W/(m2×K)](10)

h = heat transfer coefficient, reactant, wall coolant

For straight laminar flow, the dimensionless heat transfer coefficient, the Nusselt number Nu, is constant, but dependent on the boundary conditions:

Nu=Udhλ [](11)

dh=hydraulic diameter of the channel [m]

λ=thermal conductivity of the fluid [W/(m·K)]

The Nusselt number for laminar flow and fully developed radial velocity and temperature profiles is 3.66 for circular channels, 2.98 for square channels, and 7.54 for parallel plates. The local heat transfer diminishes until the profile is completely developed. There are many empirical correlations for all lengths of tubular reactors (Karniadakis et al. 2005, Bruus 2007). Kashid et al. (2015) present detailed calculations of heat transfer data for various complex channel geometries under reactive and nonreactive conditions. Micro heat exchanger devices are discussed in detail by Kockmann (2010) and Hardt (2007).

The design of chemical microreactors comprises the dimensioning of the reactors, details of the channel structures, choice of catalyst (coated walls, particles inside the channels, etc.), materials of reactor and its connections, and choice of cooling/heating media. Design basis are kinetic data and thermophysical data, like fluid flow, heat, and mass transport coefficients. Scale-up of microdevices is mostly done by numbering-up of single devices, whereby the number of parallel operating units is increased. This approach is faster than the conventional scale-up as a redesign and pilot plant operation can be avoided. Various dimensionless Damköhler numbers may be employed for process design and scale-up (Damköhler 1936, 1937, 1988):

DaI=chem. component increaseconvective comp. increase=νir(ciw)(12)

DaII=chem. component increaseconvective comp. increase=νir(Dici)(13)

DaIII=chem. component increaseconvective comp. increase=ΔHRr(ρcpΔTaxw)(14)

DaIV=chem. component increaseconvective comp. increase=ΔHRr(λΔTrad)(15)

νi=stoichiometric constant of component i

r=reaction rate [mol/(m3·s)]

w=fluid velocity [m/s]

ci=concentration of component i [mol i/m3]

Di=diffusion coefficient [m3/s]

ΔHR=reaction enthalpy [J/mol]

cp=specific heat capacity [J/(g·K)]

ρ=density [g/m3]

Trad,ax =temperature difference radial, axial [K]

For a complete reaction within a long straight microchannel and a feasible temperature control, the following conditions have to be fulfilled (Kockmann 2013):

DaI>1 for complete reaction within the channel

DaII<1 for sufficient fast mixing and radial mass transfer

DaIII≈1 for sufficient low temperature change along the channel

DaIV<1 for sufficient heat transfer in the channel

According to Emig and Klemm (2017) and Kockmann (2013), the following steps are necessary for the successful design of microstructured chemical reactors:

  • The channel diameter dh is determined to avoid radial heat and mass transfer limitations. This may be achieved by obstacles, small channels, internals, or curved channels, which induce convective vortices and enhanced dissipation.

  • The temperature change owing to reaction heat generation has to be controlled appropriately. The characteristic time of heat conduction tM=dh2/a with the temperature diffusivity a=λ(ρcp) (λ=channel friction factors) must be shorter than the characteristic reaction time tR=ci1m/k (m=reaction order). For strong exothermic reactions, the third Damköhler number should be in the range of one [see Eq. (14)]:

DaIII=rΔHRm˙cpΔTad1(16)

m˙=mass flow rate [g/s]

cp=heat capacity of the fluid [J/(g·K)]

ΔTad=adiabatic temperature rise [K]

The heat of reaction has to be removed quickly from the reacting fluid by convective cooling. The fourth Damköhler number should be less than 1 [see Eq. (15)]:

DaIV=rΔHRkavΔTlog<1(17)

k=overall heat transfer coefficient [W/(m2·K)]

av=specific surface [m2/m3]

ΔTlog=log mean temperature [K]

  • The reaction volume, VR, has to be determined. Here, for straight channels, the standard design equations for tubular reactors may be used. If the Fourier number [see Eq. (5)] is greater than 1. If Fo <1, the channel diameter must be decreased.

  • The channel length, Lc, and the number of parallel channels, Nc, are defined by the reaction volume, VR, for the production per unit time. The proper residence time has to be calculated. The first Damköhler number, DaI, must be greater than 1 for a complete reaction [see Eq. (12)]:

DaI=νikcim1Lcw¯>1(18)

w¯=flow velocity of fluid inside the channel [m/s]

Typically, the flow velocities are in the range 0.01w¯5 m/s. The number of channels is given by

τDaI=arV˙in(NcLc) [s](19)

τ=residence time [s]

ar=cross-sectional area of one channel [m2]

V˙in=inflow of fluid volume per unit of time [m3/s]

  • The channels can be arranged in a single device with several channels (internal numbering-up) or can be set up in parallel (external numbering-up).

For heterogeneous gas/solid reactions, the channels are either coated with a porous washcoat along the channel walls or the channels are filled with catalyst particles. The proper catalyst layer thickness or the particle diameters have to be designed according the common rules in reaction engineering. In particular, the diffusive resistances in the layer and particles should be kept as small as possible. Gervais and Jensen (2006) provide analysis of different regimes of diffusion and laminar flow convection with bimolecular surface reactions relevant to biochemical assays performed in microfluidic devices. Their analytical and numerical results extend the transport models beyond the models commonly used to interpret results from surface plasmon resonance experiments (Zeng et al. 2014). Under fast reaction and diffusion conditions, the surfaces saturate following moving front kinetics, similar to that observed in chromatographic columns. Faridkhou et al. (2016) review studies on kinetics and hydrodynamics in micropacked beds (Salmi et al. 2013). Examples of reactions carried out in micropacked beds showed their advantages in the case of highly exothermic reactions and synthesis of hazardous materials. A macroscale versus microscale comparison in terms of volumetric liquid-solid mass transfer coefficient revealed significantly higher kLa values for micropacked beds stemming from higher surface-to-volume ratio provided in micropacked beds. Rebughini et al. (2016) have proven the potentialities of a hierarchical approach for modeling transport phenomena in catalytic reactors by the investigation of the gas-to-particle mass and heat transfer in micropacked bed reactors. The authors performed a detailed CFD analysis of heat and mass transport on different geometries of micropacked beds at different tube-to-particle diameter ratio. They found that there is no substantial difference between the j-factors for heat and mass transfer, in agreement with the Chilton-Colburn analogy, and channeling has no impact on the estimation of the j-factor, contrary to pressure drops. Based on the CFD results, suitable correlations for the gas-to-particle mass and heat transfer in micropacked bed were derived.

Kashid and Kiwi-Minsker (2009), Kashid et al. (2015), and Pangarkar (2015) reviewed the design of microstructured reactors for multiphase reactions, which can be subdivided into fluid-solid, fluid-fluid, and three-phase reactors (Desantos et al. 1991). Fluid-solid reactions are carried out in various types of reactors, such as packed beds, fluidized/slurry, and monolith reactors. The characteristic feature of packed-bed reactors is the pressure drop of the fluid flowing through the catalytic bed. To avoid a too large pressure drop, the use of catalyst pellets of 2–6 mm is necessary. A suitable temperature control should also be installed. The particle diameter should be less than a 10th of the channel diameter. The pressure drop in packed bed microreactors may be calculated by means of the Ergun equation (see Kashid et al. 2015) and the RTD of gas flow may be estimated using the following equation:

1Peax=0.3RepSc+0.51+3.8/(RepSc)(20)

Peax=axial Peclet number

Rep=Reynolds number related to the particle diameter

Sc=Schmidt number

To avoid high-pressure drop micro fixed beds, a structured catalytic bed arranged with parallel filaments giving identical flow characteristics to multichannel microreactors was developed. The channels formed by filaments have an equivalent hydraulic diameter in the range of a few microns, ensuring laminar flow and short diffusion pathways in radial direction (Wolfrath et al. 2001, Horny et al. 2004, 2007). Another possibility is filling the reactor channels with metallic or ceramic foams (Buciuman and Kraushaus-Czarnetzki 2003, Patcas et al. 2007). Foams have a low pressure drop because of their high porosities. Metallic foams have porosities of up to 95%, whereas the porosities of ceramic foams range from 75 to 85%. They allow radial mixing of fluid combined with enhanced heat transfer because of solid continuous phase of the foam structure. Catalytic foams were employed for partial oxidations of hydrocarbons, catalytic combustion, removal of soot from diesel engines (Buciuman et al. 2003), and methanol (MEOH) steam reforming (Yu et al. 2007c), among others. An alternative to foams are fibrous materials, in particular sintered metal fiber sheets. They have an open and homogeneous structure with porosities of 70–90% and a high thermal conductivity, which ensures homogeneous temperatures in the catalytic bed. The fibers can be covered by a homogeneous layer of zeolites (Nikolajsen et al. 2006) of oxide washcoat, which can be impregnated with a catalytically active material (Luther et al. 2008). A sintered metal fiber catalyst integrated in a “sandwich” reactor is presented in Figure 5.

“Sandwich” reactor with sintered metal fiber catalyst for heterogeneous catalytic processes (Bromley et al. 2008).
Figure 5:

“Sandwich” reactor with sintered metal fiber catalyst for heterogeneous catalytic processes (Bromley et al. 2008).

Fast heat supply or heat removal may also be achieved by parallel channels in multichannel microreactors, which are characterized by a high surface-to-volume ratio together with integrated heat exchange (Figure 6).

Stacked parallel coated channels alternating with cooling channels.
Figure 6:

Stacked parallel coated channels alternating with cooling channels.

The walls may be coated with catalytically active material. The length of the channels is dependent on the reaction time required for a given yield. Catalytic layers can be generated by sol–gel processes, electrophoretic, chemical vapor deposition, or physical vapor deposition (Renken and Kiwi-Minsker 2010a,b).

In general, microreactors are suitable for fast reactions. Because of the high heat and mass transfer rates, microreactors allow precise control of operating conditions, and they are inherently safe. High conversion rates and selectivities can be achieved by employing high temperatures and pressures (Trachsel et al. 2008). As under these operating conditions, catalyst deactivation may occur quite fast, in situ catalyst regeneration must be possible, as simple catalyst change is not possible for these reactors.

Gas-liquid reactions are often carried out in falling film microreactors where the liquid flows downward as a thin film while gas flows convectively either downward or upward (Figure 7A,B).

(A) Microstructured falling film reactor (gas/liquid) (Yeong et al. 2003); (B) microbubble column with integrated cooling channels (Jähnisch et al. 2000).
Figure 7:

(A) Microstructured falling film reactor (gas/liquid) (Yeong et al. 2003); (B) microbubble column with integrated cooling channels (Jähnisch et al. 2000).

The microreactors are mostly made of steel, having open channels, typically 300 μm deep, separated by about 100-μm-thick walls. The open microchannels prevent breakup of the liquid film. The gas-liquid interface may be as large as 20,000 m2 m−3, which is 2–3 orders of magnitude larger than in conventional bubble columns. The residence time is short (5–20 s), which requires fast reactions to achieve a reasonable conversion of the reactants. Depending on properties like flow velocity, gas/liquid flow ratio, fluid properties (e.g. viscosity), microchannel materials, wall roughness, temperature, pressure, and channel geometry, there are various flow regimes such as bubbly flow, Taylor flow, slug bubbly flow, slug annular flow, churn flow, and annular flow. Details about these flow regimes are, for example, given by Shao et al. (2009) (Figure 8).

Flow regimes in microchannels (Shao et al. 2009).
Figure 8:

Flow regimes in microchannels (Shao et al. 2009).

Here, we will discuss only Taylor flow and churn flow. Taylor flow is the most commonly observed in microchannels and is also denoted as slug and train flow. Mass transfer takes place from the gas phase to the liquid phase and vice versa. Chemical reactions may occur in both phases, but preferably in the liquid phase. Van Baten and Krishna (2004) developed a mass transfer model based on a simplified geometry (see Figure 9B,C).

Experimental snapshots and schematic presentation of Taylor flow in different configurations. (A) Taylor flow in vertical capillary. (B) Schematic presentation of Taylor flow in horizontal capillary (Lb – length of bubble and LUC – unit slug length) (Van Baten and Krishna 2004, Liu et al. 2005).
Figure 9:

Experimental snapshots and schematic presentation of Taylor flow in different configurations. (A) Taylor flow in vertical capillary. (B) Schematic presentation of Taylor flow in horizontal capillary (Lb – length of bubble and LUC – unit slug length) (Van Baten and Krishna 2004, Liu et al. 2005).

Mass transfer has contributions from the two caps at the bubble ends and from the liquid film surrounding the lateral side of the bubble. The second contribution to mass transfer dominates. A simplified expression of the volumetric mass transfer coefficient, kLa, employing the expression (Kashid et al. 2015):

Lslug=dtεL0.001411.55εL2ln(εL)[m](21)

εL=(1εG)

εL=volume fraction of liquid [–]

εG=volume fraction of gas [–]

dt=tube diameter [m]

is given by

kLa4.5DmuGLuc1dt[s1](22)

Dm=molecular diffusivity [m2/s]

uG=superficial gas velocity [m/s]

Luc=Lslug/(1−εG) unit slug length [m]

An increase in mass transfer in the liquid film can be achieved by structuring the channels of falling film plates in the form of staggered grooves in herring bone arrangements. These mixers are very efficient at low Reynolds numbers (Ziegenbalg et al. 2010). Another way to structure the surface is to mimic a regular porous network. This can be done by rhombic structures (Figure 10) (Ziegenbalg et al. 2010).

Microstructured falling film reaction plate with rhombic structure to mimic a regular porous network (Ziegenbalg et al. 2010).
Figure 10:

Microstructured falling film reaction plate with rhombic structure to mimic a regular porous network (Ziegenbalg et al. 2010).

Kashid and Kiwi-Minsker (2009) present examples of gas-liquid reactions in microreactors like fluorinations, chlorinations, nitrations, and sulfonations. They also present examples of liquid-liquid reactions, for example, nitration of benzene and toluene, biodiesel production, enzymatic reactions, and vitamin precursor synthesis. Gas-liquid-solid reactions were also studied (see also Knobloch et al. 2013, Li et al. 2013). Examples were mainly hydrogenations such as hydrogenation of cyclohexene (Losey et al. 2001) or hydrogenation of nitrobenzene to aniline (Yeong et al. 2003). For the latter reaction, a microstructured falling-film reactor was used. Among several catalysts tested, γ-alumina-supported palladium prepared through incipient wetness impregnation was found to be reasonably robust.

Continuous processing of several microunit operations and automated optimization are applied in organic synthesis and production of pharmaceuticals (Hartman 2012, Moore and Jensen 2012, Bieringer et al. 2013, Peplow 2014, Santanilla et al. 2015, Schenkel 2015, McMullen and Jensen 2011, Heitmann 2016, Peeva et al. 2016, Jensen 2017). Microreactors, membranes, and multistage distillation (Lam et al. 2011) on a chip may be employed in series to manufacture chemicals. A particular problem is solids handling in microreactors. Formation of solids along the walls leads to an increased pressure drop and finally to clogging of reactor channels (Hartman 2012). Smooth perfluorinated wall surfaces reduce the fouling problem. Furthermore, intermittent flushing of the channels may remove accumulated solids. Usage of ultrasonic irradiation of proper frequency and energy input may also remove clogging in channels. Computational modeling of multiphase reactors was reviewed by Joshi and Nandakumar (2015).

Multistep reactions may be carried out in a series of microreactors and separation units (see Figure 11) (Sahoo et al. 2007, McMullen and Jensen 2010, Liguori and Bjørsvik 2011, Moore and Jensen 2012, Al-Rifai et al. 2013, Mascia et al. 2013, Ingham et al. 2015, Hohmann et al. 2016).

Experimental setup of microdevices for multistep synthesis (Sahoo et al. 2007).
Figure 11:

Experimental setup of microdevices for multistep synthesis (Sahoo et al. 2007).

Control of temperature, pressure, and flow is possible by using corresponding sensors, valves, and pumps, combined with software, like LabView or Visual Engineering Environment. The problem of a fast and reliable determination of chemical composition by spectroscopic and chromatographic approaches in microdevices has not been satisfactorily solved (Livak-Dahl et al. 2011, Moore and Jensen 2012, Yue et al. 2012, Schwolow et al. 2015). Microfluidic devices are suited for high-throughput experiments to detect new catalysts, reaction conditions, and new drugs (Rodemerck et al. 2000, Santanilla et al. 2015). Pharmaceuticals and fine chemicals manufacturers have made considerable efforts to replace individual batch synthesis steps to complete end-to-end manufacturing (Lang et al. 2011, Bieringer et al. 2013, Schenkel 2015). Advanced simulation/optimization frameworks can be applied that employ process flowsheeting software (Aspen Plus®, gPROMs®, etc.) coupled with mixed-integer nonlinear programming (MINLP) optimization solvers, multiobjective optimization, dimensionality reduction, and/or principal component analysis (Hoffmann et al. 2001, Jolliffe 2002, Shlens 2003, Brunet et al. 2012, Trespalacios and Grossmann 2014, Rangaiah and Bonilla-Petriciolet 2013). Those techniques are in particularly useful in multiproduct plants (see also Marquez et al. 2010).

2.2 Static mixers

Mixing operations are essential in the chemical industries. They include mixing of miscible fluids in single-phase flow as well as heat transfer enhancement in, for example, multifunctional heat exchangers/reactors, dispersion of gas into a liquid, dispersion of an immiscible organic phase as drops in a continuous aqueous phase, three-phase contacting, and mixing of solids. Liquid-liquid extraction, gas absorption into liquids, solid-liquid pulp slurries, and solids blending are typical examples where mixing is employed. Static mixers are now in widespread use in the chemical and petrochemical industries to perform continuous operations. They are also employed in food industries and pulp and paper factories.

The mixing efficiency is a decisive criterion for the process performance, as it determines heat and mass transfer rates, process operating time, cost and safety, as well as product quality (Luo 2013). Heat and mass transfer can be promoted, for example, in a hollow channel with a specific geometric construction that increases transverse flow. Another design uses insert-type elements inside pipes, channels, or ducts. These elements redistribute the fluids in the directions transverse to the main flow. Static mixers divide and redistribute streamlines in a sequential way using only the pumping energy of the flowing fluid. In turbulent flows, static mixers promote turbulence and generate intense radial mixing, even near the wall. In the turbulent regime, eddy diffusion gives sufficient mixing for most industrial processes. The mixers produce, owing to inserts, a complex vortex system in which concomitant phenomena simultaneously enhance mass and heat transfer. They have lower energy consumption and lower maintenance costs compared to stirrers as they do not include moving parts. Additionally, they require small space and lower equipment costs. They can provide homogenization of feed streams with a minimum residence time. Some examples of static mixers are given in Figure 12 (Edward et al. 2014).

Static mixers: (A) flow division in a helical mixer; (B) Chemplant™ static mixer; (C) flow division by baffles with various number of elements.
Figure 12:

Static mixers: (A) flow division in a helical mixer; (B) Chemplant™ static mixer; (C) flow division by baffles with various number of elements.

Inserts such as blades or helices cause local acceleration and stretching of the fluid. Incoming fluid is split into layers and then recombines the layers in a new sequence. This may be repeated in subsequent elements. If the number of layers is increased by a factor of 2 by each element, one obtains 2N layers for N elements. Those devices are classified as 2N-mixers. Others are 4N or 3(2)N−1 mixers. A classification of unit operations using static mixers is given in Figure 13.

Classification of unit operations using static mixers.
Figure 13:

Classification of unit operations using static mixers.

The most common use of static mixers in industry is blending of two or more miscible fluids, or a reacting mixture is blended to eliminate concentration gradients that would arise in empty tubes. These mixers are useful wherever radial and tangential mixing and a plug flow reaction environment are desired. Applications of static mixers in plastics industries and food factories are widespread. Blending of plasticizers, stabilizers, colorants, fillers, and flame retardants into polymer melts is a typical example. In food industries, static mixers are used to mix oils, juices, beverages, and milk drinks in food formulations. Static mixers may also be used for gas mixing prior to combustion, for example. In water treatment, chlorine or ozone may be mixed into water as a disinfectant. Static mixers are also in use for reacting systems. An example is the reaction injection molding (RIM) of polyurethanes. Commercial RIM machines use an impingement mixer followed by a static mixer to quickly blend reactive components (Kolodziej et al. 1982).

Mixing, chemical reaction, and heat transfer can occur simultaneously in the same apparatus (Anxionnaz et al. 2008). Combinations of static mixers/heat exchangers are useful in the polymer industry for melt viscosity adjustments by temperature variation for optimal process conditions, cooling of polyester melts between the reactor, and the fiber spinning unit or heating polymer solutions prior to devolatilization, among other applications (Ghanem et al. 2014). Mixing elements are in particular useful in deep laminar flow, because they provide a more uniform RTD. Lammers and Beenackers (1994) suggested using a continuous tubular reactor containing static mixers to produce starch ethers for food and pulp. Static mixers are not restricted to continuous flow systems. Figure 14 illustrates how they can be used for continuous flow, fed-batch, and batch reactors.

Reactor configurations using static mixers.
Figure 14:

Reactor configurations using static mixers.

Ali et al. (2015) proposed a concept to enhance heat transfer and mixing quality performance by using flexible vortex generators (FVGs) for a static mixer configuration, whereby the FVGs could freely oscillate owing to flow-induced forces. A considerable improvement in heat and mass transfer relative to rigid configurations could be demonstrated by CFD simulations. Static mixers are also useful in cocurrent or countercurrent liquid-liquid extraction. Many other examples are presented in reviews by Thakur et al. (2003) and Ghanem et al. (2014). A comprehensive overview over mixing in industrial practice is presented in a handbook by Paul et al. (2004) and its updated version (Kresta et al. 2015). Another book on mixing in the chemical process industry was published by Nienow et al. (1997). Baldyga and Bourne (1999) compiled fundamentals of turbulent mixing research.

Mixing may be divided into three regimes: macromixing, mesomixing, and micromixing. Macromixing is the mixing on the scale of the whole vessel. The mixing process depends directly on the transfer efficiency of the mean flow at different scales. Macromixing is generally characterized by the RTD (Habchi et al. 2009). As is known from chemical reaction engineering (see, for example, Fogler 2016), the RTD describes the global motion of the flow since it measures the time that a single volume element spent inside the reactor or other devices. This large-scale motion drives the fluid volume elements between high- and low-momentum regions in the unit operations. Static mixers reduce the RTD variance by generating a radial convective transfer. Mesomixing is on a scale smaller than the bulk circulation and is often referred to as the intermediate mixing time scale (Paul et al. 2004), where molecular and viscous diffusion are important. It describes the coarse-scale turbulent exchange between the fresh feed and its surrounding environment. Describing mesomixing can be based on the following mechanisms: a turbulent dispersion mechanism and an inertial-convective disintegration mechanism (Baldyga and Bourne 1999). Micromixing consists of viscous-convective deformation of fluid elements that accelerates the aggregate size reduction up to the diffusion scale. Micromixing is in particular important in reactors, as it controls mixing of reactants on the molecular scale, which, in turn, influences the selectivity of reactions.

There are various qualitative and quantitative approaches used to measure and/or describe the degree of mixing (Ghanem et al. 2014). Flow visualization using colored dyes or fluorescent materials and reactions yielding colored species are in use for qualitative characterization of mixing. A drawback of most of these methods is that they give no information on the spatial mixing quality throughout the mixer depth, which can lead to underestimation or overestimation of mixing times and lengths. The spatial or temporal in situ monitoring of species concentration is a quantitative method for measuring mixing. Using the Villermaux/Dushman parallel-competitive iodide/iodate reaction system, Men et al. (2007) analyzed mixing efficiency quantitatively by the segregation index derived from the ultraviolet absorption. The mixing performance of a microstructured mixer was analyzed in terms of the total volume flow and turbulent energy dissipation rate. Salmon et al. (2005) presented an experimental setup to probe the interdiffusion of various miscible and nonreacting liquids. A Raman confocal microscope allowed imaging the local concentrations of two coflowing liquids in a microchannel. These steady-state measurements provided precise quantitative information about the kinetics of the interdiffusion process. The above-mentioned iodide/iodate reaction system is an example of competitive-consecutive or competitive-parallel reactions. The principle is to carry out two reactions in parallel that both use a common reactant, which they compete for. One of the two reactions should be very fast (quasi-instantaneous), with characteristic time tR1, so that it proceeds only if mixing is extremely rapid. The second reaction should be fast, but slower than the first one. The second reaction has characteristic time tR2 close to the mixing time tm. The local chemical reaction thus results from a competition between mixing at microscales and the reaction kinetics. Quantitative information can be obtained on the yield of the slower reaction. Consequently, mixing performance is characterized by the amount of secondary product formed. The greater the yield of the slower reaction, the poorer the mixing quality. Thakur et al. (2003) present extensive lists of correlations for calculating the key parameters (pressure drop, interface generation, and heat transfer) of various types of mixers. Guidelines for selecting static mixers and scale-up considerations are also given. CFD codes are becoming ever more important in the design of static mixers (see, for example, Joshi and Ranade 2003, Versteeg and Malalasekera 2007, Yu et al. 2007a,b,c, Andersson and Andersson 2011). Some types of static mixers were modeled by CFD, for example, SMRX mixer (Kandhai et al. 1999), Kenics Static Mixer (Van Wageningen et al. 2004), and staggered herringbone mixer (Kee and Gavriilidis 2008). Van Wageningen investigated in detail the Kenics static mixer both numerically and experimentally in the range of Re=100…1000. Two numerical methods, the Lattice-Boltzmann method and FLUENT, were compared and used to simulate the flow. Furthermore, the flow field and dynamic behavior were validated by means of Laser Doppler Anemometry. Molecular dynamics (MD) modeling of turbulence is still in its infancy (see, for example, Muriel 2009, Smith 2015).

2.3 Intensified separation processes

2.3.1 Internally heat integrated distillation columns

In a standard distillation column, heat is supplied in a reboiler and taken out in a condenser at the top of the column. Owing to the temperature difference between the heating and cooling media employed in the reboiler and condenser, respectively, the separation of components is always accompanied by energy losses. Common distillation processes have an overall thermodynamic efficiency of about 11% (Cussler and Dutta 2012) and are therefore important targets for PI, as they consume a large fraction of energy in chemical plants. Freshwater (1951) introduced the first extensive thermodynamic analysis of distillation processes. He suggested transferring heat from the rectifying to the stripping section of a single distillation column, in order to reduce the temperature lift by a heat pump. This idea was worked out further by Flower and Jackson (1964) using a series of simulations based on the second law of thermodynamics (see also Null 1976). The concept of heat-integrated distillation column (HIDiC) was further investigated by Fitzmorris and Mah (1980) and Nakaiwa et al. (1997, 2001). Nakaiwa et al. (2003), Kiss and Obujić (2014), Kiss (2013), and Górak and Stankiewicz (2011) reviewed the early developments of the HIDiC technology and other recent separation systems. The HIDiC is an improvement of heat-pump operated distillation. HIDiC technology offers several very attractive features (Nakaiwa et al. 2003):

  • High energy efficiency. The highest degree of internal heat integration within HIDiC offers higher energy efficiency than other heat-integrated distillation columns do, and a large number of extra degrees of freedom for the process design, thus making it possible to utilize the maximum potential energy savings within a distillation column.

  • Zero external reflux and boil-up operation. In HIDiC, the internal heat integration plays the role of the reboiler and condenser employed in common distillation columns, such that in an ideal case, neither a condenser nor a reboiler is necessary.

  • Enhanced potential of internal heat integration techniques. Using internal heat integration, many applications within distillation processes are possible, such as multicomponents separation, batch distillation, pressure-saving distillation, and RD.

The principle of a HIDiC system is presented in Figure 15.

(A) Principles of a heat-integrated distillation column; (B) schematic drawing of a pilot plant (Gorák and Stankiewicz 2011).
Figure 15:

(A) Principles of a heat-integrated distillation column; (B) schematic drawing of a pilot plant (Gorák and Stankiewicz 2011).

In a HIDiC, heat is transferred from a hotter rectification section (operated at higher pressure) to the colder stripping section (see Figure 15A), therefore leading to gradual evaporation and condensation along the length of the stripping and rectifying section, respectively. This concept can also be used if the rectifying and stripping sections are of different sizes. Thus, a short stripper can be connected only to the top or bottom part of a long rectifier, and similarly, a short rectifier can be connected to the top or bottom part of a long stripper (Kiss and Obujić 2014). In order to establish the required temperature driving force, the vapor leaning the top of the stripping section is directly recompressed such that the rectifying section is operated at a higher pressure than the stripping section. The main advantage of HIDiC is based on the fact that the compression effort in this device is limited to bridging the temperature difference over the height of the stripping section only. In order to maximize the thermodynamic efficiency of HIDiC, the compression ratio (Pout/Pin) should be minimized (de Rijke 2007). However, minimizing the compression ratio implies minimization of the temperature difference, which can be compensated for only by a corresponding increase in the heat transfer area. Mah et al. (1977) were the first who described a HIDiC model (see also Tondeur and Kvaalen 1987, Nakaiwa 1988). This model is based on a modified tridiagonal matrix method for the mass and energy balances proposed by Wang and Henke (1966). A good equipment design is essential for industrial implementation of HIDiC. A systematic design procedure for HIDiC was proposed by Gadalla (2009), who divided the design into a thermodynamic and hydraulic part. The design process is initiated by simulating a conventional column or heat pump configuration for the given design problem. Based on the common design parameters, like feed flow rate and the feed temperature/pressure and composition, column pressure, pressure drop, and product specifications, one calculated the number of separation stages in each column section reboiler and condenser heat duties. In case of heat-pump-assisted distillation, the column configuration is simulated to calculate also the compressor power and working pressure ratio. Next, the complete HIDiC configuration, including heat exchange or integration, is simulated employing the basic design. Here, the first step considers the thermodynamic capabilities of the design and then the hydraulic capacities of the stages. The procedures are completed by optimization procedures. An interactive design approach employing a modified Pouchon-Savarit diagram was proposed by Wakabayashi and Hasebe (2013). Shahandeh et al. (2014) and Gutierrez-Guerra et al. (2014) introduced a genetic algorithm, respectively, for optimization of HIDiC configurations. As yet, almost all investigations on HIDiC were simulations and laboratory-scale experiments. One exception is the so-called SuperHIDiC introduced by the Japanese Toyo Engineering company (see Figure 16) (Chementator 2012) (see also Long et al. 2016).

SuperHIDiC configuration developed by Toyo Engineering Corp. in collaboration with the National Institute of Advanced Industrial Science and Technology (Tokyo, JP).
Figure 16:

SuperHIDiC configuration developed by Toyo Engineering Corp. in collaboration with the National Institute of Advanced Industrial Science and Technology (Tokyo, JP).

The company expects energy reductions up to about 50% in refineries employing this column. Examples of application of this column are propylene fractionation, xylene column, and aromatics disproportionation unit stripper. Maruzen Petrochemical Co. Ltd. (Japan) installed the first SuperHIDiC in a methyl-ethyl-ketone unit.

The features of this column are the following:

  • Side-exchangers can be provided at composition where enthalpy change should be provided.

  • Heat transfer area can be adjusted so as to meet desirable heat duty.

  • Pairing of stages between rectifying section and stripping section can be determined in consideration of desirable heat duty and temperature difference.

  • Overall heat transfer coefficient can be predicted on a high confidence level.

The rectifying section located below the stripping section is characterized by the following properties:

  • Side-exchanges can be accomplished by means of thermos-siphon/gravity.

  • Normal trays or packing is utilized.

  • Side-cut to obtain intermediate product or multiple-feed can be carried out.

  • Feed stage can be optimized.

SuperHIDiC enables the highest energy saving performance in distillation systems developed so far. The system is colicensed by the National Institute of Advanced Industrial Science and Technology and Toyo Engineering.

2.3.2 Dividing-wall column

A useful and efficient concept for the separation of mixtures with three or more components in one column is the dividing-wall column (DWC) (Kaibel 1987, Olujić et al. 2009, Asprion and Kaibel 2010, Dejanović et al. 2010, Niggemann et al. 2010, 2011, Kiss and Obujić 2014). The DWC is an implementation of a thermally coupled distillation design already investigated in the years 1935 (Monroe), 1946 (Wright), and 1965 (Petlyuk). Because the vertical partition in the column shell separates the column into a feed and a side stream section, DWCs are thermodynamically equivalent to Petlyuk columns. The vertical walls avoid radial mixing of vapor and liquid streams and enable the withdrawal of three products with any thermodynamically feasible purity in one column (see Figures 17 and 18).

(A) Dividing-wall column; (B) basic types of dividing-wall columns (Yildirim et al. 2011).
Figure 17:

(A) Dividing-wall column; (B) basic types of dividing-wall columns (Yildirim et al. 2011).

(A) Dividing-wall column; (B) integrated three-column configuration; (C) decomposed three-column configuration (Schröder et al. 2016).
Figure 18:

(A) Dividing-wall column; (B) integrated three-column configuration; (C) decomposed three-column configuration (Schröder et al. 2016).

Compared to conventional columns-in-series and/or in-parallel configurations, a DWC requires much less energy (up to 30% less), capital, and space. Dejanović et al. (2010) give a complete overview of the work done until 2010 on the research on implementation of DWCs, from early ideas on thermal coupling of distillation columns to practical issues that needed to be solved for their successful implementation. The design of DWCs is more difficult than that of a conventional distillation column, as there are more degrees of freedom to be considered. As yet, design models for DWCs are not available in commercial simulators (Aspen, ChemCad®, ProSim®, etc.). Approaches to simulation, optimization and control are presented in that paper (see also Grossmann et al. 2005, Kraemer et al. 2009, Niggemann et al. 2010, Dejanović et al. 2011, Kiss and Bildea 2011, Yildirim et al. 2011, Barttfeld et al. 2004, Caballero 2015, Segovia-Hernández and Bonilla-Petriciolet 2016, Franke 2017, Waltermann and Skiborowski 2017). Particular focus is directed on column internals and dimensioning. The patents literature is also surveyed by Dejanović et al. (2010). Yildirim et al. (2011) focused on current industrial applications of DWCs and related research activities. Long and Lee (2014) reviewed some energy-efficient distillation technologies that can be used in a retrofit design. The research on retrofits and implementation of retrofits using a thermally coupled distillation sequence and a DWC were reviewed. The paper proposed coupled schemes as alternatives to a Petlyuk column that do not have the classical problem of controlling the vapor transfer from one column to another and have not previously been proposed for retrofits. The authors evaluated also a solution for retrofitting azeotropic and extractive distillation systems. Various issues such as the constraints, techno-economic analysis, controllability, and operability were discussed (see also Stankiewicz and Moulijn 2004, Kiss 2013, Long et al. 2016, Rangaiah 2016). DWCs are used for a broad spectrum of systems, e.g. hydrocarbons, alcohols, aldehydes, ketones, acetals, amines, and others (Kaibel et al. 2006). Important is a comparison of modeling results with experimental data for stationary and instationary conditions. The instationary results are needed to cover also start-up and shut-down conditions. Additionally, a concept of the respective control systems is required (Donahue et al. 2016). Niggemann et al. (2010) carried out an extensive analysis of DWCs based on both experimental and simulation studies. Several different feed compositions of a ternary mixture of fatty alcohols have been examined in a purpose-built pilot plant while maintaining product specifications of ~99 wt% at steady-state conditions. Their process model consists of various elements, such as equilibrium stages, collectors and distributors, a reboiler, and a condenser. These elements can be arbitrarily combined to simulate any desired column setup. The model uses ordinary differential equations obtained from mass and energy balances of each element and a set of algebraic equations that are used to predict the physical properties, the vapor-liquid equilibria, and the column hydraulics. The MESH equations for the equilibrium stage model, in which the theoretical stages are numbered from top to bottom, have been set up. Similar model equations have been employed to describe the other elements (reboiler, condenser, collectors, and distributors). The highly nonlinear differential algebraic system of equations has been implemented in the commercial software tool ASPEN Custom Modeler. The model is capable of describing the process characteristics of DWCs, such as the heat transfer across the dividing wall (DW), the liquid distribution above the wall, and the self-adjustment of the vapor distribution below the wall. The heat transfer across the vertical partition may not be neglected owing to its impact on the temperature profiles and the required reboiler duty. The model calculates a self-adjusting vapor split according to the condition of equal pressure drop on both sides of the DW. An extensive validation of the model showed very good agreement between experimental and simulation results for pressure drops, product compositions, and temperature profiles. In addition, it was found that heat transfer across the DW and pressure drop in the nonseparating column internals are extremely important quantities that must not be neglected in laboratory-scale columns. The vapor split values vary significantly in range 0.3–0.5 if the heat transfer across the DW is taken into consideration. If this heat transfer is neglected, the vapor split remained virtually constant around 0.52. Ehlers et al. (2015) confirmed that heat transfer across the DW can actually increase or decrease the minimum energy demand of a DWC, but a heat stream crossing the DW will never change the minimum energy demand of a DWC by more than the amount of heat that is transferred. This implies that the effect of heat transfer across the wall on the energy demand of a DWC can be kept low, if the column is operated close to the point of minimum energy consumption. Niggemann and Fieg (2012) carried out an extensive validation of the transient behavior of a DWC. First, the mathematical process model was parameterized for existing DWCs on the laboratory and production scales. Then, appropriate disturbance scenarios were identified based on systematically conducted simulation studies. Subsequently, these disturbance scenarios were realized on laboratory- and production-scale columns. A comparison of the experimental and simulated results has shown that the simulation model describes the experimental disturbance scenario well in all column segments. Different propagation velocities and different amplitudes of temperatures and concentrations were successfully described. Thus, the transient process behavior of the simulation model is able to describe both the steady-state and transient behavior of DWCs. The great advantage of this validated model is that it “replaces” a real plant. Hence, several types of analysis can be efficiently conducted by means of the process model, such as developments in the fields of process control, optimization, troubleshooting, and debottlenecking. This contributes to a safe and cost-efficient transfer to a corresponding production-scale column. Adrian et al. (2004) have shown that model predictive control for DWCs is superior to single-loop PI controllers, in particular when constraints for operating conditions have to be taken into account. Ling and Luyben (2009) proposed a new DWC control structure that controls the purities of product streams and also minimizes energy consumption (see also Kiss and Bildea 2011). This was achieved implicitly by controlling a composition of the heaviest component in the prefractionator. Disturbances in feed flow and feed composition were used to demonstrate the effectiveness of the proposed control structure. A comparison of the dynamic controllability of the DWC with a conventional configuration was also provided. The authors discussed the problem of defining control structures for DWCs. Zavala-Guzmán et al. (2012) discussed the tuning of PI controllers for DWCs within a pole placement framework to compute values of controller gains, in terms of well-known and identifiable parameters for each control loop, such as static gains and time constants. The goal was to establish a methodology that reduced the number of tuning freedom degrees that inclusively allowed a simultaneous tuning of all controllers. An extension of this approach based on discrete measurements was also published by Zavala-Guzmán et al. (2016). Rodriguez et al. (2017) presented the control of an extractive and reactive DWC (R-DWC). The authors established a decentralized structure as well as a model predictive control and compared both approaches. The decentralized control showed a very oscillatory response as the result of the interactions being difficult to control; on one hand, the multivariable predictive control showed a smooth response and good control being able to handle larger disturbances than the decentralized option. Buck et al. (2011) have introduced decentralized temperature control systems by a systematic approach. Different control systems have been designed and compared by means of simulation and experiment. The methodology is a general framework, applicable to a wide range of control problems in DWCs. Errico et al. (2008) discussed a retrofit of an industrial distillation whereby a large part of the existing equipment should be kept. Various modifications of the existing plant (elimination of all reboilers/condensers or some of the reboilers/condensers) were compared with respect to the energy savings and investment costs. The optimal solution was found to be the alternative that has the minimum modifications of the existing plant. A saving of 23% on energy consumption could be achieved.

Some other models for DWCs have been reviewed by Dejanović et al. (2010). As different column configurations in a distillation network can achieve the same ultimate products, with different amounts of energy to do so. Therefore, systematic generation and evaluation of all possible complex column configurations for given multicomponent separation problems are desirable. Linninger (2009) reviewed advances to tackle the challenges of synthesizing complex column networks with computer-aided design algorithms. Linninger, in particular, discussed his temperature collocation approach, which replaces the column height or equilibrium stages as an independent variable with the bubble point temperature of the liquid mixture on a given equilibrium tray. The composition trajectories are expressed as functions in the independent variable, T, instead of the height of the column. A function was formulated that describes the composition profiles, xi, as a function of the temperature-dependent equilibrium constant, Ki, column section difference points, and generalized column section reflux. This transformation has been found to approximate column profiles for various solution models very accurately. A novel hybrid genetic algorithm deploying stochastic search in a reduced design space and Newton-methods to satisfy state equations were shown to solve optimal structure and design variables simultaneously. This is an effective tool for modeling and optimization complex column configurations while accounting for nonideal thermodynamics. Grossmann et al. (2005) reviewed work on the optimal design of distillation of individual columns using tray-by-tray models. A combination of novel representations for individual columns and superstructures, combined with disjunctive programming (Yeomans and Grossmann 2000) and robust initialization schemes, has made it possible to solve these problems with reasonable computational effort. Shah and Agrawal (2010) described a simple-to-use six-step matrix method for obtaining all the basic distillation configurations and additional thermally coupled configurations that separate a zeotropic multicompoment feed into essentially pure product streams. The configurations obtained were ranked for a given application subject to criteria of interest. The only information needed to generate the configurations was the number of components in the feed. The authors successfully enumerated all the configurations for feeds containing up to eight components. The approach can also be used to generate nondistillation and hybrid separation configurations and even easy-to-retrofit configurations. Caballero (2015) proposed a novel algorithm for the rigorous design of distillation columns that integrates a process simulator in a generalized disjunctive programming formulation. Operational conditions (reflux ratio, internal and external flows, etc.) as well as structural parameters (number of trays in each column section and, consequently, location of feed and product streams, etc.) were simultaneously optimized. The model was solved using a hybrid simulation optimization approach by taking advantage of the effective and reliable numerical methods included in process simulators for converging distillation columns as well as the thermodynamic packages, property estimation, etc., and at the same time the flexibility of equation-based environment (see also Caballero and Grossmann 2014). Caballero and Grossmann (2013) also demonstrated how to systematically identify all the sequences of separation tasks that can produce configurations that include at least a DWC. Rong (2011) has shown that DWCs can be systematically generated from conventional simple column configurations. Because the simple column sequences with sharp splits are the simple and widely studied conventional schemes for multicomponent distillation, the purpose of Rong’s work is to formulate a procedure for systematic synthesis of DWCs for such simple conventional schemes. A four-step procedure was formulated that systematically generated all possible DWCs from the simple column sequences. Starting from the subspace of the column sequences, the subspace of thermally coupled configurations is first generated, from which the subspace of thermodynamically equivalent structures is then generated. Finally, the subspace of the DWCs was generated. The procedure is easy to use and can systematically generate the possible DWCs from the simple column sequences of an n-component mixture.

Design optimization can be performed based in either sequential design procedures, whereby unit operation models may be taken from commercial simulators, or a simultaneous optimization employing mathematical programming procedures. In general, the sequential design starts with shortcut calculations that are mostly based on Fenske-Underwood-Kirkbride equations, followed by rigorous MESH models (see, for example, Seader et al. 2010). Halvorsen’s (2001) Vmin approach can provide good initialization values for liquid and vapor splits. The rigorous models may be taken from a commercial simulator. For example, ASPEN Plus® contains a so-called MULTIFRAC model for a Petlyuk configuration that is thermodynamically equivalent to a DWC without heat transfer across the wall. Luyben (2013) describes the steps to initialize the model and achieve the product specifications. DWC can be decomposed into several columns (see Figure 18 for a four-column decomposition) in such a way that the configuration is thermodynamically equivalent to a DWC. Dejanović et al. (2011) introduced a systematic procedure to DWC design employing Vmin graphs for evaluating the minimum energy demand, followed by a rigorous simulation based on the four-column configuration (see Figure 19).

(A) Dividing-wall column (DWC); (B) four-column configuration of (A) (Waltermann and Skiborowski 2017).
Figure 19:

(A) Dividing-wall column (DWC); (B) four-column configuration of (A) (Waltermann and Skiborowski 2017).

Waltermann and Skiborowski (2017) introduced a tailored superstructure for simultaneous simulation and optimization of DWCs. The formulation of their DWC model exploits the decomposition approach of Carlberg and Westerberg (1989) for problem initialization, whereas the DWC is represented by three thermally coupled columns. The mathematical model of the columns is based on the MESH equations and employed the decomposition of the optimization problem into a generic superstructure model and an implicit model for equilibrium and enthalpy calculations (Skiborowski et al. 2015), which is integrated into the optimization problem by means of an external function. Different phases and equilibrium solutions were determined by a reliable homotropy continuation algorithm (Press et al. 2007). The introduced external function overcomes the implicit discontinuities at the interface of possible miscibility gaps by means of a reformulation of the three-phase column model. The optimization was implemented in a general algebraic modeling system (Brooke et al. 2005) environment. The optimization of the discrete design degrees of freedom, i.e. the number of equilibrium trays in each section, was accomplished by means of variable locations for the feed stream, the side-streams of the subsequent columns, the top vapor stream of the lower and the bottom liquid stream of the upper subsequent column, as well as the reflux from the reboiler and the condenser. Each potential location of streams was modeled by binary decision variables. The resulting MINLP problem (Fletcher 2009) was solved in a series of relaxed NLP problems, according to an approach by Kraemer et al. (2009). Franke (2017) has presented a MINLP optimization algorithm that considers the nonconvexities of the rigorous distillation model and is able to find a high-quality solution for complex distillation problems. The developed modified Generalized Benders Decomposition algorithm was applied to the optimization of DWCs. Some calculated examples of DWCs showed significantly lower energy savings than reported in the literature. The author pointed out that it is of utmost importance to compare the optimized DWC with the optimized conventional sequence, based on the same cost function and physical property data, because otherwise, the wrong process option may be favored. Further optimization approaches have been presented by Waltermann and Skiborowski (2017).

Recent developments in equipment for DWCs have been described by Olujić et al. (2009). The authors have mentioned that a balance between pressure drop in column packings and avoidance of vapor and liquid maldistribution has to be paid attention to. CFD turned out to be a useful tool for detecting flow maldistributions. Asprion and Kaibel (2010) discuss DWCs for four and more component mixtures. Recent developments in intensified distillation-based separation processes in China have been reviewed by Li et al. (2016). Extensive reviews of distillation have been presented in edited handbooks by Huang et al. (2008), Gorák and Schoenmakers (2014) and Gorák and Olujić (2014).

An R-DWC combines a reactor and a separation unit in one column shell (see Figure 20).

Schematic showing the path from a distillation column to a reactive dividing-wall column (gray area represents the reactive zone) (Yildirim et al. 2011).
Figure 20:

Schematic showing the path from a distillation column to a reactive dividing-wall column (gray area represents the reactive zone) (Yildirim et al. 2011).

Such a configuration is an example of an extensive process integration. As can be observed from Figure 20, R-DWCs are a combination of RD (see Section 2.3.4) and DWCs. The advantages of this integrated process, i.e. high conversion, high selectivity, and product purity as well as cost and energy savings, have been demonstrated. These features are based on the following properties (Mueller and Kenig 2007):

  • Overcoming chemical and thermodynamic equilibrium limitations, leading to an increased yield.

  • Suppression of undesired consecutive reactions, resulting in a higher selectivity.

  • Direct heat integration in the case of exothermic reactions, leading to a reduced energy consumption.

  • Simultaneous liquid evaporation and reaction avoids hot spots.

  • Components with close boiling points may be separated.

The difference between a DWC and an R-DWC is the reactive zone in the prefractionator at the feed side of the column (Figure 20). In this reactive zone, the reactants of the feed stream are transformed into the products. Multiple feed streams might be used. For heterogeneously catalyzed reactions, catalyst particles are placed into the reactive zone, which might be structured packings with catalyst bags. Kaibel published the first paper on R-DWCs in the year 1984 (Kaibel 1984). Mueller and Kenig (2007) issued the first paper on R-DWCs employing a rate-based approach. Special attention was given to both the heat transfer through the DW and the vapor flow rate split below the DW. Schröder et al. (2016) analyzed the fundamental mechanisms of the R-DWCs, and a profound process understanding was deduced based on principal aspects of RD and the DWCs. Fields of application and insights into the key factors for an energy-efficient operation were systematically derived. A semi-shortcut method was proposed to determine the minimum vapor demand of the R-DWC, and its energy-saving mechanism was explained. Already during the process synthesis, one can evaluate whether R-DWCs are a promising option: The possible energy savings can be quickly quantified by this approach. In a further paper, Schröder and Fieg (2016) systematically investigated the influence of the separation properties of the reaction system on the energy saving potential. The saving mechanisms were also analyzed. Sander et al. (2007) presented experimental results of methyl acetate hydrolysis in a DWC obtained from a miniplant and a column of industrial scale. Ehlers et al. (2017) for the first time compared experimental results found in DWC and simulation results. A complex reaction system showing nonnegligible side reactions was used. The data obtained by the DWC were also compared with the operation of a conventional, nonreactive DWC with a similar chemical system analyzed for the same experimental setup. The differences between experimental and simulation results were small. Therefore, that paper gives a sound basis for the design of R-DWCs. Further details on integrated chemical processes may be found in an edited book by Sundmacher et al. (2005).

2.3.3 Reactive absorption, reactive extraction, and reactive crystallization

Reactive absorption (RA) combines absorption of gases with chemical reactions in the liquid phase, whereby the reactions improve the mass transfer and enhance solubility. It largely depends on the stoichiometry of the reactions, concentration of the reactants, and the mass transfer rates. In most cases, RA is carried out in plate or packed columns. In plate columns, the phases flow countercurrently, whereas in packed columns, liquid flows along the packing surface, and the gas occupies the rest of the void volume. Guidelines on how to select the most appropriate internals for specific RA applications are presented by Kohl and Nielsen (1997). RA may also be performed in spray columns, Venturi scrubbers, bubble columns, or thin film contactors (Yildirim et al. 2012). The main advantages of RA are the reduction in investment and operating costs, improved product purity, and lower energy demands.

As RA occurs in multiphase and multicomponent fluid systems with complicated heat and mass transfer phenomena, combined with one or several reactions, and the presence of neutral and sometimes ionic species, the modeling of RA is quite complicated. Phase equilibria, chemical equilibria, physical properties, like diffusion coefficients and viscosities, hydrodynamic and mass transport properties, and reaction kinetics have to be taken into consideration. At present, the most suitable and reliable approach for the description of staged absorption units is the rate-based approach (Kenig et al. 2003, Kenig 2008, Yildirim et al. 2012). As the conditions for RA processes vary considerably, an effective combination of different modeling approaches was suggested by Kenig (2008). The rate-based approach takes the rates of multicomponent heat and mass transfer and the chemical reaction directly into account. The mass transfer between the gas/liquid phases can be described by various models, like the two-film model (Wang and Langemann 1994) or the penetration/surface renewal model (Chung et al. 1971). The multicomponent diffusion in the films can be simulated by the Maxwell-Stefan equations (Taylor and Krishna 1993). The chemical reactions are included using a source term in the balance equations for each bulk phase and the mass transport equation for the film. Many two-film parameters can be found in the literature. Typical applications of RA are CO2/H2S removal from acid gas by ethanolamines, CO2 removal from power plant flue gas, NOx and SO2 removal from nitric acid plant and power plant off gases, respectively, and sulfuric acid production (Yildirim et al. 2012, Ramaswamy et al. 2013, Sharma et al. 2013, Smit et al. 2014). Olefin/paraffin separations by RA were reviewed by Safarik and Eldridge (1998). A review of advances in liquid adsorbents for CO2 capture was presented by Rosli et al. (2017) and by Yu et al. (2012).

Reactive extraction (RE) is a combination of physical extraction and chemical reaction in a single processing unit, whereby the reactions enhance the capacity of the solvent (Bart 2001). Esterification is mainly chosen as case study in the literature. For the simulation of countercurrent columns, one has to describe the reactive equilibria involved, based on Gibbs excess modeling, mass transfer, and diffusive resistances, as well as complex formation involving aqueous electrolytes and organic species. The column hydrodynamics is an additional item to be taken into account (Bart 2003). RE can be categorized into liquid-liquid extraction and liquid-solid extraction. In liquid-liquid RE, a second liquid phase or solvent is added into the reaction system. In general, this exhibits high miscibility and selectivity with the intermediates or products of the reaction, so that they can be continuously extracted from the reaction as soon as they have been generated. It must be chemically inert and highly immiscible toward the reactants in order to avoid undesired side reactions. Removal of products prevents further reactions and, therefore, a reduction in the yield of desired products. Solid-liquid RE involves the extraction of materials from the solid into the liquid phase, where they react and create the products wanted. For example, solid biomass often contains several useful raw materials such as lipids, proteins, fatty acids, and hydrocarbons, which can be processed to valuable products after being extracted. The kinetics of solid-liquid RE can be increased through the addition of an appropriate catalyst. Datta et al. (2015) reviewed the applications of RE in organic chemistry and biochemistry, Bart (2005) in hydrometallurgy, and Boodhoo and Harvey (2013a,b) in green chemistry. Mizzi et al. (2017) developed a general design methodology for the reactive liquid-liquid extraction, which is composed of three steps: feasibility analysis, predesign determination, and simulation validation. Their paper focused on the first two steps. The authors adapted a calculation procedure by Samant and Ng (1998) for the design of a reactive liquid-liquid column. The feasibility analysis allows verifying that the separation specifications are thermodynamically feasible. The reactive liquid-liquid diagram and the reactive extractive curve map were employed as tools for the feasibility analysis. In the second predesign step, a column configuration is determined that allows to achieve the separation goals. Additionally, the structural parameters of the column are determined. The validation steps allow validating the previously determined configuration of the column. This procedure was applied to different reactive systems with different strategies and numbers of compounds with succinct acid and leads to the design of an RE column. Thakre et al. (2016) studied RE of citric acid from dilute aqueous solutions using three different extractants. The linear solvation energy relationship model was successfully applied in that paper to predict the distribution coefficients. The process was optimized by a differential evaluation procedure, which is based on a genetic algorithm (Kumar et al. 2011a). Wasewar et al. (2004) reviewed the fermentation of glucose to lactic acid coupled with RE.

Reactive crystallization (RC) or precipitation is an important production step for many chemical and pharmaceutical industries to produce solid particles with desirable characteristics, such as high purity, large crystal size, narrow crystal size distribution (CSD), enantiomeric purity (Berry and Ng 1997, Yu et al. 2007b, Beckmann 2013, Lewis et al. 2015). RC combines the typical phenomena in crystallization, namely nucleation and crystal growth with chemical reaction. Zimmermann et al. (2015) investigated sodium chloride (NaCl) nucleation from supersaturated brines using seeded atomistic simulations, polymorph-specific order parameters, and elements of classical nucleation theory. The authors found that NaCl nucleates via the common rock salt structure. Ion desolvation was identified as the limiting resistance to attachment. The simulations were performed at realistic supersaturations to enable the first direct comparison to experimental nucleation rates for this system. Berry and Ng (1997) presented a systematic method to synthesize RC processes. It showed how to selectively crystallize a desired solid product after a reaction step and how to use compound information to effect separation of a mixture. The method is based on the generation of phase diagrams with liquid-phase reactions. Using transformed coordinates, systems with three or fewer degrees of freedom can be conveniently analyzed, regardless of the number of components and reactions. Features of the solid-liquid phase diagram that are relevant to process synthesis were identified. Li et al. (2012) analyzed the problem of particle size distribution of precipitation products resulting from inhomogeneous micromixing during RC. Wang and Ward (2015) studied conceptual methods for the rapid development of operating recipes for seeded batch RD processes using two case studies: production of barium sulfate and production of l-glutamic acid (LGA), which are model systems for RC that are widely studied in the literature. Seed loading analysis predicted that nucleation can be effectively suppressed by seeding for the LGA process, but not for the barium sulfate process. These results were supported by rigorous numerical simulations. Sarkar et al. (2007) demonstrated the potential for multiobjective optimization for a semibatch RC process. A genetic algorithm was used to obtain the Pareto-optimal solutions for constrained multiobjective optimization problems that are related to the quality of product CSD in reactive crystallizers. Insights and guidelines were obtained regarding the optimal operation of the crystallizer to obtain crystals of desired characteristics. Su et al. (2014) derived a mathematical model for semibatch pH-shift RC of LGA that takes into account the effects of protonation and deprotonation in the species balance of glutamic acid, CSD, polymorphic crystallization, and nonideal solution properties. The kinetic parameters were estimated by Bayesian inference from batch experimental data collected from the literature. Probability distributions of the estimated parameters, in addition to their point estimates, were obtained by Monte Carlo simulations. The first-principles model was observed to be in good agreement with experimental data. This model may be used for robust control strategies. Alatalo et al. (2010) developed a feedback control process approach for semibatch precipitation that allows control of both the form of the polymorphs and the CSD. The effectiveness of the use of an ultrasound probe for start-up of a crystallization process producing ammonium sulfate crystals from aqueous solution in a 75-l crystallizer was investigated by Lakerveld et al. (2011). Quantification of the number of produced crystals with ultrasound revealed the importance of ultrasonic power input, insonation time, and the geometry of the insonated volume. Devices for RC PI, like the spinning disk reactor, will be discussed below.

2.3.4 Reactive distillation

RD, sometimes called catalytic distillation, is a combination of reaction and distillation in a single column. The reactants are converted with simultaneous separation of the products and recycling of unused reactants. This implies that the boiling points of the reactants must be different from those of the reactants. By continuously removing the products, RD makes it possible to use only the stoichiometric reactants ratio and to pull the equilibrium to high conversions (see Figure 21) (Harmsen 2007).

(A) Reactive distillation column (RDC); (B) RDC with double reactive sections.
Figure 21:

(A) Reactive distillation column (RDC); (B) RDC with double reactive sections.

It is one of the most important industrial applications of PI. The reactions in RD include heterogeneous catalysis reactions, homogeneous catalysis reactions, and thermal noncatalytic reactions. In almost all cases, reactions take place in the liquid phase. Although already known in the 1920s, industrial application of RD did not take place before the 1980s. Eastman Chemical Co.’s methyl acetate RD process and the production of fuel ethers were the first large-scale RD processes. The Eastman process used 80% less energy at only 20% of the investment costs (Luyben and Yu 2008). Today, RD is utilized for processes like esterification, transesterification, hydrolysis, etherification, hydrogenation, dehydrogenation, alkylation, metathesis, carbonylation, polymer production, acyloxysilanes production, chlorination, nitration, amination, carbonates production, and chiral separations (Harmsen 2007, Kiss 2014a,b). All these reactions are limited by chemical equilibria. RD has several advantages (Taylor and Krishna 2000, Tuchlenski et al. 2001, Sundmacher and Kienle 2002, Noeres et al. 2003):

  • Reduction in capital investment, because two process steps are carried out in the same device.

  • Exothermic heat of reaction is used for vaporization of liquid.

  • Avoidance of hot spots and runaways using liquid vaporization as thermal fly wheel.

  • Conversion of reactants is improved due to overcoming of chemical and thermodynamical equilibrium limitations.

  • Selectivity is increased through suppression of undesired consecutive reactions; therefore, by-product formation is reduced. Products are removed fast from the reaction zone.

  • Azeotropes may be avoided by “reacting away” the azeotropes, but one should keep in mind that reaction can induce the formation of azeotropes that were not there to begin with (Song et al. 1997, Ravan 2013, Skiborowski et al. 2013).

  • If the reaction zone in the RD column is placed above the feed point, poisoning of the catalyst can be avoided, which results in a longer catalyst lifetime compared to conventional systems.

RD technology is applicable only if the temperature window of the vapor-liquid equilibrium matches the reaction temperature. CDTECH and Sulzer are the major commercial RD process technology providers. Over 200 commercial-scale processes have been installed up to now. The RD process design starts with a feasibility study (Malone and Doherty 2000, Tuchlenski et al. 2001). This study investigates the feasible product compositions from an RD for a given feed, column pressure, and Damköhler number. The analysis must incorporate all of the features for ideal and azeotropic mixtures, as well as phenomena caused by the introduction of chemical reactions. Various process synthesis approaches are available to determine whether the desired process can be performed as RD (Subawalla and Fair 1999, Taylor and Krishna 2000, Sundmacher and Kienle 2002, Kenig and Gorák 2007, Ahmadi et al. 2010, Altman et al. 2010, Huang et al. 2010, Segovia-Hernández et al. 2015, among others). The design of an RD is quite complex due to the strong interaction of chemical reactions and heat and mass transfer. Segovia-Hernández et al. (2015) have provided a review on current applications of deterministic and stochastic optimization techniques for the design of RD. The optimal design of RD systems is a highly nonlinear and multivariable problem, with the presence of both continuous and discontinuous design variables. The objective function used as optimization criterion is generally nonconvex with several local optima and subject to several constraints. Therefore, global optimization algorithms are needed. Simulated annealing algorithms are in use for such purposes (Segovia-Hernández et al. 2015). Aneesh et al. (2016) highlight the advantages of simultaneous design and control of RD processes. They proposed a mixed-integer dynamic optimization (MIDO) approach (Flores-Tlacuahuac and Biegler 2007) with combined control structure selection and tuning parameters with process design. This method has the capability to deal with both linear and nonlinear systems. But before applying this method with nonlinear systems, prior investigations are required on parameter uncertainty and external disturbances. Applying MIDO leads to a stochastic and large-scale MINLP problem, which is difficult to handle numerically. Huang et al. (2010) established a fundamental principle for PI in RD columns through deliberate consideration of internal mass integration and internal energy integration between the reaction operation and the separation operation involved. For RD processes with highly thermal effect, PI can be achieved with an exclusive consideration of internal energy integration between the reaction operation and the separation operation involved. However, in the presence of a highly endothermic reaction, if it features an extremely low reaction rate and/or small chemical equilibrium constant, internal mass integration has also to be considered between the reactive section and the stripping section of the RD column. For RD columns involving reactions with negligibly or no thermal effect, PI can be performed with an exclusive consideration of internal mass integration between the reaction and the separation, while for moderately thermal effects, a careful trade-off between mass integration and internal energy integration has to be conducted. The authors applied their concept to several examples. Wang et al. (2010) explored the impact of operating pressure on PI for RD columns. The authors identified three specific situations. For reversible endothermic reactions in RD columns, PI can be reinforced between the reaction operation and the separation operation involved, because increasing operating pressure enhances reactant conversion and reaction heat load. In the case of equilibrium-limited exothermic reactions, PI can be reinforced between the reaction and separation, because decreasing operating pressure leads to increased reactant conversion and reaction heat load. For RD involving kinetically controlled exothermic reactions, PI can be profitably employed if the operating pressure is appropriately selected such that reactant conversion and reaction heat load are maximized. Keller et al. (2013) optimized RD for multiple-reaction systems by using an evolutionary algorithm. Thereto, a multiobjective optimization study was performed to determine the Pareto-optimal combinations of ethyl-methyl carbonate, selectivity, and dimethyl carbonate (DMC) conversion that can be obtained in the pilot-scale RD column. The results showed that diethyl carbonate (DEC) can be produced in the pilot-scale RD column with a selectivity of 90% with respect to DEC, while still having reactant conversions of ethanol (ETOH) and DMC of 77% and 86%, respectively. Subawalla and Fair (1999) discussed guidelines for solid-catalyzed RD systems. The guidelines were used to generate initial estimates for column pressure, reactive zone location, catalyst mass, reactant feed location, reactant ratio, reflux ratio, column diameter, number of equilibrium stages, and packed height. They formed a part of a methodical design procedure that made extensive use of both nonequilibrium (rate-based) and equilibrium-stage simulation models. The guidelines were tested for two etherification systems and experimentally validated for a hydration reaction. It was found that column diameter depended both on maximum vapor velocity and on packing catalyst density, reactant ratios were a function of conversion and azeotrope formation, and the operating pressure affected the relative volatility, chemical equilibrium, and reaction rate. The reflux ratio had an impact on separation and conversion.

A large part of the literature on RD has a focus on modeling RD columns. Taylor and Krishna (2000) presented an extensive review of modeling RD. Kenig and Gorák (2007), Noeres et al. (2003), and Ahmadi et al. (2010), among others, reviewed RD modeling papers. RD occurs in multicomponent and multiphase systems, with heat and mass transfer at interphases and inside phases. Additionally, one or several, mostly reversible, reactions are involved. Complex hydrodynamics and multicomponent diffusional processes occur. Therefore, RD models are inherently very complex and require elaborate numerical methods. In practice, RD models are split into several submodels, which describe a part of the problem. Subproblems are, for example, heat and mass transfer models, chemical reaction kinetics, hydrodynamics, thermophysical models of the multicomponent systems, and Stefan-Maxwell approach for the multicomponent diffusion. Mass transfer can be described on rate-based methods. For heterogeneously catalyzed systems, phenomena inside the particles have to be described, that means the intrinsic kinetics, multicomponent diffusion phenomena, and reaction heat transport. Wetting of the outer surfaces of the particles is also a modeling problem. The hydrodynamics are often simplified by dispersion models, liquid holdup, and pressure drop simulations. Equilibrium stage models, extended by chemical reaction equilibria for fast reactions and augmented by correlation parameters, like tray efficiencies of HETS, result in a simple RD model. The numerics are ordinary or partial differential equations and algebraic equations for the thermophysical relations. One obtains a differential-algebraic system of equations. However, diffusional interactions of the multicomponent diffusional interactions cause unpredictable behavior of the tray efficiency factors, which show a strong dependency on the component concentration. Mass transfer acceleration due to chemical reactions in the interfacial regions is often described by enhancement factors (Fogler 2016). A more sophisticated way to describe column stages is the rate-based approach (Seader 1989), which directly takes into account the actual rates of multicomponent mass and heat transfer and chemical reactions. Mass transfer at the vapor-liquid interface can be described using the film model or the penetration/surface renewal model (Westerterp et al. 1988), whereas the model parameters are estimated via experimental correlations. Multicomponent diffusion in the films can be rigorously described by the Stefan-Maxwell approach. Vapor-liquid equilibria are calculated by thermodynamic models, such as non-random two liquid model, universal quasichemical equation, or statistical associating fluid theory equation (Kontogeorgis and Folas 2010, Sandler 2011, Gmehling et al. 2012), whereas the heat transfer coefficients can be determined using the Chilton-Colburn analogy (Aris 1989). Finally, one obtains mass and heat balance equations with mass transfer and reaction coupling expressions. Fluid flow, which is often nonideal in catalytic packings, has to be modeled too. Details may be found in the papers mentioned above.

Yu et al. (2014) and Kaymak et al. (2017), among others, have investigated RD columns with double reactive sections. Yu et al. (2014) have proposed this column for the separations of two-stage consecutive reversible reactions. The arrangement of two reactive sections (see Figure 21B) provides more degrees of freedom for the coordination of the two reaction operations involved and the reinforcement of internal mass integration and/or internal energy integration between the reaction operations and separation operations. The columns with double reaction zones require less investment and operating cost than equivalent columns with one reacting zone. As an example, for a reaction scheme to be operated in a double reaction zone column, the trans-esterification of DMC with ETOH to produce DEC and MEOH was chosen. The reaction scheme is as follows:

DMC+ETOHEMC+MEOH

EMC+ETOHDEC+MEOH

EMC=ethylmethyl carbonate intermediate.

The synthesis and design of the double reactive sections column in question has been given by Yu et al. (2014). Kaymak et al. (2017) have designed several alternative control structures for columns with double reaction sections and compared their robustness based on dynamic simulations. The results have shown that direct composition control is necessary. The authors could demonstrate that two temperature controllers and two composition controllers provide a robust control in terms of steady-state deviations and settling time of product purities.

Kookos (2011) developed a superstructure-based mixed-integer nonlinear model of an ideal RD column and employed it for steady-state optimization and optimal design. Additionally, the optimal point of operation was discovered quite easily and effectively, avoiding the exhaustive enumeration used in previous works. A systematic methodology was applied in order to develop an effective control structure that satisfies product purity constraints at steady state and minimizes the economic penalty associated with product overpurification.

A review of industrial applications of RD has been presented by Hiwale et al. (2004) (see also Kiss 2014a,b). An important problem is the internals of RD columns. A large European project, INTENT (Intelligent Column Internals for Reactive Separations), aimed at fundamental improvement of column internals. The results are presented in a special issue of Chemical Engineering and Processing (Volume 44, 2005). The key theoretical innovation has been the application of CFD software in combination with rigorous, rate-based process simulation. The project resulted in a software tool for internal preselection, ADVISER; a software tool for the fluid flow and reaction simulation, CFX-INTINT; and a rate-based flow simulator, PROFILER. All models were experimentally verified for five reactions in pilot plants. The details have been described in the special volume mentioned above. Discussions of scale-up problems for RD columns may be found in the book by Sundmacher and Kienle (2002).

Besides the standard design of RD columns, there are special designs, for example, horizontal RD for multicomponent chiral resolution. Au-Yeung et al. (2013) have proposed a novel horizontal RD apparatus and a new overall process scheme for continuous multicomponent chiral resolution via reversible enantioselective acylation of a chiral substrate by a chiral acyl donor. The process enables simultaneous production of up to four enantiomers with enhanced chiral purity. The horizontal RD vessel was employed to provide a longer liquid-phase residence time needed for adequate conversion. Low vapor-traffic pressure drop allows operation under vacuum at reduced temperatures for good enzyme stability and enantioselectivity. The general technology has potential as a means to producing a wide range of chiral synthons used in asymmetric syntheses of chiral pharmaceuticals and other biologically active products.

An industrial view of reactive separations has been presented by Stankiewicz (2003), Kiss (2014a,b), Harmsen (2007, 2010), and Tuchlenski et al. (2001), among others.

2.3.5 Membrane separations and hybrid separations

A membrane is a barrier that separates and/or contacts two different regions and controls the exchange of matter and energy between the regions. The membrane can be a selective or a contacting barrier. In the first case, it controls the exchange between the two regions adjacent to it in a very specific manner. In the second case, its function is mainly to contact the two regions between where the transport occurs (see Figure 22).

Membrane separation principle.
Figure 22:

Membrane separation principle.

A membrane may be solid or liquid, homogeneous or heterogeneous, isotropic or anisotropic in its structure. A membrane can be a fraction of a micrometer or several millimeters thick. Its electrical resistance can vary from millions of Ohm to a fraction of an Ohm. Membranes are permselective, which is determined by differences in the transport rates of various components in the membrane matrix. The permeability of a membrane is a measure of the rate at which a given component is transported through the membrane under specific conditions of concentration, temperature, pressure, and/or electric field. The transport rate of a component through a membrane is determined by the structure of the membrane, by the size of the permeating molecules, its geometrical structure, and the possible electrical charge of the molecule and/or of the membrane. The selectivity of the membranes is determined by their pore radii distribution for porous membranes (see Figure 23).

Ranges of pore sizes in membranes and their respective processes.
Figure 23:

Ranges of pore sizes in membranes and their respective processes.

For polymer membranes, the solute solubility is of importance. Ultrapure hydrogen may be produced by palladium membranes. From an economic point of view, the flux through the membranes is of importance. Selectivity and flux often conflict sharply with each other. Membrane technology has been compiled in many books, for example, Bungay et al. (1983), Drioli and Barbieri (2011), Drioli et al. (2011), Scott and Hughes (2013), Mulder (2012), Marcano and Tsotsis (2002), Strathmann (2011), Drioli and Curio (2007), and Basile (2013). They can be tailored and adjusted to specific separation tasks. Membrane processes meet the requirements of PI because they can, in many cases, replace conventional energy-intensive techniques to accomplish the selective and efficient transport of specific components and to improve the performance of reactive processes. Energy requirements, easy control and scale-up, large operational flexibility, low capital and operating costs, and good stability under operation conditions are further advantages of membrane processes. At present, membrane techniques are essential to a wide range of applications, including the production of potable water (Alzahrani and Mohammad 2014), remediation of textile effluents (Van der Bruggen et al. 2004, Dasgupta et al. 2015), lactic acid production (Pal et al. 2009), biotechnology (Rios et al. 2007, Sirkar et al. 2015), membrane distillation (MDi) (Alkihudhiri et al. 2012), MRs (Dautzenberg and Mukherjee 2001, Marcano and Tsotsis 2002, Drioli et al. 2012, Brunetti et al. 2017), membrane crystallizers (Pramanik et al. 2016), seawater desalination (Elimelech and Phillip 2011), gas separation (GS) (Bernardo et al. 2009), food industry (Mohammad et al. 2012), etc.

Membranes are made of various materials like polymers, ceramics, carbons, zeolites/MOFs, oxides (alumina, titania, and zirconia), and metals (palladium, silver, and alloys). Porous and nonporous polymer membranes are employed for GS, reverse osmosis (RO), nanofiltration, ultrafiltration (UF), and microfiltration (Ulbricht 2006). The ceramic membranes are chemically inert and stable at high temperatures. This stability makes ceramic microfiltration and UF membranes suitable for food, biotechnology, and pharmaceutical applications, in which membranes require repeated steam sterilization. Ceramic membranes are also in use in catalytic reactors. Carbon sieve membranes are employed for GS because of their molecular sieving effects. Zeolites are microporous crystalline alumina silicates with uniform pore size. Although they have molecular sieving effects, there is still no GS using zeolite membranes in industrial use (Rangnekar et al. 2015), but they are utilized for drying organic liquids such as ETOH, acetonitrile, glycerol, etc., by steam permeation/pervaporation using Linde Type A (LTA) zeolite membranes. Dry bio-ETOH is mostly produced by pressure swing adsorption (PSA) using 3A zeolites (K+ exchanged LTA). A Japanese institute (Bussan Nanotech Research Institute) developed a Na-LTA zeolite membrane for dehydration of bio-ETOH by a hybrid distillation/vapor permeation process (Sato et al. 2008). In 2012, the Dalian Institute of Chemical Physics installed at Jiangsu Xinhua Chemical Co. Ltd. an LTA zeolite membrane unit for i-propanol dewatering with a capacity of 50,000 tons/year (Rangnekar et al. 2015). Metal-organic frameworks (MOFs) are constructed from metal ions or metal ion clusters and bridging organic linkers. They exhibit, like zeolites, regular crystalline lattices with relatively well-defined pore structures. As yet, more than 20,000 different MOFs have been synthesized. On the laboratory scale, several MOF membranes have been prepared for separation processes, but Qin et al. (2014) state in their comprehensive review that there is still a long way to go in achieving the practical application of MOF membranes in separation processes. Different ways of membrane surface modifications are mentioned in the literature (Rios et al. 2007). Deposition of biopolymers at the membrane surface, covalent attachment of enzymes onto ceramic membranes through glutaraldehyde bonds, and low-temperature-plasma-induced graft polymerization are such surface modifications. Some of these modifications enhance filtration performance. In dense metal membranes, molecular transport occurs through a solution-diffusion mechanism. In particular, in palladium membranes, hydrogen atoms interact with palladium metal. Hydrogen permeation through the membrane is a complex process with stages such as dissociation of molecular hydrogen at the gas/metal interface, adsorption of the atomic hydrogen on membrane surface, dissolution of atomic hydrogen into the palladium matrix, diffusion of atomic hydrogen toward the opposite side, recombination of atomic hydrogen to form hydrogen molecules at the metal/gas interface, and desorption of hydrogen molecules. Palladium membranes allow the production of ultrapure hydrogen.

In general, the solution-diffusion model applies to nonporous membranes (dense metals, ceramics, and polymers) in which separation is a result of differences in solubility and diffusivity of permeates. The solution-diffusion model assumes thermodynamic equilibrium at the membrane interface and both solvent and solute transport through the membrane are driven by chemical potential gradients. No structural information of the membrane is included in the diffusion-solution model. Transport through porous membranes is dominated by size exclusion and is often described by the pore-flow model. This model is based on three assumptions: first, fluids on either side of the membrane are in equilibrium with the membrane at the interface, meaning that there is a continuous gradient of chemical potential across the membrane; second, the solute and solvent activity gradients across the membrane are zero and the chemical potential gradients across the membrane are zero, whereby the chemical potential gradient across the membrane can be expressed as a pressure gradient; third, straight cylindrical pores are assumed across the thickness of the membrane. No other pore structural characteristics (e.g. pore shape, pore radii distribution, and tortuosity) are accounted for. These models and their refined modifications are reviewed, for example, by Wang et al. (2014). More elaborate models are based on the extended Nernst-Planck equation improved by pore size distribution data (Tsuru et al. 1991, Bowen and Welfoot 2002a,b, Mohammad et al. 2015). These models incorporate more physical realism of the membrane process in order to better match measurable parameters. The development of rigorous physical descriptions, such as molecular dynamics simulations, has been limited due to the lack of detailed knowledge of the physical structure and electrical properties of real membranes and process streams. For the hydrogen-palladium system the situation is better. Li and Wahnström (1992) carried out molecular dynamics simulations for hydrogen diffusion in palladium. Only after coupling of hydrogen atoms to the low-lying electron-hole pair excitations among the conduction electrons, close agreement with experimental quasielastic-neutron-scattering data could be obtained (see also Jewell and Davis 2006).

Seawater desalination through membrane technology, and in particular through RO, represents one of the unique successes of membrane technology and is one of the clearest examples of PI (Fritzmann et al. 2007, Dreizin et al. 2008, Elimelech and Phillip 2011). In the coming decades, surging population growth, urban development, and industrialization will increase worldwide demand for fresh water. Early large-scale desalination plants, mostly in the Gulf countries, were based on thermal desalination, where the seawater is heated and the evaporated water is condensed to produce fresh water. Such plants consume substantial amounts of thermal and electrical energy. Therefore, over the last two decades, RO desalination plants have become the leaders in water production from seawater. In RO, seawater is pressurized against a semipermeable membrane that lets water pass through but retains salt. This technology is described in detail by, for example, Fritzmann et al. (2007). The energy consumption of RO plants could be reduced significantly over the last decades. Therefore, the widespread use of RO for desalination is due to its lower energy consumption, higher water recovery factor, and lower cost with respect to thermal plants. Additionally, the less CO2 discharge from the energy consumed and less concentrated brine to be disposed of as waste are further advantages. The lower energy consumption is due to higher-permeability membranes, installation of energy recovery devices, and the use of more efficient pumps. An energy consumption rate of 1.8 kWh/m3 in a modern seawater RO plant could be demonstrated in a pilot-plant at 50% water recovery. The theoretical minimum energy of desalination, for example, for seawater at 35,000 ppm salt and at a typical recovery of 50% is 1.06 kWh/m3. As RO plants do not operate as a reversible thermodynamic process, the actual energy consumption, however, is larger. The energy demand for seawater desalination by state-of-the-art RO is about a factor of 2 of the theoretical minimum energy for desalination. Due to the need for extensive pretreatment and posttreatment steps, the overall energy consumption of new seawater RO plants is three to four times higher than the theoretical minimum energy demand. Therefore, further improvement of seawater RO plants should focus on the pretreatment and posttreatment (brine disposal) stages. Nevertheless, modern seawater RO plants are a real PI success compared to thermal plants. Hagedorn et al. (2017) have developed a seawater desalination plant using MDi. Permeate gap MDi (PGMD) and direct contact MDi (CDMD) spiral wound modules with different channel lengths have been used to evaluate the most suitable module configuration. DCMDi modules have shown a higher flux compared to PGMDi modules; therefore, this configuration has been chosen for further investigations. In order to develop large modules, an upscaling study was performed to reveal possible flow limitations. No limitations could be observed under sufficiently high flow velocities. A first pilot plant desalinating seawater was operated for 9 months to gain experience under real conditions. Fouling is one of the main problems in any membrane separation (van der Bruggen et al. 2008, Mohammad et al. 2015). Classical solutions to fouling are the optimization of pretreatment methods and cleaning of membranes. Suggested pretreatment methods often make use of other pressure-driven membrane separations such as UF and microfiltration. Flocculation, adsorption, sand bed filtration, backflush, forward flush, reverse flush, sonication, air sparging, chemical cleansing, and turbulence promotion by static mixers are further cleaning techniques. Of course, the membrane stability should not be reduced by these methods. Cleaning of groundwater, surface water, and waste water is also in the field of RO applications. Wastewater from textile production can also be cleaned by a combination of ultratiltration/microfiltration and nanofiltration or RO. A major contribution on the total amount of textile wastewater generated is made by the processing stages, which include scouring, dyeing, printing, finishing, and washing (Dasgupta et al. 2015). At present, most investigations on textile waste water were carried out in an academic environment. Fouling problems hampered large-scale industrial applications yet. The situation is different in the food industry (Mohammad et al. 2012). The dairy industry has been one of the pioneers in the development of UF equipment and techniques on the experience gained from its application in the production of cheese. Membrane technology is utilized in the beverage industry for processing a variety of fruit and vegetable juices. In juice clarification, UF can be used to separate juices into fibrous concentrated pulp (retentate) and a clarified fraction free of spoilage microorganisms (permeate). The pasteurized clarified fraction can then undergo nonthermal membrane concentration and, eventually, whole juice reconstitution by combination with pasteurized pulp, in order to obtain a product with improved organoleptic properties. In fish industry, UF is mainly used for fractionation and waste recovery processes. In food industry, membrane processes are advantageous because of their environmental friendliness, cost saving, and product improvement. A multitude of research activities have been carried out for production of lactic acid in fermentative process using cheap, renewable carbon sources (Pal et al. 2009). Lactic acid is the most widely occurring hydroxy-carboxylic acid used as food preservative and acidulent. In several membrane-based studies, successful separation of the components of fermentation by micro, ultra, nano, and RO and electrodialysis membranes has been demonstrated. A combination of microfiltration and nanofiltration might be able to reach commercial production of monomer grade lactic acid. As yet, there seem to be no large-scale membrane plants for lactic acid production.

MDi is a well-known membrane contactor unit (Khayet and Matsuura 2011, Alkihudhiri et al. 2012, Drioli et al. 2012). MDi is a thermally-driven separation process consisting of the combination of water evaporation and vapor condensation in an integrated process. Only vapor molecules are able to pass through a hydrophobic membrane. MDi separation is driven by the vapor pressure difference existing between the porous hydrophobic membrane surfaces. The operating temperatures in MDi are low compared to conventional distillation of evaporation processes as the solution is not necessarily heated up to the boiling point. Moreover, the hydrostatic pressure encountered in MDi is lower than that used in pressure-driven membrane processes like RO or UF. Therefore, the mechanical membrane properties are less demanding. The porous hydrophobic membrane, which is not wetted by the process liquids due to surface tension forces, does not alter the vapor/liquid equilibrium of the involved species. Condensation inside the pores does not occur. A 100% rejection of the nonvolatile solute can theoretically be achieved. Mass transfer in MDi occurs through the pores of the membrane, whereas the heat is transferred through both the membrane matrix and its pores. The heat transfer within the membrane is due to the latent heat accompanying vapor or gas flux and the heat transferred by conduction across both the membrane material and the gas-filled pores. There are boundary layers on the feed and permeate sides of the membrane, giving rise to the so-called temperature polarization and concentration polarization. The transport of gases and vapors through the pores can be described by the Stefan-Maxwell approach. Microporous MDi membranes are available in tubular, capillary of flat sheet forms. Spiral wound membranes are also available. In this type, flat sheet membrane and spacers are enveloped and rolled around a perforated central collection tube. The feed moves across the membrane surface in an axial direction, while the permeate flows radially to the center and exits through the collection tube. Common materials are polytetrafluoroethylene (PTFE), polypropylene, polyethylene, or polyvinylidene fluoride. The pore sizes are larger than in RO, which results in lower fouling problems. In terms of permeate collection and driving force generation, MDi can be classified into four categories:

  • Direct contact MDi, where the hot and cold fluid are in direct contact with the membrane surface. This version of MDi has been widely studied.

  • Vacuum MDi, where a pump is used to create a vacuum in the permeate membrane side. Condensation takes place outside the membrane module.

  • Sweeping gas MDi, where inert gas is used to sweep the vapor at the permeate membrane side to condense outside the module.

  • Air gap MDi, where the feed solution is in direct contact with the hot side of the membrane surface only. Stagnant air is introduced between the membrane and the condensation surface. The vapor crosses the air gap to condense over the cold surface inside the membrane unit. The advantage of this design is the reduced heat loss by conduction.

Although there are hundreds of papers on academic investigations, which show promising results in various applications, only a very few solar-assisted MDi demonstration systems for water production are in operation (Shirazi and Kargari 2015). A comprehensive overview of the MDi technology and its applications has been presented in the books by Khayet and Matsuura (2011) and Drioli and Giorno (2010).

Far better, with respect to industrial applications is the situation for GS in the chemical industry (Bernardo et al. 2009). A prominent example is hydrogen recovery as a first large-scale commercial application of membrane GS technology (Ockwig and Nenoff 2007). Currently, the most important membrane applications in the petroleum industry are employed in nitrogen production, hydrogen recovery, natural gas sweetening, nitrogen removal, enhanced oil recovery via CO2, monomer recovery in polyolefin production, pervaporation processes, and organic solvent nanofiltration. The commercial success of membrane technology started in the mid-1970s of the Permea polysulfone hollow-fiber prism system for in-process recycling of hydrogen from ammonia purge gases. As the ammonia reactor operates at 130 bar, the necessary driving force for N2/H2 separation is available. This technology has been extended to H2/CO or H2/CH4 separations. Hydrogen demand is increasing owing to new environmental regulations. Hydrotreating, hydrocracking, and hydrodesulfurization are typical hydrogen consumers. The investment costs for membrane processes are lower compared to PSA or cryogenic separation. Polyimide membranes are successfully applied for H2 recovery in refineries due to their stability and high separation factors (H2/N2 ~100–200). Hydrogen production in an MR and integrated GS reduces the energy consumption and investment costs. An example mentioned in an edited book by Drioli and Barbieri (2011) is presented in Figure 24, where a conventional production plant and an intensified hydrogen production plant are compared.

Hydrogen production from natural gas; (A) conventional plant; (B) integrated membrane plant (Drioli et al. 2012).
Figure 24:

Hydrogen production from natural gas; (A) conventional plant; (B) integrated membrane plant (Drioli et al. 2012).

One of the largest membrane processes in use is the nitrogen production from air. Membranes are dominating applications of less than 50 tons/day and relatively low purity (0.5–5% O2). Thousands of compact on-site membrane systems generating nitrogen gas are installed in offshore and petrochemical industry. Mostly, single-stage membrane operation is employed. Air is pressurized and fed into the membrane separators where the “faster” gases O2, CO2, and H2O vapor permeate through the polymeric fibers. These gases are collected and vented to the atmosphere, while the slower, nonpermeate N2 is available at the other end of the separator. Nitrogen is used to prevent fires and explosions in tanks and piping systems and to prevent equipment degradation during shutdown periods, in compressors, pipelines, and reactors.

Since CO2 reduces the heating value of natural gas, is corrosive, and freezes at relatively high temperature, forming blocks of dry ice that can clog equipment lines and damage pumps, CO2 removal from natural gas is mandatory. Membrane technology is possible for CO2 and H2S separations as the high wellhead gas pressure can be used as driving force for separation, and many membrane materials are very permeable to these species. For example, cellulose triacetate (Cynara-NATCO) is taken in hollow-fiber modules. PRISM (Air Products) is another commercial membrane for CO2/H2S removal. Membrane systems are typically installed for small size applications (less than 6000 Nm3/h) and remote locations. Further applications may be found in the paper by Bernardo et al. (2009).

A combination of distillation or reaction with pervaporation to form a hybrid separation process is an attractive PI process, as reduction of energy consumption, improvement of product quality, and less investment costs can be achieved. An example of a combination of distillation with pervaporation is presented in Figure 25 (Lipnizki et al. 1999, Suk and Matsuura 2006, Gorák and Stankiewicz 2011).

Hybrid process combining distillation with pervaporation for a binary system with a low-boiling azeotrope.
Figure 25:

Hybrid process combining distillation with pervaporation for a binary system with a low-boiling azeotrope.

Dehydration of solvents is the mostly used industrial hybrid separation process for drying organic solvents, such as alcohols. A combination of RD and membrane separation is also possible (Buchaly et al. 2007). Figure 26 (Bengtson et al. 2002) presents a hybrid process in which hydrogen and 4-chlorphenol (0.5% in H2O) react in a poly(ether-b-amide) (PEBA) membrane, with palladium nanoclusters as catalytically active material inside the membrane, to form phenol.

Catalytic pervaporation of 4-chlorophenol/Pd/Rh (Bengtson et al. 2002).
Figure 26:

Catalytic pervaporation of 4-chlorophenol/Pd/Rh (Bengtson et al. 2002).

The elastomer PEBA is known as a polymer that effectively concentrates slightly polar chemicals such as phenols, higher alcohols, and the like from water. The reactive pervaporation enriched and simultaneously hydrated 4-chlorophenol compared to the feed. The enrichment factor has been 100. A careful selection of the membrane thickness, temperature (~30°C), and Pd particle size is essential.

MRs are so-called multifunctional reactors which are useful unit operation in PI, for example, in chemical and petrochemical industry, biotechnology, energy conversion, etc. Due to their multifunctionality in one unit operation, they fulfill PI requirements like lower investment costs, lower energy consumption, lower volume occupied, lower material consumption, higher conversion and/or selectivity, etc. MRs are capable of carrying out chemical reactions and separation in the same unit. The membrane selectively removes one or more products from the reaction mixture, or distributes and controls the addition of reactants in the reactor volume, or improves the contact among reactants and catalyst or nonmiscible phases. Combinations of these functions are also possible. The membranes can be selective or nonselective, with or without catalytic activity. There are many configurations of MRs to combine the membrane separation module and the reactor into a single unit. Marcano and Tsotsis (2002) have classified these configurations for catalytic MRs into six basic types:

  • Catalytic MR

  • Catalytic nonpermselective MR

  • Packed-bed MR (PBMR)

  • Packed-bed catalytic MR (PBCMR)

  • Fluidized-bed MR

  • Fluidized-bed catalytic MR

The most commonly utilized catalytic MR is the PBMR (see Figure 27A).

Catalytic membrane reactors: (A) catalytic packed bed, inert membrane; (B) catalyst membrane.
Figure 27:

Catalytic membrane reactors: (A) catalytic packed bed, inert membrane; (B) catalyst membrane.

The reaction is carried out in the packed bed of catalyst particles placed inside a membrane tube. One or more products, depending on the membrane properties, are separated by the membrane. For reversible reactions, the conversion can be increased owing to removal of products (circumventing equilibrium limitation). The membrane can be inert or also catalytically active to provide an additional catalytic function for further reactions (PBCMR). In biotechnology, reactive membrane extractors are in use, where the membrane removes inhibitory products. Dissolved biocatalysts may be flushed along the membrane or segregated within the membrane module. Immobilization (adsorption, ionic binding, covalent binding, or molecular recognition) of the biocatalyst onto the membrane is also possible. The MR may be operated as a sidestream membrane unit outside the bioreactor or as a submerged MR inside the bioreactor. The submerged membrane unit may be also put into a separate tank outside the bioreactor tank. This is the preferred version in waste water treatment because bioreactor tank and membrane tank can be optimized independently, with practical advantages for operation and maintenance.

PBMRs are often designed by one-dimensional pseudo-homogeneous models for the packed bed, whereby the mass-flow of products through the membrane is included in the mass balances of the components withdrawn by the membrane. The Ergun equation can be employed for pressure drop calculations along the tube. More elaborate CFD simulations are, of course, also possible. Heat balances for the reactions are coupled to the mass balances (see Tóta et al. 2007).

In catalytic MR, the membrane acts as a catalyst support and as a separation layer (see Figure 27B). Coating the surface of a dense membrane by catalytically active material is also possible. Both polymeric and inorganic catalytic MRs have been used. Bhat and Sudhukhan (2009) have presented a comprehensive overview of PI aspects for steam methane reforming using membranes. Further applications of MRs have been listed by Brunetti et al. (2017), Dautzenberg and Mukherjee (2001), Bengtson et al. (2002), Basile (2013), Basile and Charcosset (2016), Drioli et al. (2012), Marcano and Tsotsis (2002), and Basile and Gallucci (2011), among others. Diban et al. (2013) have reviewed investigations of MRs for in situ water removal during catalytic reactions in the food, pharmaceutical, cosmetics, and petrochemical sectors. The most comprehensive studies on water removal with MRs have been performed in esterification reactions.

Porous catalytic membranes may be also used as catalyst supports without separating function (see Figure 28).

Convective flow in catalytic membranes (Fritsch et al. 2004).
Figure 28:

Convective flow in catalytic membranes (Fritsch et al. 2004).

The reactants are pressed through the cylindrical catalytic membrane having large pores. This results into rather large fluxes, which are controllable by setting the proper pressure drop over the membrane. The advantages of this mode of operation is the controllable catalyst contact time, which is useful for consecutive reactions, and a smaller amount of catalyst for a given conversion owing to the convective flux inside the pores instead of almost uncontrollable diffusional transport (Fritsch et al. 2004). Modeling of such reactors may be found in Garayhi et al. (1998).

In general, it is noticeable in PI by means of membranes that, except for the few applications mentioned above, academic investigations predominate work on membranes compared to industrial applications.

2.3.6 Continuous chromatography

A combination of continuous separation and reaction is the simulated moving bed reactor (SMBR). This technology allows the integration of reaction in the merely separative simulated moving bed (SMB) process. SMB provides continuous operation of normally discontinuous chromatography. The combination with reaction enables overcoming equilibrium reaction limitations or achieving thermal coupling (Lode et al. 2001). A comprehensive book by Rodrigues (2015) and Ludanes et al. (2013), and reviews by Gomes and Rodrigues (2012), Lode et al. (2001), and by Juza et al. (2000) demonstrate the features and applications of this technology. Modeling of SMBs has been described by Johannsen (2007). Broughton and Gerold (1961) introduced SMB by a first universal oil products (UOP, American company) patent. This technology was originally developed in the areas of petroleum refining and petrochemicals and become known as the Sorbex process (Parex/Molex Process) licensed by UOP. The idea behind SMB is depicted in Figure 29A.

(A) A four-section simulated moving bed (SMB) unit rhs: conc. profiles of A and B in zones; (B) schematic representation of an SMBR unit with four sections and three columns per section considering a reaction of type A+B⇔C+D, in which C is the less-adsorbed product and D is the more adsorbed one (Rodrigues 2015).
Figure 29:

(A) A four-section simulated moving bed (SMB) unit rhs: conc. profiles of A and B in zones; (B) schematic representation of an SMBR unit with four sections and three columns per section considering a reaction of type A+B⇔C+D, in which C is the less-adsorbed product and D is the more adsorbed one (Rodrigues 2015).

A series of connected columns filled with fixed solid adsorbents is used. To mimic the countercurrent flow of solid and fluid, the positions of the two inlet and the two outlet ports are shifted periodically by one column after a certain shift time in the same direction as the fluid flow. In order to make the discrete movement closely simulate the continuous movement, which is implemented in a true moving bed (TMB), each section of a TMB unit is divided into several subsections. In Figure 29B, three subsections are shown. Owing to its periodic character, the SMB process never settles down into a steady state. However, after a certain number of shifts, a cyclic steady state is reached. This state is characterized by identical concentration profiles in each cycle. an example of internal concentration profiles is presented on the rhs of Figure 29A. These profiles are found in the middle of the shift period. A and B can be collected continuously with high purity at the raffinate and extract ports. Seidel-Morgenstern et al. (2008) summarized the features of classical SMB processes as follows:

  • Constant operating parameters are applied (flow rates, feed concentrations, and column configurations).

  • There are at least four columns in four different zones.

  • Isocratic operation is used (i.e. the same elution strength throughout the entire unit).

  • There are direct connections between the columns.

  • High product purity is the goal.

  • Permanent collection of the products at the raffinate and/or extract ports is realized.

  • Two outlet (product) fractions can be controlled.

In the Sorbex SMB technology, a rotary valve is used to periodically change the position of the eluent, extract, feed, and raffinate lines along the adsorbent bed. At any particular moment, only four lines between the rotary valve and the adsorbent bed are active. Examples from the petrochemical industries are the Parex units for the separation of p-xylene from its isomers on zeolites, the Molex for the separation n-paraffins from branched and cyclic hydrocarbons, and the Olex process to separate olefins from paraffins. The sugar industry employs the Sarex process for the separation of fructose from glucose. SMB is now a well-established technology in the separation of fine chemicals with several SMB units installed in the pharmaceutical industries for the production of single-enantiomer drugs, for example, Bayer, Merck, Carbogen, GlaxoSmithKline, Novartis, Pfizer, and UCB Pharma. Papathanasiou et al. (2017) have developed advanced control strategies of the multicolumn countercurrent solvent gradient purification process, an industrial, semicontinuous, chromatographic process, used for the purification of several biomolecules. The authors have presented a novel control approach that manages to drive the process toward continuous, sustainable operation. The presented controllers have been designed within the Parametric Optimization and Control (PAROC) framework/software platform that enables the development of intelligent, model-based controllers through a step-by-step approach. Since the 1990s, new SMB modes of operation have been developed (Seidel-Morgenstern et al. 2008, Rodrigues 2015). Other companies developed alternative SMB schemes. For example, the Institut Francais du Pétrole (Rueil-Malmaison, France) has introduced a commercial SMB process in which the rotary valve was replaced by a combination of commonly used chromatography columns and commercial valves (Rodrigues 2015). Many new modes of SMB operation have been developed, such as Varicol process, MultiFeed, Outlet Streams Swing, M3C process, and JO process, among others (Rodrigues 2015). Besides separations of binary mixtures, also ternary separators have been investigated (see, for example, Hur and Wankat 2005).

An extension of the SMB is the SMBR, in which the continuous countercurrent chromatographic separation is combined with chemical reaction. It also comprises fixed-bed columns arranged in series and in a close circuit, but these columns are packed with an adsorbent loaded with a catalyst or a mixture of adsorbent and catalyst particles. In the SMBR, instead of feeding the components to be separated, the reactants are fed and react at the catalyst/adsorbent. The products are simultaneously separated and collected in the outlet streams (extract and raffinate) diluted in desorbent (usually one of the reactants is used as desorbent). For instance, if the feed comprised two reactants (A and B), in which A is used as desorbent, and A and B react reversibly to give two products C and D, the latter being more adsorbed than the former, then a mixture of D and A is obtained in the extract and a mixture of C and A in the raffinate (see Figure 29B). The inlet/outlet streams divide the unit into four different sections, each one with a specific role and having a specified number of columns (Rodrigues 2015):

  • Section 1, located between desorbent and extract nodes, in which the solid is regenerated by desorption of the most-adsorbed product (D) using the desorbent (A);

  • Section 2, located between the extract of feed nodes;

  • Section 3, located between the feed and raffinate nodes, in which the reaction takes place and the products (C and D) are separated as they are formed; and

  • Section 4, located between the raffinate and desorbent nodes, in which the desorbent (A), before being recycled to Section 1, is regenerated by adsorption of the less-returned product (C).

Mazzotti et al. (1996) have presented results about esterification of acetic acid with ETOH on a highly cross-linked sulphonic ion-exchange resin (Amberlyst 15) in a continuous SMBR laboratory unit. The resins acted simultaneously and effectively both as a catalyst as well as a selective sorbent. This allowed obtaining reaction products of high purity and, since the reaction is equilibrium limited, to achieve greater conversion with respect to that attainable without separation. The thermodynamic and kinetic descriptions of the system have been combined to develop a fully predictive mathematical model of the chromatographic reactor. Qamar et al. (2017) have derived analytical solutions and moments of a two-dimensional linear general rate model to simulate a single-solute transport in the chromatographic columns of cylindrical geometry. The derived analytical solutions were compared for verification with the numerical solutions of a high resolution flux limiting finite volume scheme. Typical case studies were analyzed (see also Qamar et al. 2016, 2014). Bashir et al. (2017) analyzed a linear general rate model of two-component liquid chromatography considering heterogeneous reactions of types A→B and A⇔B. The model equations incorporate axial dispersion, external and intra particle pore diffusion, interfacial mass transfer linear sorption kinetics, and first-order heterogeneous chemical reactions. Coupling of a flow reactor with SMB chromatography has been reported (O’Brian et al. 2012). The system can be operated continuously to provide the target compound in high yield.

Modeling of SMBs (Johannsen 2007) and SMBRs (Lode et al. 2001, Ströhlein et al. 2005, Rodrigues 2015) has been subject of intensive research over more than 50 years. Models of SMBs are based on the following assumptions:

  • An axially dispersed plug flow model is used to describe the fluid flow.

  • A plug flow model is used to represent the countercurrent solid flow in the TMB approach. Dispersion models are sometimes also in use.

  • The adsorbent particles are considered homogeneous and mass transfer between fluid and solid is described by the linear driving force model.

  • The model can handle any kind of adsorption equilibrium isotherm.

  • Isothermal operation.

  • No bed radial concentration gradients.

  • Constant fluid velocity.

  • Uniform particle size.

The model equations for the real SMB result from the mass balances over a volume element of the bed and at a particle level (Rodrigues 2015). A critical evaluation of assumptions made in SMB and SMBR models has been presented by Tondeur (1995). SMBRs require kinetic models for the chemical reactions. Constant operating temperature has to be checked. Rodrigues (2015) has described case studies of ethyl lactate and acetals production in SMBRs. The experiments and modeling activities needed are explained in detail.

2.3.7 Dynamic operations and multiphase reactors

The possibilities of PI due to instationary operation have been known for decades (Boreskov and Matros 1983, Silveston et al. 1995, Zhdanov 2004, among others). Periodic operation of catalytic reactors, multifunctional autothermal reactors operated in countercurrent or reverse-flow, periodically operated trickle-bed reactors, periodic temperature forcing of catalytic reactions, oscillatory flow continuous reactors, pulsed bubble columns, and cyclic distillation are typical examples. These modes of operation lead to higher yields, higher selectivities, and lower energy consumption.

In order to improve the reaction performance, e.g. to increase the reaction rate or selectivity with respect to desired products, large temporal perturbation of conventional (stable) kinetics via variation of reactant pressure, temperature, and feed composition of flow reversal has been studied in chemical engineering for decades (Matros and Bunimovich 1996, Matros 1996, Silveston and Hanika 2002, Emig and Liauw 2002, Zhdanov 2004). Bailey and Horn, Zolotarskii and Matros, Renken, Mordvintsev, and Si and Blackburn have published simple kinetic models that have illustrated the effect of periodic perturbation of reactant concentration on the reaction selectivity and yield (Zhdanov 2004). Zolotarskii and Matros have demonstrated that, for their proposed reaction scheme, the reaction selectivity may have a maximum at an optimal frequency comparable with the characteristic response time. Kinetic models to illustrate the benefits of periodic perturbation of reactant concentrations on the performance of catalytic reactions usually include only elementary steps forming a catalytic cycle, which runs often quite rapidly. Accordingly, one can hardly reach beneficial unsteady-state regimes especially if reactions are run in a large-scale reactor. In principle, one can employ slow side steps for optimization. Mordvintsev and Zhdanov (see Zhdanov’s review 2004) have introduced a model that uses side steps for investigations. Many mechanistic concepts presented in the literature do not describe in detail real reactions. The rate constants employed in such models are often considered to be free parameters and are chosen such that the effects predicted are large. Response to bistable reactions, such as CO oxidation on platinum, and spatiotemporal phenomena have been described by Zhdanov (2004), Larter and Showalter (2007), Ertl (2009), and Mikhailov and Ertl (2017) among others. Boreskov and Matros (1983) have outlined the main advantages of unsteady-state operation:

  • Noticeable increases in selectivity and yield are possible.

  • Catalyst provides not only its basic function as accelerator of chemical reactions but also that of a heat regenerator. This allows one to exclude inefficient recuperative heat-exchangers and significantly reduce the reactor cost.

  • Industrial gases with low initial concentrations can be processed without heat expenditure.

  • Owing to the dynamic properties of the catalyst bed in reactors operated in unsteady-state conditions, it is possible to create almost optimal conditions with respect to productivity and selectivity.

Silveston et al. (1995) have presented an overview and introduction into periodic operation of catalytic reactors (see also Silveston and Hudgins 2012). They explain the variables that arise in periodic operation, such as the period, split, amplitude, and phase lag. Several experimental setups and examples have been presented in that paper. Except for off-gas treatment, a wider application of the unsteady-state technologies has not been realized. One of the key problems is that the optimization of full-scale reactors cannot be performed explicitly in experiments. Extensive simulations, based on reliable kinetic and transport data under instationary conditions, are indispensible. A very reliable control of the reactor operation is mandatory. Additionally, one needs buffer tanks to put a damp on oscillations of reactor output.

The catalytic cleaning of petrol or diesel motor vehicle exhaust gas is based on the so-called three-way Pt-Rh catalysts, converting simultaneously the two reducing pollutants, CO, unburned hydrocarbons, and NOx to nontoxic products, such as CO2, H2O, and N2. Rhodium is used as a reduction catalyst, while platinum is employed as an oxidation catalyst. Ceria or ceria-zirconia oxides are added as oxygen storage promoters. The catalytic materials are suspended in a washcoat to disperse the active material over a large surface area. The core, on which the washcoat is distributed, is usually a ceramic monolith with a honeycomb structure. The coat must retain its surface area and prevent sintering of the catalytic metals even at high temperatures (~1000°C). The reduction of NOx and oxidation of CO and hydrocarbons occur most efficiently when the catalytic converter receives exhaust from an engine running slightly above the stoichiometric point. Technologically, this condition is met by using an electronic engine control module, which receives a signal from an oxygen sensor for maintaining at the air/fuel ratio around the stoichiometric setpoint. Owing to the load change of the engine and the time delay in the air/fuel correction, the catalytic process operates inherently in an instationary mode (Güthenke et al. 2007, Chatterjee et al. 2011).

Kolios et al. (2000) explained in detail autothermal fixed-bed reactor concepts. The integration of reaction and heat exchange within one piece of equipment has advantages over the conventional unit operation design: heat losses can be minimized and the reactor is less sensitive to perturbations because of its inherent adaptivity. Autothermal reactors are widespread in industrial applications in the field of waste air purification. The design of autothermal reactors is a nontrivial task because the intrinsic feedback of heat gives rise to a complex parametric and dynamic behavior. A useful application of autothermal multifunctional reactors is the coupling of endothermic and exothermic reactions where the product of the endothermic reaction is the desired one (Haynes et al. 1992, Ercan and Gartside 1996, Kulkarni and Duduković 1996). Kolios et al. (2002) have developed a systematic procedure for analyzing coupling of endothermic and exothermic reactions in one multifunctional autothermal unit. A modified design employing concurrent heat exchange in the catalytic part combined with countercurrent end sections extends the limits of the optimal operating regime substantially. The most flexible design allows for the direct control of the heat release through an axially distributed fuel feed. A novel reactor design, the so-called folded plate reactor, has a separating wall between the exothermic and endothermic compartment. The separating wall consists of a single, folded sheet of metal that forms channels with rectangular cross-sections. The channel width can be made as small as approximately 1 mm, providing optimal conditions for an efficient heat exchange. Both channels are accessible from the side along the entire length of the reactor. The channels are filled with spacers that fulfill multiple functions: they support the channel walls and they act as firs for improving the heat transfer over the separating walls. Furthermore, they can be used as catalyst carriers and as static mixers in order to distribute the side stream uniformly within the main stream. The concept has been tested successfully for steam reforming reactions. Stolte et al. (2013) have introduced a novel form of dynamic operation named pulsed activation method. It can be viewed as a form of periodic operation in which very fast temperature pulsing is used to induce chemical reactions directly and locally as needed. The main goal in this method is to activate catalytic reactions at will and within a time scale such that physical transport related dynamics cannot follow. The CO oxidation over a Pt catalyst has been investigated as a test reaction. It has been observed that the higher the pulse energy, the higher the conversion of CO is. The reaction rate also has increased with increasing pulse frequency.

Beckmann and Keil (2003) could increase the yield of hydroformylation of ethylene to propionaldehyde utilizing a supported-liquid phase catalyst in a fixed-bed reactor by a factor of two. For this purpose, the hydrogen feed was varied in an optimized way whereby the ethylene and CO feed were kept constant. The effect of instationary hydrogen feed on the yield could be explained by means of the Wilkinson cycle. Harvey et al. (2001, 2003) have described an oscillatory flow reactor (OFR) consisting of tubes containing equally spaced orifice plate baffles (see Figure 30) (see also McGlone et al. 2015).

Schematic of oscillatory flow reactor for biodiesel production (Harvey et al. 2003).
Figure 30:

Schematic of oscillatory flow reactor for biodiesel production (Harvey et al. 2003).

An oscillatory motion is superimposed upon the net flow of the process fluid, creating flow patterns conductive to efficient heat and mass transfer, while maintaining plug flow. Unlike conventional plug flow reactors, where a minimum Reynolds number must be maintained, the degree of mixing is independent of the net flow, allowing long residence times to be achieved in a reactor of greatly reduced length-to-diameter ratio. The OFR allows batch processes that need long residence times, like, for example, saponification reactions, to be converted to continuous, thereby intensifying the process. Conversion to continuous processing may improve the economics of suitable processes, as the improved mixing should generate a better product at lower residence time. The tanks-in-series model can be used to describe the OFR, whereby the number of tanks is fitted to experimental data. Harvey et al. (2003) demonstrated the OFR for biodiesel production from rapeseed oil in a pilot-scale plant (see also Qiu et al. 2010). The OFR combines a reduction of reactor volume and a better control of the reaction with enhanced safety and better selectivity and yield. Effective droplet break-up and controlled droplet size in liquid-liquid dispersion are also features of the OFR (Pereira and Ni 2001, Anxionnaz et al. 2008).

Employing a vibration exciter with the proper frequencies improves mass transfer in bubble columns considerably (Krishna et al. 2000, Ellenberger and Krishna 2002, Budzyński et al. 2017) (see Figure 31A).

(A) Bubble column with vibration exciter; (B) Temporal development of air bubbles in water; amplitude of vibrator 1 mm; frequency 200 Hz; initial bubble diameter 5 mm (Kniazev and Keil 2013).
Figure 31:

(A) Bubble column with vibration exciter; (B) Temporal development of air bubbles in water; amplitude of vibrator 1 mm; frequency 200 Hz; initial bubble diameter 5 mm (Kniazev and Keil 2013).

Vibrations of a membrane below the gas sparger with a suitable frequency or intermittently changing frequencies and amplitudes break up bubbles. Additionally, in the liquid boundary layer, the liquid is vigorously moved, which also improves mass transfer. The vibration frequencies preferably should hit the bubble eigenfrequencies to induce their vigorous oscillating movements. Depending on the liquid and gas properties, frequencies in the range between 50 and 500 Hz of the membrane are suitable for that purpose. Owing to Bjerknes forces, which is an additional force opposite to buoyancy, occur in a pulsed bubble column. These forces decrease the bubble velocity toward the top of the column. As the gas/liquid mixture is somewhat compressible, one does not have to accelerate the entire liquid mass inside the column. The energy input needed in a pulsed bubble column is less than in an equivalent gasified stirred tank. Bubble coalescence along the way to the top of the column is avoided (see Figure 31B) (Kniazev and Keil 2013). The larger bubbles break into smaller ones. This maintains the large gas/liquid interface. The pulsed bubble column is particularly useful for fast gas/liquid reactions, like hydrogenation of natural oil to margarine, where the size of the gas/liquid interface is rate determining. This has been demonstrated experimentally. Budzyński et al. (2017) have presented results of mass transfer and gas hold-up data and respective correlations over a wide range of operating parameters.

Forced periodic operation and induction of pulses in trickle-bed reactors can improve yield and avoid hot spots for exothermic reactions (Lange et al. 1994, 1999, 2004, Boelhouwer et al. 2001, Silveston and Hanika 2004, Nigam and Larachi 2005, among others). Trickle-bed reactors have found extensive application in the organic and petrochemical industries. Inducing continuous pulsing flow by fast periodic increases in liquid loading or in gas loading has been demonstrated experimentally. Boelhouwer et al. (2001) have made clear by experiments that by means of periodic operation of the trickle-bed reactor, it is possible to obtain pulsing flow at throughputs of liquid associated with trickle flow during steady-state operation. Enhanced mass and heat transfer rates are then considered to be due to the change in flow regime. This feed strategy to force pulse initiation is termed liquid-induced pulsing flow. The advantages associated with pulsing flow may then be utilized to improve reactor performance in terms of an increase in capacity and the elimination of hot spots, while interfacial contact times are comparable to trickle flow. An additional advantage of liquid-induced pulsing flow is the possibility to time the pulse frequency and, therefore, the time constant of the pulses. Further investigations of this group have been published in a review by Silveston and Hanika (2004). Lange et al. (1994) described the results of experiments of cyclohexene to cyclohexane and α-methylstyrene to cumene on palladium catalysts. Changes in the control variables such as feed composition, feed rate, or temperature were investigated. The aim of the study was to find out the conditions of periodic operation that would enable higher average inlet concentrations without evaporating the feed mixture and to improve time-averaged conversion. For the reaction of α-methylstyrene to cumene, Lange et al. (1999) could demonstrate that under liquid flow interruption, the time average conversion is higher than under steady-state operating conditions. This phenomenon could be explained by a mathematical model presented in their paper. Figure 32 gives an overview on different effects that influence the performance of a trickle-bed reactor (Lange et al. 2004).

Overview of different effects on trickle-bed reactor performance (Lange et al. 2004).
Figure 32:

Overview of different effects on trickle-bed reactor performance (Lange et al. 2004).

A comparison of experimental results with simulations revealed, for the same reaction as mentioned above, that reliable chemical kinetics and mass transfer correlation under respective instationary conditions are absolutely necessary to obtain a good agreement of simulations and experiments. Nigam and Larachi (2005) explained the hysteresis behavior in pressure drop and liquid hold-up in trickle-bed reactors in terms of particle wetting properties. The limits of the present trickle-flow reactor models have been compiled by Lange (2007).

Cyclic distillation emerged as another important trend in PI (Maleta et al. 2011). Essentially, a cyclic distillation column has an operating cycle consisting of two key operations: a vapor flow period, when vapor flows upward through the column and liquid remains stationary on each plate, and second, a liquid flow period, when vapor flow is stopped, reflux and feed liquid are supplied, and liquid is dropped from each tray to the one below (Kiss 2013). As a result, the throughput of such a column using the controlled cycle mode of operation is typically more than two times higher than the conventional throughput. There are several advantages employing cyclic distillation (Kiss 2013):

  • High tray efficiencies (140–300% Murphree efficiency).

  • Reduced energy requirements (30–50% less).

  • Increased quality of the products due to higher separation efficiency.

  • Smaller pressure drops on trays compared with conventional steady-state operation.

  • The cyclic distillation configuration and operation allows larger liquid holdups that can be beneficial for RD, such as catalytic distillation. Cyclic distillation is used in food industry on industrial scale for concentrating alcohol from 8 wt% to 27–45 wt% (Kiss 2013).

Silveston and Hudgins (2004) have investigated periodic temperature forcing of catalytic reactions. The experimental results seem to be rather disappointing. Dautzenberg and Mukherjee (2001) reviewed further multifunctional reactors.

3 Fields

3.1 Centrifugal fields

The application of high gravity fields for intensified gas/liquid contact in a radial counter-current flow apparatus was patented by Ramshaw and Mallinson (1981). This has been one of the starting points of PI. A typical rotating packed bed (RPB), which utilizes the principle of high gravity fields, is presented in Figure 33A.

(A) Simplified schematic of a typical rotating packed bed (RPB); (B) continuous distillation process using rotating packed bed (Wang et al. 2011).
Figure 33:

(A) Simplified schematic of a typical rotating packed bed (RPB); (B) continuous distillation process using rotating packed bed (Wang et al. 2011).

Figure 33B shows a continuous distillation process using RPBs (Wang et al. 2011). It comprises a rotor made of packing and auxiliaries, such as casing, shaft, liquid distributor, and inlet/outlets. The liquid is fed through a distributor onto the inner side of the rotor and flows radially outward as thin films, rivulets, or droplets by centrifugal force. The gas enters into the rotor at the outer side and flows radially inward by pressure gradient. The gas and liquid countercurrently contacts in the rotor packing, wherein mass transfer takes place (Rao et al. 2004, Wang et al. 2011). Numerous scientific papers have been published on the HIGEE technology (Sudhoff et al. 2015). Studies and industrial practice have shown that RPBs intensify gas/liquid interfacial mass transfer and thus decrease equipment volume by 1–2 orders of magnitude compared with its conventional counterpart. There are several variants of RPBs, some of which will be discussed below. Extensive fundamental studies of HIGEE in absorption (Yi et al. 2009), reactive precipitation in spinning cone devices (Wang et al. 2017) or in spinning disc reactor (SDR) (Oxley et al. 2000), preparation of nanoparticles (Kuang et al. 2015, Chen and Shao 2007), thin-film SDR for condensation polymerization (Boodhoo and Jachuck 2000) (see Figure 34), mass transport characteristics (Aoune and Ramshaw 1999), forced convection boiling in a stator-rotor-stator SDR (srs-SDR) (De Beer et al. 2016), and liquid hold-up (Burns et al. 2000), among others, have been conducted.

Schematic of a spinning-disc reactor (SDR) (Boodhoo and Jachuck 2000).
Figure 34:

Schematic of a spinning-disc reactor (SDR) (Boodhoo and Jachuck 2000).

There are far more papers available on the items mentioned above. A more complete list is given by Sudhoff et al. (2015). Some investigations on distillation in RPBs have been published (see citations in Wang et al. 2011, Sudhoff et al. 2015).

Distillations in RPBs were carried out at ICI, University of Texas in Austin, China (NUC, NCU), University of Dortmund/Germany, Taiwan (ITRI), IIT Kanpur (India), and some other places. Sudhoff et al. (2015) and Agarwal et al. (2010) have published systematic design procedures for distillation in RPBs. Sudhoff et al. (2015) have presented an integrated design method for RPBs that can be used not only for design but also for comprehensive process analysis to evaluate the fields of its application. The paper has two major goals. First, the design method shall result in basic design and prediction of operating variables of an RPB for a given separation task or to estimate the performance of an already existing RPB for a process analysis; second, the method shall provide a reliable tool for feasibility studies for the application of RPBs for distillation operations and to identify feasible fields of application. The technology should be promoted to industrial maturity by providing a reliable tool for a conceptual process design. The model uses known correlation equations for hydrodynamics as well as new correlations for mass transfer. Novel concepts of equiareal discretization and integrated centrifugal acceleration are developed and implemented. The model is the core of the integrated design method. It also predicts the power consumption and pressure drop, required equipment space, and investment costs. Results obtained by the model show its applicability and prove the suitability of RPBs for highly flexible distillation processes. Fluctuations in the feed composition can also be handled with the model.

Yi et al. (2009) have published a model to illustrate the mechanism of gas/liquid mass transfer with reactions in an RPB for CO2 absorption by Benfield solution. The authors carried out experiments at various rotating speeds, liquid flow rates, gas flow rates, and temperatures. The predicted CO2 concentrations in the outlet gas agreed well with the experimental data. The profiles of the gas-phase volumetric mass transfer coefficients along the radial direction of the packing could reasonably explain the end effect in RPF, which means that RPB has much better mass transfer efficiency in the inlet region of the packing than at the outer end.

Aranowski et al. (2017) have presented the spinning fluids reactor (SFR), which uses tangential inlets of both fluids that cause a swirling flow. The high tangential velocity of the liquid phase results in a high shearing force that decreases the size of the generated bubbles and increases the mass transfer area per bulk liquid. The reactor of their design can reach gas/liquid interfacial areas up to 16,400 m2/m3, which is an order of magnitude higher than values obtained in the majority of gas/liquid contactors. The device is very compact; the volume of the SFR does not exceed 7 dm3. It has the potential to be applied in a wide range of systems, where high gas/liquid contact area and small size of process equipment are required.

To explore the possible PI in trickle-flow reactors, Dhiman et al. (2005) measured the reaction rates of hydrogenation of α-methyl styrene to cumene with a palladium catalyst in rotating beds of spherical particles and metal foam, which acted as catalyst support. To quantify the intensification achieved, the reaction rates were compared with those of conventional trickle beds. The enhancement in the reaction rates has been measured to be in the range of 30–40 times in a centrifugal force field of about 450 times the gravitational force field. An industrial reactor of 60 m3 could be replaced with a rotating bed <1.5 m3 in volume. However, the volume reduction is possible only for mass-transfer limited reactions.

McFarlane et al. (2010) have investigated the kinetics of transesterification in a centrifugal contactor reactor/separator at temperatures from 45 to 80°C and pressures up to 2.6 bar. The high shear force and turbulent mixing achieved in the reactor minimized the effect of diffusion on the apparent reaction rate, and hence, it could be assumed that the transesterification rate was limited by the reaction kinetics. The chemical kinetics has been successfully modeled using a three-step mechanism of reversible reactions and employing activation energies from the literature, with some modification in preexponential factors. The approach to equilibrium between the acylglycerides limits the overall rate of production of methyl ester. After the reactants were in the centrifugal reactor, the overall conversion to methyl esters has been found to be dependent only on the temperature. Significant improvement in product quality could only be achieved after a second and third pass through the centrifugal contactor, where product and unreacted oil from the first and second stages were collected and separated from the glycerine. De Beer et al. (2016) have investigated boiling of a pure fluid inside the rotor-stator cavities of an srs-SDR. Intensification of boiling heat transfer reduces the required heat exchange area, which reduces the capital costs and the space requirements. Moreover, it allows the application of a lower-temperature driving force ΔT, which is thermodynamically favorable and essential in utilization of low-grade heat streams using vapor recompression. Intensification of flow boiling is realized by increasing the boiling heat transfer coefficient and the efficient removal of the formed vapor phase from the heat exchange surface. The authors varied the rotational velocity of the srs-SDR, the average temperature driving force ΔT, and mass flow rate. Values of the heat transfer coefficient increase by a factor of three by increasing the rotational velocity up to 105 rad/s, independently of the temperature driving force and mass flow rate. Nucleate boiling is partially suppressed by increasing the rotational velocity; the boiling is dominated by forced convective evaporation. Comparison of boiling in the srs-SDR to rotating thin film evaporation shows that the srs-SDR yields a factor of 1.5–2 higher values of the heat transfer coefficient, especially at increasing mass flow rate. The authors have concluded that the srs-SDR allows a highly controlled intensification of forced convection boiling, albeit at the cost of a high energy input. Furthermore, in the case of evaporative separations, fouling is expected to be prevented by the high shear stress induced by rotating heat exchanging surface. In the case of very high heat fluxes, for which surface vapor blanketing becomes limiting, the application of a centrifugal field allows effective removal of the formed vapor phase.

Boodhoo and Jachuck (2000) investigated reactions involving the preparation of two types of unsaturated polyesters from different monomers and a saturated polyester in an SDR (Figure 34). The SDR consists of a grooved brass disc 360 mm in diameter, supported by a rotating shaft and driven by a 2 kW electric motor. A high-temperature bearing system was used and stationary radiant heaters placed under the rotating disc were employed for heating the reactor surface. The brass disc was 1 cm thick and had 16 thermocouples embedded at several locations for monitoring the reactor surface temperature. Temperature is a significant parameter in the enhancement of the polymerization speed. Significant reductions in the reaction times could be achieved due to enhanced transport rates. A tight control of the molecular weight distribution of the polymers has been achieved, and the inherent safety as well as the energy efficiency could be improved with the SDR.

Dashliborun et al. (2017) have introduced a new low-shear rotating reactor concept for PI of heterogeneous catalytic reactions in concurrent gas/liquid downflow and upflow packed-bed reactors. Exhaustive hydrodynamic experiments were carried out using embedded low-intrusive wire mesh sensors. The effect of the rotational velocity on liquid flow patterns in the bed cross-section, liquid saturation, pressure drop, and regime transition was investigated. Furthermore, liquid residence times and Péclet numbers estimated by a stimulus-response technique and a macromixing model have been presented and discussed with respect to the prevailing flow patterns. The analysis of the experimental results has revealed that column rotation had a noticeable impact on the hydrodynamics of both downflow and upflow modes. Rotating the bed with velocities up to 60 rpm depending on the fluid flow rate and mode of operation can significantly improve the crosswise uniformity of the phase distribution. Depending on fluid superficial velocity and reactor rotational velocity, two different flow patterns, namely dispersed and annular flow, were recognized in the downflow mode. Similarly, the column rotation prompted homogenized or annular flow patterns in concurrent upflow. More flexibility in adjusting liquid residence time and back-mixing was found in the RPB operating at constant gas and liquid flow rates. Furthermore, the authors have speculated that depending on the type of reactions to be carried out in fixed-bed reactors, either being liquid- or gas-limited, complete irrigation of the catalyst combined with thinner liquid films around the catalyst surface can be achieved by tuning an appropriate vessel rotational velocity to ease accessibility of the active sites either to be liquid and/or gaseous reactants.

Several investigations on the production of nanoparticles in high-gravity rotating beds have been published. A review has been presented by Chen and Shao (2007). By way of example, the large-scale preparation of amorphous cefixime (CFX) nanoparticles by antisolving precipitation in a high-gravity RPB will be discussed (Kuang et al. 2015). CFX is an oral third-generation cephalosporin antibiotic used to treat infections such as pneumonia or bronchitis. CFX exhibits poor aqueous solubility and low dissolution rate, which limits its effective absorption and bioavailability. RPBs can strongly intensify the mixing and mass transfer processes. High supersaturation, fast nucleation rate, and uniform spatial concentrations may be achieved by RPBs. Therefore, it can provide good control of particle size and size distribution. The authors used the high-gravity antisolvent precipitation technology, implemented by an RPB with a horizontal rotation axis. Tetrahydrofuran (THF) and diisopropylether (IPE) were used as solvent and antisolvent, respectively. Raw CFX was dissolved in THF at a concentration of 100 mg/ml. Then the drug solution and IPE were sprayed onto the inside edge of the rotator and mixed in the packed bed zone to yield nanoparticles immediately, without additional additives. The as-prepared CFX nanoparticles had an average size of 57 nm and were capable of generating a maximum achievable supersaturation level that reached ~22.8 times of raw CFX’s saturation solubility within 5 min, followed by its gradual decrease to ~3.3 times at equilibrium. The specific surface area was nearly 12 times as much as that of the raw drug. Oxley et al. (2000) have found that SDRs are very useful for fast organic reactions and precipitations, with specific half-lives up to 5 s. The rotational speed is an extra variable for reaction operation. The authors investigated a phase-transfer-catalyzed Darzen’s reaction to prepare a drug intermediate and the recrystallization of an active pharmaceutical ingredient. A very tight particle size distribution could be obtained employing the SDR. Further rotating devices for solids production, such as the spinning cone concept, etc., are reviewed by Wang et al. (2017).

Law et al. (2017) discussed the so-called TORBED reactor, a type of swirling fluidized bed reactor that can be used for processing a wide range of materials (Figure 35).

TORBED® compact bed reactor (Law et al. 2017).
Figure 35:

TORBED® compact bed reactor (Law et al. 2017).

The device was developed by Torftech (UK and Canada) and provides unique benefits in precise, rapid, smaller-scale, and lower-cost solutions to industrial materials processing problems, such as catalyst processing, high-temperature calcination, dry gas scrubbing, deoiling of solids, mineral processing, and food processing. The so-called compact TORBED provides very high rates of heat and mass transfer between gas and solid. The materials do not have to be carefully graded, and the process is capable of being very accurately controlled. Furthermore, the apparatus shows only small solid fouling and rapid response. More than 150 TORBED® reactors have been installed yet.

Wang et al. (2008) have introduced a novel high-gravity device: the rotating zigzag bed (RZB), which exhibits many superior features owing to its rotor combining a rotational part with a stationary one (Figure 36).

Rotating zigzag bed HiGee variant of Wang et al. (2008).
Figure 36:

Rotating zigzag bed HiGee variant of Wang et al. (2008).

The characteristics of RZB are its capability of middle-feed and a multirotor configuration in one unit. Thus, one unit of RZB can be applied to continuous distillation processes with a higher mass transfer rate. Experimental results using a methane-water mixture has shown its excellent mass transfer rates with an acceptable pressure drop. Comparison with an RPB has shown that RZB provides equivalent mass transfer efficiency to RPB but exhibits excellent operability with a higher turndown ratio than a RPB does. Comparison with valve tray distillation indicates that the efficiency of RZB is slightly lower than the plate efficiency of valve trays, but if the difference between the tray space and baffle space is taken into consideration, RZB provides a much higher efficiency than that of a valve tray. The pressure drop per theoretical stage of the RZB is almost as large as a tray column.

A review of several high-gravity processes has been published by Zhao et al. (2010).

Burns et al. (2000) and Aoune and Ramshaw (1999) have presented experimental results of liquid hold-up in high-voidage structured packing and mass transfer characteristics of liquid films on rotating discs.

3.2 Ultrasound

Ultrasound is sound waves with frequencies higher than the upper audible limit of human hearing: ≥20 kHz. Physically, ultrasound is not different from audible sound. Ultrasound passing through a solution, for example, water, creates regions inside the solution with high and low pressure according to the periodic compression and expansion. In general, the solution contains some dissolved gas, for example, air. A series of compressions and rarefactions in a liquid may lead to bubbles whose diameter increases over several acoustic cycles (Figure 37).

(A) Schematic representation of the lifetime of a transient cavitation bubble; (B) imploding bubble.
Figure 37:

(A) Schematic representation of the lifetime of a transient cavitation bubble; (B) imploding bubble.

First of all, there has to be a nucleus of the bubbles. Gas bubbles as nucleation sites may be found throughout the solution or trapped in small-angle crevices on solid impurities and contracts with the acoustic cycle if the acoustic pressure is above a certain minimum. If the liquid is supersaturated with gas, the bubbles will grow. For small crevices (≤10 μm), surface tension is a dominant factor. For longer crevices, gas saturation is more important. After some acoustic cycles, the external pressure dominates and the enlarged gas bubbles collapse to a minimum radius of ~0.5 μm in about 0.3 ms. The maximum radius of the bubbles before collapsing is ~40–50 μm. Temperatures of >5000 K and pressures of a few thousand bars are locally generated owing to the fast implosion of the bubbles (Figure 37B). The adiabatic ratio γ=Cp/Cv of the gas contents of a luminescing bubble mainly determines the hot spot temperature. The implosion happens with a collision density of about 1.5 kg/cm2 and pressure gradients of about 2 TPa/cm, with lifetimes shorter than 0.1 ms and cooling rates above 1010 K/s. The speed of collapse is ~1350 m/s. Physical details of bubble dynamics have been described in many books and articles, for example, by Leighton (1994), Lauterborn and Ohl (1997), Keil and Swamy (1999), Thompson and Doraiswamy (1999), Young (1999), Doraiswamy (2001), Mason and Lorimer (2002), Gogate (2008), Brennen (2013), Pokhrel et al. (2016), Wood et al. (2017), and Sancheti and Gogate (2017). The influence of dissolved gas on ultrasonic cavitation has been reviewed by Rooze et al. (2013). The high temperature inside the adiabatically collapsing bubble leads to the generation of OH˙ radicals in water solutions. During the collapse of a gas bubble that is nonlinearly oscillating due to ultrasound, sonoluminescence occurs. The high temperature inside the bubble while collapsing leads to an opaque plasma consisting of ions and electrons with a high density of ~1000 kg/m3. This plasma emits light. These highly active radicals can initiate chemical reactions. Therefore, for obtaining many radicals, a sonochemical reactor should have an optimized geometry and liquid filling. Other important parameters such as pressure amplitude, frequency, ambient pressure, transducer type, signal type, ratio of vessel/transducer diameters, liquid flow, liquid height, liquid temperature, liquid properties, and dissolved gases have been reviewed by Wood et al. (2017) and Pokhrel et al. (2016), among others. In general, an increase in pressure amplitude will relate directly to the power transferred to the liquid and increase the number of cavitation bubbles, but there is an upper limit. There are upper and lower limits of pressure amplitude to the cavitation threshold. Above the upper limit, coalescence and degassing occur with limited active cavitation. Too many bubbles close to the ultrasound transducer cause a dampening effect on the sound waves. Below the lower limit, the amplitude of sound field is too small to induce nucleation or bubble growth. In general, higher frequencies will result in increased nucleation and production of bubbles that are comparatively small in size. This is because the resonance size of a bubble is inversely related to the applied frequency (Leighton 1994). The effect of increasing the temperature of the liquid is to decrease the cavitation threshold due to an increase in the liquid vapor pressure or a decrease in surface tension of viscosity. Additionally, the gas solubility of the liquid will decrease at higher temperatures, and as a consequence, there will be fewer cavitation nuclei available. The effects of different dissolved gases on ultrasonic cavitation have been reviewed by Rooze et al. (2013). An important point is the prediction of the distribution of cavitational intensity in the reactor so that a proper design of the reactors can be achieved. Therefore, the simulation of pressure fields inside sonicated chemical reactors is inevitable. Dähnke and Keil (1998) and Dähnke et al. (1999a,b) appear to be pioneering in terms of simulations of pressure fields existing in the reactor (Doraiswamy 2001, Gogate 2008). A review on the simulation of the spatial distribution of the acoustic pressure in sonochemical reactors with numerical methods has been presented by Tudela et al. (2014). Fundamental papers on acoustics in bubbly mixtures have been published by Carstensen and Foldy (1947), Keller and Miksis (1980), Caflish et al. (1985), Commander and Prosperetti (1989), Ye and Ding (1995), and Plesset and Prosperetti (1977), among others. Important is taking bubble mixtures into account, and not the dynamics of just one bubble. Horst et al. (2007) have published a review on ultrasound reactors and modeling. Ultrasonic horns are the most commonly used reactor designs among the sonochemical reactors (Figure 38A).

(A) US horn transducer; (B) Harwell loop reactor.
Figure 38:

(A) US horn transducer; (B) Harwell loop reactor.

These are typically immersion type of transducers, and very high intensities are observed near the horn. The intensity decreases exponentially as one moves away from the horn tip and vanishes at a distance of as low as 2–5 cm. Therefore, ultrasound has only a short penetration length, depending on the power input and operating frequency. Horst et al. (1996) have developed a conically tapering reactor using high-intensity ultrasound from a horn for applications in Grignard reactions. Dahlem et al. (1999) have introduced a so-called Telsonic horn that exhibits radial vibrations, but also just below the horn, high cavitational activity could be observed. Unfortunately, horns show erosion and particle shedding at their tip. Ultrasonic baths are in use on laboratory and industrial scale. The bottom of the baths is irradiated with transducers. Many other designs of sonoreactors have been presented by Keil and Swamy (1999). A Harwell loop reactor is presented in Figure 38B. This reactor combines a sonicated zone with a “silent” vessel. The limited penetration range of ultrasound is overcome with this reactor, which also permits residence time control. Other aspects of sonochemical reactors have been reviewed by Thompson and Doraiswamy (1999), Cintas et al. (2015), and Asgharzadehahmadi et al. (2016).

Ultrasonics has been employed in many applications, such as chemical synthesis (Thompson and Doraiswamy 1999, Doraiswamy 2001, Mason and Lorimer 2002, Leonelli and Mason 2010, Chatel 2017, Colmenares and Chatel 2017, Sancheti and Gogate 2017), production of nanomaterials (Suslick and Price 1999, Pokhrel et al. 2016), biotechnology (Rokhina et al. 2009, Ajmal et al. 2016, Nakashima et al. 2016, Bansode and Rathod 2017, Huang et al. 2017), food technology (Patist and Bates 2008, Vilkhu et al. 2008, Chemet et al. 2011), waste water treatment (Gogate and Pandit 2004, Mahamuni and Adenuyi 2010), crystallization (Gielen et al. 2017), mixing enhancement (Zhao and Wang 2017), production of highly stable oil in water emulsions (Carpenter et al. 2017), etc.

Ultrasonic radiation has been used in many chemical reactions in order to enhance the yield and selectivity. Thompson and Doraiswamy (1999) have listed several reactions that can be enhanced by sonochemistry. One has to keep the temperature constant, and one has to employ normed vessels to compare results with and without sonication. Ultrasound can initiate reactions, for example, the Grignard reaction (Horst et al. 1996), accelerate the rate of reaction owing to enhanced mass transfer, and change the reaction pathway. In very rare cases, new compounds can be synthesized by ultrasound due to generated OH˙ radicals. In electrochemistry, ultrasound may be useful, as electrodes are continuously cleaned, the liquid is degassed, which limits the gas bubble accumulation on the electrode surface, and the cavitation reduces the thickness of the diffusion layer on the electrodes. The benefits of sonoelectrochemistry have been reported for a number of processes including electrosynthesis, electroanalysis, bioelectrochemistry, synthesis of conducting polymers, and electroplating (Compton et al. 1997). Many effects of sonochemistry in chemical synthesis are not understood in detail yet.

In environmental area, decomposition of toxic organic compound into smaller molecules, degradation of bacteria in waste water (Neis 2015), sonophotocatalytic waste water treatment (Gogate and Pandit 2004), and advanced oxidation processes involving ultrasound and ultraviolet radiation in waste water treatment (Mahamuni and Adenuyi 2010) are some examples of utilization of ultrasound. In sewage sludge treatment, ultrasound is applied as a pretreatment to improve anaerobic sludge stabilization. The high shear forces created in the advent of cavitation can be used to improve process efficiency in sludge dewatering and to achieve sludge disintegration. Due to the ultrasonic disruption of biomass in the sludge, subsequent microbial degradation occurs far faster than in the conventional treatment.

In the food industry, high power ultrasound has become an efficient tool for large-scale commercial applications, such as emulsification, homogenization, extraction, crystallization, dewatering, low-temperature pasteurization, degassing, defoaming, activation and inactivation of enzymes, particle size reduction and viscosity alteration. Ultrasound in food processing and preservation leads to higher product yields and shorter processing times; reduces operating and maintenance costs; improves taste, texture, flavor, and color; and reduces pathogens at lower temperatures (Patist and Bates 2008, Vilkhu et al. 2008, Chemet et al. 2011). PI of ultrasound in food processing also includes more effective mixing and micromixing, faster energy and mass transfer, reduced thermal and concentration gradients, reduced temperature, selective extraction, reduced equipment size, faster response to process extraction control, faster start-up, increased production, and elimination of process steps. Food industries can nowadays be provided with practical and reliable ultrasound equipment. Chemet et al. (2011) have presented several photos of industrial scale ultrasound equipment.

In recent years, the practice of ultrasonic irradiation began to emerge as a tool for the activation of enzymes under mild frequency conditions. The incorporation of ultrasound in any of enzymatic reactions not only increases yield but also accelerates the rate of reaction under mild conditions and less side products. Workable ambient frequency for lipase catalyzed reactions falls in the range of 20–40 kHz. Pulsating irradiation can be more beneficial, as it can have internal control on the rise of local temperature and hence avoid denaturation of enzymes. An optimized temperature of 40–60°C is suitable for lipases. It is important that the active conformation of lipase remains intact and no denaturation occurs due to the increase in substrates or product concentrations around the lipase. Selection of the proper solvent is a crucial step, and a small amount of water is required for lipases to retain its catalytically active conformation (Bansode and Rathod 2017). At the molecular level, ultrasound provides promoting or damage effects on enzyme activities by altering the characteristics of enzymes, substrates, and the reactions between enzymes and substrates and providing an optimal environment for the reactions. At the cellular level, ultrasound may promote microbial growth by losing cell bunches, increasing the permeability of cell membranes, adjusting culture medium, and providing effects on cellular components, cellular functions, and genetics (Huang et al. 2017). Representative ultrasound-assisted bioprocesses are, for example, transesterification of triglicerydes and free fatty acids for biofuel production, emulsification of vegetable oil and MEOH for biofuel production, laccase-catalyzed decolorization of textile effluents, horse radish peroxidase-catalyzed degradation of phenol, protease catalyzed oxidation of untanned leather waste, cellulose-catalyzed degradation of distillery waste water, tyrosinase-laccase immobilization on sonogel-carbon transducer, anaerobic digestion of waste activated sludge, and dewatering of waste activated sludge (Rokhina et al. 2009). Lignocellulosic biomass is usually pretreated before enzymatic hydrolysis to enhance its digestibility. Pretreatment should improve the formation of sugars and avoid excessive degradation, which can lead to loss of sugars and formation of inhibitors. A combination on hydrodynamic cavitation (HC) with sodium percarbonate for the pretreatment of lignocellulose biomass turned out to be efficient in terms of both glucose and xylose production. No furfural was generated (Ajmal et al. 2016, Nakashima et al. 2016).

HC is also a viable and energy-efficient technique for the preparation of oil in water nanoemulsions. Carpenter et al. (2017) have optimized the shape, size, and operating pressure on the formation of mustard oil in water nanoemulsion. The optimization criterion was the lowest droplet size obtainable. Various geometrical configurations and dimensions of hydrodynamic cavitating devices (circular venturi, slit venturi, and five different orifice plates) were investigated. Zhao and Wang (2017) have found that extraordinarily rapid mixing can be achieved in confined mixing layers by active forcing with an optimal narrow frequency band. The investigations have revealed that the optimal forcing frequency of the fast mixing is tightly related to a complicated acoustic resonance mechanism of the entire water tunnel system. This finding may lead to a new technology for mixing and heat transfer enhancement.

Gielen et al. (2017) have used a pulsed ultrasonic field of 30 kHz during the cooling crystallization paracetamol in a batch and a recycled flow crystallizer. Pulsed ultrasound creates two distinct bubble regimes. When ultrasound is turned on, bubbles oscillate, grow, and implode, while they dissolve if sonication is switched off. In both setups, the nucleation temperature, crystal size, and shape were investigated at various pulse settings. Under the ultrasonic conditions, formation of nuclei was obtained at a temperature of at least 8°C higher compared to nonsonicated tests, independent of a crystallizer configuration. When ultrasound is switched on more than 10% of the time, a similar nucleation temperature as with continuous treatment is obtained. At this minimal pulse setting, a bubble population, consisting of both oscillating and dissolving bubbles, is present in the vessel at all times. The final particle size of paracetamol can be controlled in the batch setup by the pulse conditions, without affecting the crystal shape.

Microbubbles (~10 μm diameter) provide high surface area per unit volume. They find a large number of applications in medical, marine, and chemical industry (Parmar and Majumder 2013). They are widely used for drug delivery systems, and they provide a high mass transfer coefficient as compared to conventional bubbles, and hence, by use of microbubbles, intensification of mass transfer can be achieved. The article describes several approaches on how to generate microbubbles and their applications. Research on microbubbles is still in its infancy. To sum up, ultrasound has proved to be an efficient PI tool in various industries with a high potential for further developments.

3.3 Electric and magnetic fields

Microwaves are part of the electromagnetic spectrum, with a wavelength ranging from 1 m to 1 nm, which corresponds to a frequency range of 300 MHz to 300 GHz. A large part of this range is occupied by the radar and telecommunication applications, and in order to avoid interference, industrial and domestic microwave applications operate at several standard allocated frequencies, most often at 2.45 GHz. Different from the conventional heating, microwave heating involves an energy conversion from the electromagnetic energy to thermal energy rather than the heat transfer. Microwave energy is delivered directly to the material through molecular interaction with the electromagnetic field. Since microwaves can penetrate the material and supply energy, heat can be generated throughout the volume of the material, resulting in volumetric heating (dielectric heating). The main advantages for microwaves are related to a rapid increase in the bulk temperature (10 K/s, no high temperature at the vessel wall is detected; Kappe 2004, Stankiewicz 2006, Kappe et al. 2013, Sun et al. 2016, Estel et al. 2017). High reaction temperatures can rapidly be attained when irradiating polar materials in a microwave field. For example, MEOH can be rapidly superheated to temperatures >100°C above its boiling point when irradiated in a sealed vessel. Ionic liquid can show temperature jumps of ~200°C within a few seconds when irradiated with microwaves. Dramatic reaction rate enhancements between reactions performed under standard oil-bath conditions (heating under reflux) and microwave-heated processes have frequently been observed (Kappe 2004, Stuerga 2006).

Besides volumetric heating, microwave heating offers a number of advantages, such as the following (Sun et al. 2016):

  • Selective material heating

  • Noncontact heating

  • Uniformity of heating

  • Very high power densities developed in the processing zone

  • Quick start-up and stopping

  • The ability to treat waste in situ

  • Portability of equipment and processes

Based on these advantages, microwaves have been used in various technological and scientific fields, for example, food processing, biomass treating, drying, sludge processing, medical waste treatment, waste water cleanup, sintering of metals and ceramics, etc.

The electric field (E-field) component of microwaves is responsible for dielectric heating. Dipolar polarization and ionic conduction are the primary mechanisms of dielectric heating. In polarization mechanism, a dipole is sensitive to external electric fields and will attempt to align itself with the field by rotation. Under a high-frequency electric field, the dipoles do not have sufficient time to respond to the oscillating electric field; as a result of this phase lag, they collide with each other and power is dissipated to generate heat in the material. This is the case for polar materials. The dipolar polarization mechanism involves the heating of electrically insulating materials by dielectric loss. In conduction mechanism, any mobile charge carriers (electrons, ions, etc.) move back and forth through the material under the influence of the E-field, creating an electric current. These induced currents will cause heating in the sample due to any electrical resistance caused by the collisions of charged species with neighboring molecules or atoms (Metaxas and Meredith 1983, Metaxas 1996, Sun et al. 2016). Besides the E-field, the magnetic field component (H-field) is more efficient than the E-field for heating some dielectric materials (e.g. ferrite) and certain conductive powder materials (Cheng et al. 2001). The principal mechanisms for microwave H-field heating are eddy current losses, hysteresis losses, and magnetic resonance losses, including domain wall resonance and electron spin resonance and residual losses (Sun et al. 2016).

A microwave oven (Figure 39) is essentially composed of a microwave source (magneton or solid state generators) with its power supply and controls, connected to a transmission line (waveguide for higher power, coaxial cables for lower power) that conveys the electromagnetic energy in a metallic cavity (applicator) into which the actual chemical reactor is inserted.

General scheme describing a complete arrangement of a microwave system dedicated to heating in a closed applicator (single mode, in this case) (Leonelli et al. 2015).
Figure 39:

General scheme describing a complete arrangement of a microwave system dedicated to heating in a closed applicator (single mode, in this case) (Leonelli et al. 2015).

The latter can be composed of a common borosilicate or quartz reactor or of microwave transparent polymer (usually Teflon® or PTFE and some others). Other important components are those dedicated to impedance matching. The three-stubs (Figure 39) tuner allows the impedance matching between generator and load by inserting metal posts along the transmission line with manual or automatic system. The three-port circulator allows redirecting the power reflected from the load to an auxiliary load (usually water) positioned on the third port. It protects the microwave source from reflected power, and if the third port is equipped, it can be used also to measure reflected power by a calorimetric system. The coupling iris is another impedance matching device composed of tailored openings along the transmission line to achieve the maximum energy transfer from the source to the load. Finally, along the line, a directional coupler can be positioned; it measures emitted (forward) and reflected power and hence quantifies the amount of energy dissipated into the load. For details and photos of commercial microwave devices, see Leonelli and Veronesi (2015) (see also Meredith 1998).

A preliminary modeling of the complicated phenomena is essential. Some examples of the hydrodynamics, dielectric properties, physicochemical parameters, control of the system, and kinetics are presented by Estel et al. (2017). As has been mentioned by Kappe et al. (2013), the reliable monitoring of reaction temperature is nontrivial but absolutely critical to the investigation of microwave effects. That paper has also discussed the interpretation of microwave effects on chemical reactions, in particular, many confusing results published in the literature. Kappe (2004) has listed many reactions investigated by microwaves. Horikoshi and Serpone (2015) have edited a comprehensive book of microwaves in homogeneous and heterogeneous catalysis (see also Stankiewicz 2006, Altman et al. 2010, Hessel et al. 2013a,b, Horikashi and Serpone 2015).

Applications of microwaves in RD have been published by Werth et al. (2015) and Ding et al. (2016), among others. Werth et al. (2015) have developed a detailed model that takes into account the chemical reaction (homogeneously catalyzed transesterification of dimethylcarbonate with ETOH) and the superheating of liquid phase. The experiments showed no significant effect of microwaves on the performance of the RD process. Neither the separation efficiency at macroscopic scale, as present in a RD column, nor the reaction rate has been enhanced. Ding et al. (2016) have investigated the esterification of acetic acid with ETOH in a microwave RD (MRD) process. Their results showed that, with the same total energy consumption, MRD needed less time than RD did to obtain 70% overhead ethyl acetate. Compared with the RD probes, the instantaneous improvement of ethyl acetate content achieved by MRD was up to 6.9% under the same reflux ratio and 6.7% under the same acetic feed flow rate. Their results have shown that the application of microwaves intensified the performance of RD. Aspen batch distillation was used for the simulation of the MRD process.

Microwave radiation converts various types of cellulosic biomass into valuable chemicals, including liquid and solid fuels (Sanders et al. 2012). The initial activation of the cellulosic polysaccharide helices very rapidly leads to the formation of reactive oligosaccharides, which can quickly undergo further chemical reactions. The chemical engineer has to control this decomposition process so that a limited number of reaction pathways occur, leading to selective processes for converting biomass into molecular products as well as to keep the energy efficiently of the technique cost-effective. An effective way to do this is to build rapid separation of particular products or intermediates into continuous microwave processing. The separated molecular streams need to be quenched or undergo rapid downstream chemistry and utilize the reactive nature of these intermediates to create valuable new products. The conversion of biomass into chemicals and biofuels is an active research area as trends move to replace fossil fuels with renewable resources. The review by Nomanbhay and Ong (2017) highlights the potential of microwaves in biodiesel production (see also Fang et al. 2016, Gude 2017). Numerous types of feedstocks have been introduced to prepare biodiesel: vegetable oil, nonedible oil, waste cooking oil, and algae. With the assistance of microwave technology, the advantages of microwaves have been brought over to biodiesel production. The conversion efficiency and yield show that microwaves have the potential for large-scale biodiesel production, as they are able to interact with various components. One should keep in mind that most of the results collected so far are from laboratory-scale experiments. Scale-up of microwave devices is still not solved in detail.

Microwave sintering has emerged in recent years as a new method for sintering a variety of materials that has shown significant advantages against conventional sintering procedures (Gupta et al. 2007, Oghbaei and Mirzaee 2010). The main advantages of microwaves in sintering are the following:

  • Much lower energy consumption than conventional sintering.

  • Diffusion process intensifies by using microwaves due to its enhanced mechanism.

  • Higher heating rates can be obtained, and thus, the sintering time is reduced.

  • Higher density and better grain distribution can be achieved by microwaves.

  • Better physical and mechanical properties can be obtained by microwave sintering.

Nowadays, hybrid heating techniques that combine direct microwave heating with infrared heat sources are a standard technique. This approach avoids some problems such as temperature runaway and temperature nonuniformities. The combined action of microwaves and microwave-coupled external heating source (microwave hybrid heating) can be utilized to achieve rapid sintering from both inside and outside of the powder compact. Flash sintering is a recently developed method in which ceramics and other materials can be sintered at low temperatures in a very short time (<60 s). This sintering technique is based on electrical Joule heating. It is a nonlinear phenomenon, characterized by a sharp increase in the conductivity of the sample and simultaneous rapid densification under an electric field above a threshold temperature in a few of seconds. This phenomenon is observed after a certain incubation time and above a critical electric field strength. The mechanisms of flash sintering are not well understood in detail. A comprehensive review on flash sintering has been published by Yu et al. (2017). With respect to modelling of flash sintering see, for example, Pereira da Silva et al. (2016).

Electric fields can induce phase inversions in liquid-liquid dispersions, in which the dispersed phase becomes continuous and the continuous phase becomes dispersed. This phenomenon may be used to ensure that the aqueous phase remains the continuous phase, even at high volume fraction of the organic phase. Additionally, it may be used to increase the volume fraction of a dispersed organic phase without phase inversion. It may also be used to enhance mass transfer rates from one phase to the other by inducing phase inversion (Tsouris and Dong 2000). Pulsed electric fields (PEFs) are a nonthermal method of food preservation that uses short electric pulses for microbial inactivation and causes minimal detrimental effect on food quality. The basic principle of the PEF technology is the application of short pulses of high electric fields with duration of microseconds to milliseconds and intensity in the order of 10–80 kV/cm. Pulsed electric currents are delivered to a product placed between a set of electrodes. The applied high voltage causes microbial inactivation. The electric field may be applied in the form of exponentially decaying, square wave, bipolar, or oscillatory pulses. After the treatment, the food is packed aseptically and stored under refrigeration (Barbosa-Cánovas and Zhang 2001).

Magnetic fields can be used for improved mixing (Rakoczy et al. 2017). These authors employed a rotating magnetic field to investigate its effect on the mixing of various liquids. Depending on physical properties, an improved mixing could be achieved. Inhomogeneous high magnetic fields affect the hydrodynamics in trickle-flow reactors. Depending on magnetic susceptibility, inhomogeneous magnetic fields can generate hypogravity or hypergravity conditions. This phenomenon can be used to improve the liquid holdup in trickle-bed reactors (Larachi 2007), resulting in a better contact between liquid and catalyst surface. The magnetic field effect has been described by Larachi in terms of an artificial gravity body force.

4 Conclusions and outlook

This short review has demonstrated that PI already has an impact on chemical process engineering, in particular in distillation technology, microengineering, and membrane separation. On the other hand, one has to keep in mind that many developments have not penetrated the industry. As chemical process engineering is more an evolutionary than a revolutionary industry, investors proceed continuously. They want proof that new technologies will be safe and will not fail. For some PI developments, scale-up knowledge and pilot plant operating experience are missing. Therefore, only further research and subsequent demonstration plants, perhaps funded by the government, will give backing to further industrial PI installations.

The present review is by no means complete. Over the last two decades, thousands of papers have been issued, but many of the important developments have been discussed.

Acknowledgments

The author is grateful to Prof. A. Gorák (TU Dortmund), Prof. A. Stankiewicz (TU Delft), and Prof. G. Fieg (TU Hamburg) for reading this paper and their useful comments. The author is also grateful to Mrs. H. Oppelaar for writing the text and preparing the figures.

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About the article

Received: 2017-09-08

Accepted: 2017-09-21

Published Online: 2017-12-19

Published in Print: 2018-02-23


Citation Information: Reviews in Chemical Engineering, Volume 34, Issue 2, Pages 135–200, ISSN (Online) 2191-0235, ISSN (Print) 0167-8299, DOI: https://doi.org/10.1515/revce-2017-0085.

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