Published since January 1, 1964

Practical Metallography

Praktische Metallographie – Preparation, Imaging and Analysis of Microstructures

ISSN: 2195-8599

Impact Factor: 0.266

About this journal

Practical Metallography is a bilingual (German-English) journal that informs you thoroughly on materialographic preparation, imaging and analysis of microstructures. The journal covers the development and improvement of metallographic methods and equipment, possibilities of optical and electron microscopy, spectroscopy, diffraction techniques, non-destructive testing, metallographic investigations of materials, problems of specimens preparation and evaluation including useful laboratory advice and recipes, failure analysis including damage detection and elimination.
All articles are subject to thorough, independent peer review.
Practical Metallography works closely with Deutsche Gesellschaft für Materialkunde e.V. (DGM)

Abstracting and Indexing

Practical Metallography is covered by the following services:

Baidu Scholar
Chemical Abstracts Service (CAS) - CAplus
Chemical Abstracts Service (CAS) - SciFinder
CNKI Scholar (China National Knowledge Infrastructure)
CNPIEC - cnpLINKer
Dimensions
EBSCO Discovery Service
Google Scholar
J-Gate
KESLI-NDSL (Korean National Discovery for Science Leaders)
Microsoft Academic
MyScienceWork
Naver Academic
Naviga (Softweco)
ProQuest (relevant databases)
ReadCube
SCImago (SJR)
SCOPUS
Semantic Scholar
Sherpa/RoMEO
Summon (ProQuest)
TDNet
WanFang Data
Web of Science - Current Contents/Engineering, Computing, and Technology
Web of Science - Science Citation Index Expanded
WorldCat (OCLC)
Yewno Discover

Supplementary Materials

Topics

Volume 58 Issue 11

November 2021

Accessible November 15, 2021

Page range: 681-682

Download PDF

Editorial

Accessible November 15, 2021

Editorial

Page range: 683-683

Download PDF

November 15, 2021

Increasing the Image Sharpness of Light Microscope Images Using Deep Learning

P. Krawczyk, A. Jansche, T. Bernthaler, G. Schneider

Page range: 684-696

Abstract

Image-based qualitative and quantitative structural analyses using high-resolution light microscopy are integral parts of the materialographic work on materials and components. Vibrations or defocusing often result in blurred image areas, especially in large-scale micrographs and at high magnifications. As the robustness of the image-processing analysis methods is highly dependent on the image grade, the image quality directly affects the quantitative structural analysis. We present a deep learning model which, when using appropriate training data, is capable of increasing the image sharpness of light microscope images. We show that a sharpness correction for blurred images can successfully be performed using deep learning, taking the examples of steels with a bainitic microstructure, non-metallic inclusions in the context of steel purity degree analyses, aluminumsilicon cast alloys, sintered magnets, and lithium-ion batteries. We furthermore examine whether geometric accuracy is ensured in the artificially resharpened images.

November 15, 2021

Visualization of Prior Austenite Grain Boundaries in Low-Carbon Steels

M. Böcker, M. Steinbacher, R. Fechte-Heinen

Page range: 697-714

Abstract

Knowledge of the size of the prior austenite grain is of key importance. If abnormal grain growth occurs during austenitization, the resultant inhomogeneous microstructure may negatively affect the strength and toughness properties of the final product. The visualization of prior austenite grain boundaries with an etchant based on picric acid has been applied for years. Despite this long-time experience, it is often challenging to achieve sufficiently good visualization of prior austenite grain boundaries in many steel grades, especially low-carbon steels. This work will study the effect of the cooling rate from austenitizing temperature down to room temperature, of the subsequent tempering treatment and the etchant on the visualization of prior austenite grain boundaries in a low-carbon microalloyed steel. All these parameters have an impact on the etching result. A suitable etchant for the visualization of prior austenite grain boundaries in a low-carbon microalloyed steel could be found.

Failure analysis

November 15, 2021

Metallurgical Failure Investigation of Fractured Dog Bone Seal Retainer Ring Fillet Welds in the Turbine Exhaust Casing of a Heavy-duty Gas Turbine Engine

A. Neidel, T. Gädicke, S. Riesenbeck

Page range: 715-724

Abstract

Short fillet welds used to fasten a large retainer ring to so-called dog bone seals failed in the turbine exhaust casing of a non-OEM heavy-duty gas turbine engine used for power generation. The subject fillet welds fractured due to high cycle fatigue loading. Neither weld imperfections nor any other material defects were found that could have contributed to the failure. It was concluded that an unfavorable design, specifying very short fillet welds for fastening the dog bone seal segments to the retainer ring, was the root cause of failure. In a purely static loading situation, this design would probably not have failed. However, in a dynamic loading scenario as is the case in any gas turbine engine exhaust, such a design is simply not sturdy enough.

November 15, 2021

Report on the 55th Metallography Conference from 29.09. – 01.10.2021

Page range: 725-727

November 15, 2021

Picture of the month

Page range: 728-728

November 15, 2021

Presentation of the DGM Metallography Award 2021

Page range: 729-731

November 15, 2021

Presentation of 33^th Buehler Best Paper Award 2020

Page range: 732-733

November 15, 2021

Presentation of Struers Best Contribution and Best Poster Award 2021

Page range: 734-735

Winners of the Photo Competition / Gewinner des Fotowettbewerbs

November 15, 2021

Winners of the Photo Competition

Page range: 736-737

News

November 15, 2021

Großer Bahnhof für Gerhard Schneider

Page range: 738-741

Meeting Diary

November 15, 2021

Meeting Diary

Page range: 742-743

Volume 58 (2021)

Volume 57 (2020)

Volume 56 (2019)

Volume 55 (2018)

Volume 54 (2017)

Volume 53 (2016)

Volume 52 (2015)

Volume 51 (2014)

Volume 50 (2013)

Volume 49 (2012)

Volume 48 (2011)

Volume 47 (2010)

Volume 46 (2009)

Volume 45 (2008)

Volume 44 (2007)

Volume 43 (2006)

Volume 42 (2005)

Volume 41 (2004)

Volume 40 (2003)

Volume 39 (2002)

Volume 38 (2001)

Volume 37 (2000)

Volume 36 (1998)

Volume 34 (1997)

Volume 33 (1996)

Volume 32 (1995)

Volume 31 (1994)

Volume 30 (1993)

Volume 29 (1992)

Volume 28 (1991)

Volume 27 (1990)

Volume 26 (1989)

Volume 25 (1988)

Volume 24 (1987)

Volume 23 (1986)

Volume 22 (1985)

Volume 21 (1984)

Volume 20 (1983)

Volume 18 (1981)

Volume 17 (1980)

Volume 16 (1979)

Volume 15 (1978)

Volume 14 (1977)

Volume 13 (1976)

Volume 12 (1975)

Volume 11 (1974)

Volume 10 (1973)

Volume 9 (1972)

Volume 8 (1971)

Volume 7 (1970)

Volume 6 (1969)

Volume 5 (1968)

Volume 4 (1967)

Volume 2 (1965)

Volume 1 (1964)

5-year Impact Factor	0.260
Cite Score	0.5
Impact Factor	0.266
Journal Citation Indicator	0.08
SCImago Journal Rank	0.156
Source Normalized Impact per Paper	0.215

Submit

Manuscript submission

You can easily submit your manuscript online. Simply go to https://mc.manuscriptcentral.com/practmet and you will be guided through the whole submission and publishing process.

Editorial

Editor
Prof. Dr.-Ing. Frank Mücklich (muecke@matsci.uni-sb.de)
Saarland University
Deutsche Gesellschaft für Materialkunde e.V. (DGM)

Editorial Office
Michael Engstler (pmeditor@materialography.net)
Saarland University
Campus D3 3
66123 Saarbrücken

Dr.-Ing. Agustina Guitar
Laura Ulrich
Niklas Müller

Society contact
Honorary Chairman, DGM
Prof. Dr. Dr. Günter Petzow
Deutsche Gesellschaft für Materialkunde e.V. (DGM)

(Deutsch)

Online ISSN: 2195-8599
Print ISSN: 0032-678X
Type: Journal
Language: Multiple languages
Publisher: De Gruyter
First published: January 1, 1964
Publication Frequency: 12 Issues per Year

Practical Metallography

Praktische Metallographie – Preparation, Imaging and Analysis of Microstructures

Contents

Editorial

Increasing the Image Sharpness of Light Microscope Images Using Deep Learning

Abstract

Visualization of Prior Austenite Grain Boundaries in Low-Carbon Steels

Abstract

Metallurgical Failure Investigation of Fractured Dog Bone Seal Retainer Ring Fillet Welds in the Turbine Exhaust Casing of a Heavy-duty Gas Turbine Engine

Abstract

Report on the 55th Metallography Conference from 29.09. – 01.10.2021

Picture of the month

Presentation of the DGM Metallography Award 2021

Presentation of 33th Buehler Best Paper Award 2020

Presentation of Struers Best Contribution and Best Poster Award 2021

Winners of the Photo Competition

Großer Bahnhof für Gerhard Schneider

Meeting Diary

Presentation of 33^th Buehler Best Paper Award 2020