Quantitative multi-image analysis in metals research

Quantitative multi-image analysis (QMA) is the systematic extraction of new information and insight through the simultaneous analysis of multiple, related images. We present examples illustrating the potential for QMA to advance materials research in multi-image characterization, automatic feature i...

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Main Authors:	Demkowicz, M. J., Liu, M., McCue, I. D., Seita, Matteo, Stuckner, J., Xie, K.
Other Authors:	School of Mechanical and Aerospace Engineering
Format:	Article
Language:	English
Published:	2023
Subjects:	Engineering::Materials Metal Research Multi-Images
Online Access:	https://hdl.handle.net/10356/165033
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Institution:	Nanyang Technological University
Language:	English

id	sg-ntu-dr.10356-165033
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spelling	sg-ntu-dr.10356-1650332023-03-11T16:48:17Z Quantitative multi-image analysis in metals research Demkowicz, M. J. Liu, M. McCue, I. D. Seita, Matteo Stuckner, J. Xie, K. School of Mechanical and Aerospace Engineering School of Materials Science and Engineering Engineering::Materials Metal Research Multi-Images Quantitative multi-image analysis (QMA) is the systematic extraction of new information and insight through the simultaneous analysis of multiple, related images. We present examples illustrating the potential for QMA to advance materials research in multi-image characterization, automatic feature identification, and discovery of novel processing-structure-property relationships. We conclude by discussing opportunities and challenges for continued advancement of QMA, including instrumentation development, uncertainty quantification, and automatic parsing of literature data. Ministry of Education (MOE) Published version MJD was supported by the US Department of Energy, National Nuclear Security Administration under award no. DE-NA0003857. IM was supported by an Early Career Faculty grant from NASA’s Space Technology Research Grants Program. MS was supported by the Ministry of Education of Singapore, Official Number: MOE2017-T2-2-119. JS was supported by the NASA Transformational Tools and Technologies (T3) project under the Transformative Aeronautics Concept Program within the Aeronautics Research Mission Directorate. KX was supported by the US National Science Foundation, Division of Materials Research, under award no. 2004752. KX is grateful to W.S. Lin for assistance with DefectSegNet. 2023-03-08T06:25:35Z 2023-03-08T06:25:35Z 2022 Journal Article Demkowicz, M. J., Liu, M., McCue, I. D., Seita, M., Stuckner, J. & Xie, K. (2022). Quantitative multi-image analysis in metals research. MRS Communications, 12(6), 1030-1036. https://dx.doi.org/10.1557/s43579-022-00265-7 2159-6859 https://hdl.handle.net/10356/165033 10.1557/s43579-022-00265-7 36474648 2-s2.0-85140061476 6 12 1030 1036 en MOE2017-T2-2-119 MRS Communications © The Author(s) 2022. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons. org/licenses/by/4.0/. application/pdf
institution	Nanyang Technological University
building	NTU Library
continent	Asia
country	Singapore Singapore
content_provider	NTU Library
collection	DR-NTU
language	English
topic	Engineering::Materials Metal Research Multi-Images
spellingShingle	Engineering::Materials Metal Research Multi-Images Demkowicz, M. J. Liu, M. McCue, I. D. Seita, Matteo Stuckner, J. Xie, K. Quantitative multi-image analysis in metals research
description	Quantitative multi-image analysis (QMA) is the systematic extraction of new information and insight through the simultaneous analysis of multiple, related images. We present examples illustrating the potential for QMA to advance materials research in multi-image characterization, automatic feature identification, and discovery of novel processing-structure-property relationships. We conclude by discussing opportunities and challenges for continued advancement of QMA, including instrumentation development, uncertainty quantification, and automatic parsing of literature data.
author2	School of Mechanical and Aerospace Engineering
author_facet	School of Mechanical and Aerospace Engineering Demkowicz, M. J. Liu, M. McCue, I. D. Seita, Matteo Stuckner, J. Xie, K.
format	Article
author	Demkowicz, M. J. Liu, M. McCue, I. D. Seita, Matteo Stuckner, J. Xie, K.
author_sort	Demkowicz, M. J.
title	Quantitative multi-image analysis in metals research
title_short	Quantitative multi-image analysis in metals research
title_full	Quantitative multi-image analysis in metals research
title_fullStr	Quantitative multi-image analysis in metals research
title_full_unstemmed	Quantitative multi-image analysis in metals research
title_sort	quantitative multi-image analysis in metals research
publishDate	2023
url	https://hdl.handle.net/10356/165033
_version_	1761781946975780864

Quantitative multi-image analysis in metals research

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