Predicting material microstructure evolution via data-driven machine learning

Predicting microstructure evolution can be a formidable challenge, yet it is essential to building microstructure-processing-property relationships. Yang et al. offer a new solution to traditional partial differential equation-based simulations: a data-driven machine learning approach motivated by t...

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Detalles Bibliográficos
Autor principal: Kautz, Elizabeth J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2021
Materias:
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Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8276005/
https://www.ncbi.nlm.nih.gov/pubmed/34286300
http://dx.doi.org/10.1016/j.patter.2021.100285
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author Kautz, Elizabeth J.
author_facet Kautz, Elizabeth J.
author_sort Kautz, Elizabeth J.
collection PubMed
description Predicting microstructure evolution can be a formidable challenge, yet it is essential to building microstructure-processing-property relationships. Yang et al. offer a new solution to traditional partial differential equation-based simulations: a data-driven machine learning approach motivated by the practical needs to accelerate the materials design process and deal with incomplete information in the real world of microstructure simulation.
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spelling pubmed-82760052021-07-19 Predicting material microstructure evolution via data-driven machine learning Kautz, Elizabeth J. Patterns (N Y) Preview Predicting microstructure evolution can be a formidable challenge, yet it is essential to building microstructure-processing-property relationships. Yang et al. offer a new solution to traditional partial differential equation-based simulations: a data-driven machine learning approach motivated by the practical needs to accelerate the materials design process and deal with incomplete information in the real world of microstructure simulation. Elsevier 2021-06-18 /pmc/articles/PMC8276005/ /pubmed/34286300 http://dx.doi.org/10.1016/j.patter.2021.100285 Text en © 2021 The Author https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Preview
Kautz, Elizabeth J.
Predicting material microstructure evolution via data-driven machine learning
title Predicting material microstructure evolution via data-driven machine learning
title_full Predicting material microstructure evolution via data-driven machine learning
title_fullStr Predicting material microstructure evolution via data-driven machine learning
title_full_unstemmed Predicting material microstructure evolution via data-driven machine learning
title_short Predicting material microstructure evolution via data-driven machine learning
title_sort predicting material microstructure evolution via data-driven machine learning
topic Preview
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8276005/
https://www.ncbi.nlm.nih.gov/pubmed/34286300
http://dx.doi.org/10.1016/j.patter.2021.100285
work_keys_str_mv AT kautzelizabethj predictingmaterialmicrostructureevolutionviadatadrivenmachinelearning

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