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16-04-2024 | Originalarbeit

Accelerated Materials Design and Materials Data Management at MCL

Authors: Daniel Scheiber, Natalia Bedoya, Bernd Schuscha, Dominik Brandl, Lorenz Romaner, Jürgen Spitaler

Published in: BHM Berg- und Hüttenmännische Monatshefte

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Abstract

MCL is putting into practice a new paradigm for materials design based on an iterative process using Active Learning and a Bayesian optimization. In this context, we have built up the materials acceleration platform ALPmat (Active Learning Platform for materials design), which serves as infrastructure for data management and to run workflows for targeted material optimization based on inverse design algorithms. We present the new materials design process together with the architecture of the ALPmat. Moreover, we demonstrate the functionality of ALPmat for the optimization of bainitic steels in terms of yield strength and uniform elongation and present the related method development in terms of workflows, data management, and modeling.

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Literature
3.
go back to reference D. Xue, P. V. Balachandran, J. Hogden, J. Theiler, D. Xue, and T. Lookman, “Accelerated search for materials with targeted properties by adaptive design,” Nat. Commun., vol. 7, no. 1, p. 11241, Apr. 2016, https://doi.org/10.1038/ncomms11241. D. Xue, P. V. Balachandran, J. Hogden, J. Theiler, D. Xue, and T. Lookman, “Accelerated search for materials with targeted properties by adaptive design,” Nat. Commun., vol. 7, no. 1, p. 11241, Apr. 2016, https://​doi.​org/​10.​1038/​ncomms11241.
Metadata
Title
Accelerated Materials Design and Materials Data Management at MCL
Authors
Daniel Scheiber
Natalia Bedoya
Bernd Schuscha
Dominik Brandl
Lorenz Romaner
Jürgen Spitaler
Publication date
16-04-2024
Publisher
Springer Vienna
Published in
BHM Berg- und Hüttenmännische Monatshefte
Print ISSN: 0005-8912
Electronic ISSN: 1613-7531
DOI
https://doi.org/10.1007/s00501-024-01456-6

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