Accelerating active learning materials discovery with FAIR data and workflows: A case study for alloy melting temperatures

Active learning (AL) is a powerful sequential optimization approach that has shown great promise in the discovery of new materials. However, a major challenge remains the acquisition of the initial data and the development of workflows to generate new data at each iteration. In this study, we demons...

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Bibliographic Details

Published in:	Computational materials science Vol. 249; p. 113640
Main Authors:	Harwani, Mohnish, Verduzco, Juan C., Lee, Brian H., Strachan, Alejandro
Format:	Journal Article
Language:	English
Published:	Elsevier B.V 05.02.2025
Subjects:	Active Learning FAIR data FAIR data Active Learning
ISSN:	0927-0256
Online Access:	Get full text
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