An active learning high-throughput microstructure calibration framework for solving inverse structure–process problems in materials informatics

标题
An active learning high-throughput microstructure calibration framework for solving inverse structure–process problems in materials informatics
作者
关键词
Microstructure descriptors, Bayesian optimization, Process–structure, Additive manufacturing, Grain growth, Kinetic Monte Carlo, ICME
出版物
ACTA MATERIALIA
Volume 194, Issue -, Pages 80-92
出版商
Elsevier BV
发表日期
2020-05-19
DOI
10.1016/j.actamat.2020.04.054

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