A machine learning accelerated distributed task management system (Malac-Distmas) and its application in high-throughput CALPHAD computation aiming at efficient alloy design

A machine learning accelerated distributed task management system (Malac-Distmas) and its application in high-throughput CALPHAD computation aiming at efficient alloy design

High-throughput calculations/simulations are the prerequisite for the efficient design of high-performance materials. In this paper, a machine learning accelerated distributed task management system (Malac-Distmas) was developed to realize the high-throughput calculations (HTCs) and storage of vario...

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Bibliographic Details
Main Authors: Jianbao Gao, Jing Zhong, Guangchen Liu, Shenglan Yang, Bo Song, Lijun Zhang, Zuming Liu
Format: Article
Language:English
Published: KeAi Communications Co. Ltd. 2022-01-01
Series:Advanced Powder Materials
Subjects:
High throughput
CALPHAD
Machine learning
Thermodynamics
Kinetics
Alloy design
Online Access:http://www.sciencedirect.com/science/article/pii/S2772834X21000051

Internet

http://www.sciencedirect.com/science/article/pii/S2772834X21000051

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