Artificial Intelligence for Materials Science - Springer Series in Materials Science
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(FIVE YEARS 8)

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Published By Springer International Publishing

9783030683092, 9783030683108

Latest Documents Most Cited Documents Contributed Authors Related Sources Related Keywords

Genetic Algorithms

Artificial Intelligence for Materials Science - Springer Series in Materials Science ◽

10.1007/978-3-030-68310-8_5 ◽

2021 ◽

pp. 115-131

Author(s):

Shichang Li ◽

Dengfeng Li

Keyword(s):

Genetic Algorithms

Machine Learning Interatomic Force Fields for Carbon Allotropic Materials

Artificial Intelligence for Materials Science - Springer Series in Materials Science ◽

10.1007/978-3-030-68310-8_4 ◽

2021 ◽

pp. 93-113

Author(s):

Xiangjun Liu ◽

Quanjie Wang ◽

Jie Zhang

Keyword(s):

Machine Learning ◽

Force Fields ◽

Interatomic Force

Thermal Nanostructure Design by Materials Informatics

Artificial Intelligence for Materials Science - Springer Series in Materials Science ◽

10.1007/978-3-030-68310-8_7 ◽

2021 ◽

pp. 153-195

Author(s):

Run Hu ◽

Junichiro Shiomi

Keyword(s):

Materials Informatics

Accelerated Discovery of Thermoelectric Materials Using Machine Learning

Artificial Intelligence for Materials Science - Springer Series in Materials Science ◽

10.1007/978-3-030-68310-8_6 ◽

2021 ◽

pp. 133-152

Author(s):

Rinkle Juneja ◽

Abhishek K. Singh

Keyword(s):

Machine Learning ◽

Thermoelectric Materials

Brief Introduction of the Machine Learning Method

Artificial Intelligence for Materials Science - Springer Series in Materials Science ◽

10.1007/978-3-030-68310-8_1 ◽

2021 ◽

pp. 1-20

Author(s):

Tian Wang

Keyword(s):

Machine Learning ◽

Machine Learning Method ◽

Learning Method

Machine Learning Accelerated Insights of Perovskite Materials

Artificial Intelligence for Materials Science - Springer Series in Materials Science ◽

10.1007/978-3-030-68310-8_8 ◽

2021 ◽

pp. 197-223

Author(s):

Shuaihua Lu ◽

Yilei Wu ◽

Ming-Gang Ju ◽

Jinlan Wang

Keyword(s):

Machine Learning ◽

Perovskite Materials

Two-Way TrumpetNets and TubeNets for Identification of Material Parameters

Artificial Intelligence for Materials Science - Springer Series in Materials Science ◽

10.1007/978-3-030-68310-8_3 ◽

2021 ◽

pp. 59-91

Author(s):

S. Y. Duan ◽

X. Han ◽

G. R. Liu

Keyword(s):

Material Parameters

Machine Learning for High-Entropy Alloys

Artificial Intelligence for Materials Science - Springer Series in Materials Science ◽

10.1007/978-3-030-68310-8_2 ◽

2021 ◽

pp. 21-58

Author(s):

Shuai Chen ◽

Yuan Cheng ◽

Huajian Gao

Keyword(s):

Machine Learning ◽

High Entropy Alloys ◽

High Entropy

Artificial Intelligence for Materials Science - Springer Series in Materials ScienceLatest Publications

TOTAL DOCUMENTS

H-INDEX

Published By Springer International Publishing

Genetic Algorithms

Machine Learning Interatomic Force Fields for Carbon Allotropic Materials

Thermal Nanostructure Design by Materials Informatics

Accelerated Discovery of Thermoelectric Materials Using Machine Learning

Brief Introduction of the Machine Learning Method

Machine Learning Accelerated Insights of Perovskite Materials

Two-Way TrumpetNets and TubeNets for Identification of Material Parameters

Machine Learning for High-Entropy Alloys

Artificial Intelligence for Materials Science - Springer Series in Materials Science
Latest Publications