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Design and Preparation of High-Entropy Nitride Ceramics via Machine Learning
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Juan LIU1, 2, Chuanjin TIAN1, Chang'an WANG2
Journal of the Chinese Ceramic Society | 2023, 51(12) : 3095 - 3101
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Journal of the Chinese Ceramic Society | 2023, 51(12): 3095-3101
• Research Articles •
Design and Preparation of High-Entropy Nitride Ceramics via Machine Learning
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Juan LIU1, 2, Chuanjin TIAN1, Chang'an WANG2
Affiliations
  • 1.School of Materials Science and Engineering, Jingdezhen Ceramic Institute, Jingdezhen 333403, Jiangxi, China
  • 2.State Key Laboratory of New Ceramics and Fine Processing, School of Materials Science and Engineering, Tsinghua University, Beijing 100084, China
  • LIU Juan (1996-), female, Master candidate. E-mail:

About Author:

LIU Juan (1996-), female, Master candidate. E-mail:

Published: 2023-09-11 doi: 10.14062/j.issn.0454-5648.20230234
Outline
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As one of emerging ceramic materials, high-entropy ceramics become a research hotspot in the field of ceramics. However, their compositional design has some challenges for component design based on experimentation and "trial and error". In recent years, the combination of machine learning and experiments can provide an effective method to solve this problem. In this paper, four machine learning models were established, the best-performing gradient-boosting decision tree model (R2=0.92) through training and evaluation was selected for prediction. A single-phase (Ti0.2V0.2Zr0.2Nb0.2Hf0.2)N high-entropy nitride ceramic was then synthesized based on the predication by the model. This effective approach can provide some ideas for the design of high-entropy nitride ceramic and discover new systems.

high-entropy ceramics  /  nitride ceramics  /  machine learning  /  materials design  /  model forecast
刘娟, 田传进, 汪长安. 基于机器学习设计和制备高熵氮化物陶瓷. 硅酸盐学报, 2023 , 51 (12) : 3095 -3101 . DOI: 10.14062/j.issn.0454-5648.20230234
Juan LIU, Chuanjin TIAN, Chang'an WANG. Design and Preparation of High-Entropy Nitride Ceramics via Machine Learning[J]. Journal of the Chinese Ceramic Society, 2023 , 51 (12) : 3095 -3101 . DOI: 10.14062/j.issn.0454-5648.20230234
Year 2023 volume 51 Issue 12
34
6
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Article Info
doi: 10.14062/j.issn.0454-5648.20230234
  • Receive Date:2023-04-10
  • Online Date:2026-10-19
  • Published:2023-09-11
Article Data
Affiliations
History
  • Received:2023-04-10
  • Revised:2023-04-30
Funding
Affiliations
    1.School of Materials Science and Engineering, Jingdezhen Ceramic Institute, Jingdezhen 333403, Jiangxi, China
    2.State Key Laboratory of New Ceramics and Fine Processing, School of Materials Science and Engineering, Tsinghua University, Beijing 100084, China

Corresponding:

WANG Chang'an (1969-), male, Ph.D., Professor. E-mail:
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表12种不同金属材料的力学参数
科
Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)
属
Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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