与机器学习相结合的计算材料学实验设计

doi:10.12461/PKU.DXHX202406004

University Chemistry ›› 2025, Vol. 40 ›› Issue (3): 171-177.doi: 10.12461/PKU.DXHX202406004

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Experimental Design of Computational Materials Science Combined with Machine Learning

Jia Zhou, Huaying Zhong

State Key Laboratory of Urban Water Resource and Environment, School of Science, Harbin Institute of Technology (Shenzhen), Shenzhen 518055, Guangdong Province, China

Received:2024-06-03 Accepted:2024-10-10 Published:2025-03-19
Contact: Jia Zhou E-mail:jiazhou@hit.edu.cn

Abstract

Abstract: This paper presents a comprehensive computational materials science experiment designed for senior undergraduate and graduate students. The band gaps of two-dimensional materials are investigated using materials simulation and machine learning techniques. Through this experiment, students will gain a foundational understanding of machine learning principles and workflows, while also developing their ability to apply first-principles calculations and machine learning to solve materials-related problems.

Key words: Two-dimensional materials, Materials simulation, First-principles, Machine learning, Band gaps

Jia Zhou, Huaying Zhong. Experimental Design of Computational Materials Science Combined with Machine Learning[J].University Chemistry, 2025, 40(3): 171-177.

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Experimental Design of Computational Materials Science Combined with Machine Learning

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