密度泛函理论
理论(学习稳定性)
表征(材料科学)
过渡金属
结构稳定性
工作(物理)
材料科学
计算机科学
纳米技术
化学物理
化学
计算化学
物理
热力学
机器学习
工程类
催化作用
结构工程
生物化学
作者
Andrey A. Kistanov,S. A. Shcherbinin,Romain Botella,Artur R. Davletshin,Wei Cao
标识
DOI:10.1021/acs.jpclett.2c00367
摘要
A large number of novel two-dimensional (2D) materials are constantly being discovered and deposited in databases. Consolidated implementation of machine learning algorithms and density functional theory (DFT)-based predictions have allowed the creation of several databases containing an unimaginable number of 2D samples. As the next step in this chain, the investigation leads to a comprehensive study of the functionality of the invented materials. In this work, a family of transition metal dichlorides have been screened out for systematic investigation of their structural stability, fundamental properties, structural defects, and environmental stability via DFT-based calculations. The work highlights the importance of using the potential of the invented materials and proposes a comprehensive characterization of a new family of 2D materials.
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