• 文献标题:   Electronic structure calculations of twisted multi-layer graphene superlattices
  • 文献类型:   Article
  • 作  者:   TRITSARIS GA, CARR S, ZHU ZY, XIE YQ, TORRISI SB, TANG J, MATTHEAKIS M, LARSON DT, KAXIRAS E
  • 作者关键词:   tight binding, machine learning, highthroughput calculation, electronic band structure, twistronic, materials informatic, quantum material
  • 出版物名称:   2D MATERIALS
  • ISSN:   2053-1583
  • 通讯作者地址:   Harvard Univ
  • 被引频次:   3
  • DOI:   10.1088/2053-1583/ab8f62
  • 出版年:   2020

▎ 摘  要

Quantum confinement endows two-dimensional (2D) layered materials with exceptional physics and novel properties compared to their bulk counterparts. Although certain two- and few-layer configurations of graphene have been realized and studied, a systematic investigation of the properties of arbitrarily layered graphene assemblies is still lacking. We introduce theoretical concepts and methods for the processing of materials information, and as a case study, apply them to investigate the electronic structure of multi-layer graphene-based assemblies in a high-throughput fashion. We provide a critical discussion of patterns and trends in tight binding band structures and we identify specific layered assemblies using low-dispersion electronic bands as indicators of potentially interesting physics like strongly correlated behavior. A combination of data-driven models for visualization and prediction is used to intelligently explore the materials space. This work more generally aims to increase confidence in the combined use of physics-based and data-driven modeling for the systematic refinement of knowledge about 2D layered materials, with implications for the development of novel quantum devices.