Electronic structure calculations of twisted multi-layer graphene superlattices. (18th June 2020)

• Record Type: Journal Article
• Authors: Tritsaris, Georgios A; Carr, Stephen; Zhu, Ziyan; Xie, Yiqi; Torrisi, Steven B; Tang, Jing; Mattheakis, Marios; Larson, Daniel T; Kaxiras, Efthimios
• Is Part Of: 2D materials. Volume 7:Number 3(2020)
• Publication Date: 2020-06-18
• Subjects: tight binding -- machine learning -- high-throughput calculations -- electronic band structure -- twistronics -- materials informatics -- quantum materials; Graphene -- Periodicals; Materials science -- Periodicals; Nanostructured materials -- Periodicals; 620.115
• DOI: 10.1088/2053-1583/ab8f62
• Languages: English
• ISSNs: 2053-1583

Abstract

Abstract: 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.