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Electronic structure calculations of twisted multi-layer graphene superlattices

Georgios A. Tritsaris1*, Stephen Carr2, Ziyan Zhu2, Yiqi Xie1, Steven B. Torrisi2, Jing Tang3, Marios Mattheakis1, Daniel Larson2, Efthimios Kaxiras2*

1 John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts 02138, USA

2 Department of Physics, Harvard University, Cambridge, Massachusetts 02138, USA

3 Department of Physics, Nanjing University, Nanjing, 210093, China

* Corresponding authors emails: gtritsaris@seas.harvard.edu, kaxiras@physics.harvard.edu
DOI10.24435/materialscloud:2020.0050/v1 [version v1]

Publication date: May 04, 2020

How to cite this record

Georgios A. Tritsaris, Stephen Carr, Ziyan Zhu, Yiqi Xie, Steven B. Torrisi, Jing Tang, Marios Mattheakis, Daniel Larson, Efthimios Kaxiras, Electronic structure calculations of twisted multi-layer graphene superlattices, Materials Cloud Archive 2020.0050/v1 (2020), doi: 10.24435/materialscloud:2020.0050/v1.


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.

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393.8 MiB Tight binding band structures of twisted multi-layer graphene superlattices.


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External references

Journal reference
G. A. Tritsaris, S. Carr, Z. Zhu, Y. Xie, S. B. Torrisi, J. Tang, M. Mattheakis, D. Larson, E. Kaxiras, 2D Mater. 7, 035028 (2020) doi:10.1088/2053-1583/ab8f62
Journal reference (Paper in which a materials notation for 2D layered assemblies is described.)
G. A. Tritsaris, Y. Xie, A. M. Rush, S. Carr, M. Mattheakis, and E. Kaxiras, J. Chem. Inf. Model. (2020) doi:10.1021/acs.jcim.0c00630
Website (Interactive visualization of tight binding band structures of twisted multi-layer graphene superlattices.)


Graphene 2D layered materials High-throughput calculations Tight binding band structures Machine learning Twistronics Quantum devices

Version history:

2020.0050/v1 (version v1) [This version] May 04, 2020 DOI10.24435/materialscloud:2020.0050/v1