Abstract

The successful discovery and isolation of graphene in 2004, and the subsequent synthesis of layered semiconductors and heterostructures beyond graphene have led to the exploding field of two-dimensional (2D) materials that explore their growth, new atomic-scale physics, and potential device applications. This review aims to provide an overview of theoretical, computational, and machine learning methods and tools at multiple length and time scales, and discuss how they can be utilized to assist/guide the design and synthesis of 2D materials beyond graphene. We focus on three methods at different length and time scales as follows: (i) nanoscale atomistic simulations including density functional theory (DFT) calculations and molecular dynamics simulations employing empirical and reactive interatomic potentials; (ii) mesoscale methods such as phase-field method; and (iii) macroscale continuum approaches by coupling thermal and chemical transport equations. We discuss how machine learning can be combined with computation and experiments to understand the correlations between structures and properties of 2D materials, and to guide the discovery of new 2D materials. We will also provide an outlook for the applications of computational approaches to 2D materials synthesis and growth in general.

Highlights

  • The perfection and physical properties of atomically thin twodimensional (2D) materials are extremely sensitive to their synthesis and growth process

  • Two main approaches have been employed for the synthesis of 2D materials, i.e., (i) top-down approaches such as mechanical[2] and liquid-phase exfoliation that allows scalability[3], and (ii) bottom-up approaches such as chemical vapor deposition (CVD) and atomic layer deposition techniques[4]

  • The goal of this review is to provide an overview of the main theoretical and computational methods for understanding the thermodynamics and kinetics of mass transport, reaction, and growth mechanisms during synthesis of 2D materials

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Summary

Introduction

The perfection and physical properties of atomically thin twodimensional (2D) materials are extremely sensitive to their synthesis and growth process. As the energies in the FF model are additive, this potential has been widely used to calculate physical or mechanical properties for various materials via analytic expressions, including many 2D

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