Machine learning (ML) has experienced rapid development in recent years and been widely applied to assist studies in various research areas. Two-dimensional (2D) materials, due to their unique chemical and physical properties, have been receiving increasing attention since the isolation of graphene. The combination of ML and 2D materials science has significantly accelerated the development of new functional 2D materials, and a timely review may inspire further ML-assisted 2D materials development. In this review, we provide a horizontal and vertical summary of the recent advances at the intersection of the fields of ML and 2D materials, discussing ML-assisted 2D materials preparation (design, discovery, and synthesis of 2D materials), atomistic structure analysis (structure identification and formation mechanism), and properties prediction (electronic properties, thermodynamic properties, mechanical properties, and other properties) and revealing their connections. Finally, we highlight current research challenges and provide insight into future research opportunities.

机器学习（ML）近年来经历了快速发展，并被广泛应用于辅助各个研究领域的研究。自从分离出石墨烯以来，二维 (2D) 材料由于其独特的化学和物理特性而受到越来越多的关注。ML 和 2D 材料科学的结合显着加速了新功能 2D 材料的开发，及时审查可能会激发 ML 辅助 2D 材料的进一步开发。在这篇综述中，我们对机器学习和二维材料领域交叉领域的最新进展进行了横向和纵向总结，讨论了机器学习辅助的二维材料制备（二维材料的设计、发现和合成）、原子结构分析（结构识别和形成机制），和特性预测（电子特性、热力学特性、机械特性和其他特性）并揭示它们之间的联系。最后，我们强调当前的研究挑战并提供对未来研究机会的见解。