Abstract The emergence of two-dimensional (2D) materials has captured the imagination of researchers since graphene was first exfoliated from graphite in 2004. Their exotic properties give rise to many exciting potential applications in advanced electronic, optoelectronic, energy and biomedical technologies. Scalable growth of high quality 2D materials is crucial for their adoption in technological applications the same way the arrival of high quality silicon single crystals was to the semiconductor industry. A huge amount of effort has been devoted to grow large-area, highly crystalline 2D crystals such as graphene and transition metal dichalcogenides (TMDs) through various methods. While CVD growth of wafer-scale monolayer graphene and TMDs has been demonstrated, considerable challenges still remain. In this perspective, we advocate for the focus on the crystal growth morphology as an underpinning for understanding, diagnosing and controlling the CVD process and environment for 2D material growth. Like snowflakes in nature, 2D crystals exhibit a rich variety of morphologies under different growth conditions. The mapping of crystal shapes in the growth parameter space “encodes” a wealth of information, the deciphering of which will lead to better understanding of the fundamental growth mechanism and materials properties. To this end, we envision a collective effort by the 2D materials community to establish the correlation between crystal shapes and the intrinsic thermodynamic and kinetic parameters for CVD reactions through integrated crystal growth experiment, database development and machine learning assisted predictive modeling, which will pave a robust path towards controlled synthesis of 2D materials and heterostructures.

中文翻译：

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通过化学气相沉积 (CVD) 实现二维晶体的可控合成

摘要 自 2004 年石墨烯首次从石墨中剥离以来，二维 (2D) 材料的出现吸引了研究人员的想象力。它们的奇异特性在先进的电子、光电、能源和生物医学技术中产生了许多令人兴奋的潜在应用。高质量 2D 材料的可扩展增长对于它们在技术应用中的采用至关重要，就像高质量硅单晶进入半导体行业一样。大量的努力致力于通过各种方法生长大面积、高度结晶的二维晶体，​​如石墨烯和过渡金属二硫属化物 (TMD)。虽然晶圆级单层石墨烯和 TMD 的 CVD 生长已经得到证明，但仍然存在相当大的挑战。从这个角度来看，我们主张关注晶体生长形态，以此作为理解、诊断和控制 CVD 工艺和二维材料生长环境的基础。就像自然界中的雪花一样，二维晶体在不同的生长条件下表现出丰富多样的形态。生长参数空间中晶体形状的映射“编码”了大量信息，破译这些信息将有助于更好地理解基本的生长机制和材料特性。为此，我们设想 2D 材料社区共同努力，通过集成的晶体生长实验、数据库开发和机器学习辅助预测建模，建立晶体形状与 CVD 反应的内在热力学和动力学参数之间的相关性，