Tian Yu, Yan Zefan, Jiang Lin, Liu Rongzheng, Liu Bing, Shao Youlin, Yang Xu, Liu Malin
Institute of Nuclear and New Energy Technology, Tsinghua University, Beijing 100084, China.
Hunan Valin Xiangtan Iron and Steel Co., Ltd., Xiangtan 411101, China.
Materials (Basel). 2024 Oct 21;17(20):5131. doi: 10.3390/ma17205131.
Chemical vapor deposition (CVD) is a crucial technique in the preparation of high-quality thin films and coatings, and is widely used in various industries including semiconductor, optics, and nuclear fuel, due to its operation simplicity and high growth rate. The complexity of the CVD process arises from numerous parameters, such as precursor chemistry, temperature, pressure, gas flow dynamics, and substrate characteristics. These multiscale parameters make the optimization of the CVD process a challenging task. Numerical simulations are widely used to model and analyze the CVD complex systems, and can be divided into nanoscale, mesoscale, and macroscale methods. Numerical simulation is aimed at optimizing the CVD process, but the inter-scale parameters still need to be extracted in modeling processes. However, multiscale coupling modeling becomes a powerful method to solve these challenges by providing a comprehensive framework that integrates phenomena occurring at different scales. This review presents an overview of the CVD process, the common critical parameters, and an in-depth analysis of CVD models in different scales. Then various multiscale models are discussed. This review highlights the models in different scales, integrates these models into multiscale frameworks, discusses typical multiscale coupling CVD models applied in practice, and summarizes the parameters that can transfer information between different scales. Finally, the schemes of multiscale coupling are given as a prospective view. By offering a comprehensive view of the current state of multiscale CVD models, this review aims to bridge the gap between theory and practice, and provide insights that could lead to a more efficient and precise control of the CVD process.
化学气相沉积（CVD）是制备高质量薄膜和涂层的关键技术，因其操作简单且生长速率高，在半导体、光学和核燃料等各个行业中得到广泛应用。CVD 过程的复杂性源于众多参数，如前驱体化学性质、温度、压力、气体流动动力学和衬底特性。这些多尺度参数使得 CVD 过程的优化成为一项具有挑战性的任务。数值模拟被广泛用于对 CVD 复杂系统进行建模和分析，可分为纳米尺度、介观尺度和宏观尺度方法。数值模拟旨在优化 CVD 过程，但在建模过程中仍需提取跨尺度参数。然而，多尺度耦合建模通过提供一个整合不同尺度现象的综合框架，成为解决这些挑战的有力方法。本综述概述了 CVD 过程、常见的关键参数，并深入分析了不同尺度的 CVD 模型。然后讨论了各种多尺度模型。本综述重点介绍了不同尺度的模型，将这些模型整合到多尺度框架中，讨论了实际应用的典型多尺度耦合 CVD 模型，并总结了可在不同尺度之间传递信息的参数。最后，给出了多尺度耦合方案作为前瞻性展望。通过全面介绍多尺度 CVD 模型的当前状态，本综述旨在弥合理论与实践之间的差距，并提供有助于更高效、精确控制 CVD 过程的见解。
