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| 过渡金属硫族化合物的可控生长：机理分析与模拟挑战 |
| Controllable growth of transition metal chalcogenide: mechanism analysis and simulation challenges |
| 投稿时间：2025-06-28 |
| DOI：10.3969/j.issn.1005-5630.202506280084 |
| 中文关键词: 化学气相沉积 过渡金属硫族化合物 数值模拟 生长参数 |
| 英文关键词:chemical vapor deposition transition metal chalcogenides numerical simulation growth parameters |
| 基金项目:国家自然科学基金（121040140）；大学生创新创业训练计划项目（S202510370570，S202510370549） |
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| 中文摘要: |
| 随着过渡金属硫族化合物（transition metal chalcogenides，TMDCs）薄膜材料在微电子、光电器件和能源存储等领域的快速发展，获取大尺寸、高性能TMDCs的需求日益增长。化学气相沉积（chemical vapor deposition，CVD）作为一种重要的制备技术，因其优异的可控性和规模化生产能力而备受关注。然而，优良的制备工艺高度依赖温度、前驱体浓度和气体流速等关键参数，以及反应器内流体动力学和化学反应的协同作用，导致工艺优化面临重大挑战。本文综述了CVD工艺中影响TMDCs薄膜质量与沉积效率的核心参数，并重点探讨了TMDCs的CVD调控机制。通过数值模拟方法，系统分析了气体流动、传热传质及表面化学反应对薄膜均匀性和结晶质量的影响。研究表明，数值模拟不仅能够深入解析TMDCs生长的物理化学过程，还可为实验工艺优化提供指导。然而，多物理场耦合模型的建立、跨尺度模拟方法的开发以及实验-模拟数据的协同验证仍是当前面临的主要挑战。 |
| 英文摘要: |
| With the rapid development of transition metal chalcogenides (TMDCs) thin-film materials in microelectronics, optoelectronic devices, and energy storage applications, the demand for wafer-scale, high-performance TMDCs has grown significantly. Chemical vapor deposition (CVD), as a critical synthesis technique, has attracted considerable attention due to its superior controllability and scalability. However, optimizing the fabrication process highly depends on key parameters such as temperature, precursor concentration, and gas flow rate, as well as the synergistic interplay between fluid dynamics and chemical reactions within the reactor, posing significant challenges for process refinement. This review summarizes the core parameters influencing the quality and deposition efficiency of TMDCs thin films in CVD processes, with a particular focus on the regulatory mechanisms governing TMDCs growth. Through numerical simulation methods, we systematically analyze the effects of gas flow dynamics, heat and mass transfer, and surface chemical reactions on film uniformity and crystallinity. Multiple researches have demonstrated that numerical simulations not only provide deep insights into the physicochemical nature of TMDCs growth but also offer quantitative guidance for experimental process optimization. However, it still remains key challenges, including the establishment of multi-physics coupled models, the development of multiscale simulation approaches, and the synergistic validation of experimental and computational data. |
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