SCI和EI收录∣中国化工学会会刊

Chinese Journal of Chemical Engineering ›› 2025, Vol. 79 ›› Issue (3): 172-184.DOI: 10.1016/j.cjche.2024.10.032

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Toward the rational design for low-temperature hydrogenation of silicon tetrachloride: Mechanism and data-driven interpretable descriptor

Zhe Ding1,2, Li Guo1,2, Fang Bai1,3, Chao Hua1,3,4, Ping Lu1,4, Jinyi Chen1,3   

  1. 1. Key Laboratory of Green Process and Engineering, Institute of Process Engineering, Chinese Academy of Sciences, Beijing 100190, China;
    2. School of Chemical Engineering, University of Chinese Academy of Sciences, Beijing 100049, China;
    3. Hubei Three Gorges Laboratory, Yichang 443000, China;
    4. State Key Laboratory of Petroleum Molecular & Process Engineering, Beijing 100190, China
  • Received:2024-03-21 Revised:2024-10-24 Accepted:2024-10-25 Online:2025-01-09 Published:2025-03-28
  • Supported by:
    This work was supported by Hubei Three Gorges Laboratory Open Innovation Fund Project (SC231002) and CFD Simulation to Explore the Mass and Heat Transfer Laws of Thermal Decomposition of Mixed Salt Organic Compounds Project (2021YFC3201404).

Toward the rational design for low-temperature hydrogenation of silicon tetrachloride: Mechanism and data-driven interpretable descriptor

Zhe Ding1,2, Li Guo1,2, Fang Bai1,3, Chao Hua1,3,4, Ping Lu1,4, Jinyi Chen1,3   

  1. 1. Key Laboratory of Green Process and Engineering, Institute of Process Engineering, Chinese Academy of Sciences, Beijing 100190, China;
    2. School of Chemical Engineering, University of Chinese Academy of Sciences, Beijing 100049, China;
    3. Hubei Three Gorges Laboratory, Yichang 443000, China;
    4. State Key Laboratory of Petroleum Molecular & Process Engineering, Beijing 100190, China
  • 通讯作者: Jinyi Chen,E-mail:chenjy@ipe.ac.cn
  • 基金资助:
    This work was supported by Hubei Three Gorges Laboratory Open Innovation Fund Project (SC231002) and CFD Simulation to Explore the Mass and Heat Transfer Laws of Thermal Decomposition of Mixed Salt Organic Compounds Project (2021YFC3201404).

Abstract: Low-temperature hydrogenation of silicon tetrachloride (STC) is an essential step in polysilicon production. The addition of CuCl to silicon powder is currently a commonly used catalytic method and the silicon powder acts as both a reactant and a catalyst. However, the reaction mechanism and the structure-activity relationship of this process have not been fully elucidated. In this work, a comprehensive study of the reaction mechanism in the presence of Si and Cu3Si was carried out using density functional theory (DFT) combined with experiments, respectively. The results indicated that the rate-determining step (RDS) in the presence of Si is the phase transition of Si atom, meanwhile, the RDS in the presence of Cu3Si is the TCS-generation process. The activation barrier of the latter is smaller, highlighting that the interaction of Si with the bulk phase is the pivotal factor influencing the catalytic activity. The feasibility of transition metal doping to facilitate this step was further investigated. The Si disengage energy (Ed) was used as a quantitative parameter to assess the catalytic activity of the catalysts, and the optimal descriptor was determined through interpretable machine learning. It was demonstrated that d-band center and electron transfer play a crucial role in regulating the level of Ed. This work reveals the mechanism and structure-activity relationship for the low-temperature hydrogenation reaction of STC, and provides a basis for the rational design of catalysts.

Key words: Silicon tetrachloride, Hydrogenation, Reaction mechanism, Interpretable machine learning, Catalyst, Structure-activity relationship

摘要: Low-temperature hydrogenation of silicon tetrachloride (STC) is an essential step in polysilicon production. The addition of CuCl to silicon powder is currently a commonly used catalytic method and the silicon powder acts as both a reactant and a catalyst. However, the reaction mechanism and the structure-activity relationship of this process have not been fully elucidated. In this work, a comprehensive study of the reaction mechanism in the presence of Si and Cu3Si was carried out using density functional theory (DFT) combined with experiments, respectively. The results indicated that the rate-determining step (RDS) in the presence of Si is the phase transition of Si atom, meanwhile, the RDS in the presence of Cu3Si is the TCS-generation process. The activation barrier of the latter is smaller, highlighting that the interaction of Si with the bulk phase is the pivotal factor influencing the catalytic activity. The feasibility of transition metal doping to facilitate this step was further investigated. The Si disengage energy (Ed) was used as a quantitative parameter to assess the catalytic activity of the catalysts, and the optimal descriptor was determined through interpretable machine learning. It was demonstrated that d-band center and electron transfer play a crucial role in regulating the level of Ed. This work reveals the mechanism and structure-activity relationship for the low-temperature hydrogenation reaction of STC, and provides a basis for the rational design of catalysts.

关键词: Silicon tetrachloride, Hydrogenation, Reaction mechanism, Interpretable machine learning, Catalyst, Structure-activity relationship