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

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 (E_d) 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 E_d. 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.