HiMac: High-Throughput Initialization of Multidentate Adsorption Configurations for Geometry Relaxation and...

High-throughput computation is essential for the rational design of heterogeneous catalysts, and the quality of the initial adsorption configurations directly determines the efficiency and success rate of subsequent geometry optimization. Existing heuristic methods are constrained by rigid-body approximations, making it difficult for them to handle complex multidentate adsorption, and the low-precision force field correction schemes on which they rely lack generality. To address this issue, this work proposes a general algorithm, High-Throughput Initialization of Multidentate Adsorption Configurations (HiMac). The algorithm reformulates configuration generation as a multiobjective optimization problem. It employs forward kinematics to model molecular flexibility and combines it with a loss function based on parent molecule similarity, thereby unifying site selection with pose adjustment. A statistical learning module is further integrated to prioritize the exploration of chemically favorable sites and reduce the computational cost. Experiments show that HiMac generates high-quality initial configurations for geometry relaxation and transition-state searches, is applicable to arbitrary adsorbate-surface systems, and provides a general and efficient method to accelerate the rational design of heterogeneous catalysts.