9:15 AM - 9:30 AM
▼ [24a-E203-2] Application of combinatorial group theory to the atomic substitution problem
Keywords:materials informatics, high-throughput
Supercell model is often utilized to study a disordered system within periodic ab-initio framework. In this model, a supercell is created in which a certain number of target elements are substituted. The key problem in the generation of supercells is how to identify and eliminate symmetry-equivalent structures from a vast number of substitution patterns. These structures are physically identical, and thus redundant for ab-initio simulations. By reducing the number of considered structures to only those which are symmetrically unique, the computational cost can be reduced by various order of magnitude.
In this work, we mapped the atomic substitution problem into a graph coloring problem, implementing canonical augmentation as the isomorph rejection technique. In this approach, symmetry-equivalent structures are pruned in a search tree, covering the space of all possible substitutions, without directly comparing the structures. To further improve rejection efficiency, we also incorporated quantities derived from the structural information into the algorithm.
Built upon these concepts, we developed a python package, called SHRY (Suite for High-throughput generation of models with atomic substitutions implemented by python), whose main function is to identify and select, from any given structures, a single representative structure for each symmetry-equivalent class of structures. We benchmarked its performance against existing approaches, confirming its significant efficiency over existing approaches.
In this work, we mapped the atomic substitution problem into a graph coloring problem, implementing canonical augmentation as the isomorph rejection technique. In this approach, symmetry-equivalent structures are pruned in a search tree, covering the space of all possible substitutions, without directly comparing the structures. To further improve rejection efficiency, we also incorporated quantities derived from the structural information into the algorithm.
Built upon these concepts, we developed a python package, called SHRY (Suite for High-throughput generation of models with atomic substitutions implemented by python), whose main function is to identify and select, from any given structures, a single representative structure for each symmetry-equivalent class of structures. We benchmarked its performance against existing approaches, confirming its significant efficiency over existing approaches.