CRISP: Enhancing ASE Workflows With Advanced Molecular Simulation Post-Processing

Molecular simulations are invaluable for analysing molecular systems, but existing post-processing tools are often limited by a lack of customization, interactivity, and efficiency with large datasets. To address this, we developed CRISP (Comprehensive Repository for Insightful Simulation Post-Processing), an open-source Python toolkit designed to enhance workflows within the Atomic Simulation Environment (ASE). CRISP provides a versatile platform for detailed analysis and visualization, featuring a customizable and modular design, various static analysis methods, interactive 3D visualizations, and parallel processing capabilities optimized for high-performance computing. We demonstrate its effectiveness through case studies, including the analysis of statistical convergence in zeolite simulations, subsampling large datasets for machine learning, and analysing the dynamic stability of atomic clusters. CRISP effectively bridges the gap between raw simulation data and actionable insights, offering an efficient solution for researchers and saving significant time in code development.