Computational Investigation of Polymer-Perovskite Interfacial Interactions for Energy Storage Applications: DFT Insights and Machine Learning Potential Assessment

Lead-free halide perovskite supercapacitors show promise, but PVDF binder adhesion mechanisms remain unclear. We use DFT+D3 calculations to investigate PVDF oligomer adsorption on CsSnCl₃(100) surfaces, examining orientation-dependent binding, termination effects, and Li⁺ transport at polymer-covered interfaces. Electronic structure analysis reveals charge redistribution and work function modifications. We benchmark machine learning potentials against DFT data to assess their accuracy for polymer-perovskite systems, establishing feasibility for finite-temperature dynamics studies of these interfaces.This study provides foundational understanding of binder-perovskite interactions while identifying promising ML frameworks for efficient exploration of electrode design space in lead-free supercapacitor applications.