Determining the Potential of Maximum Entropy from Ab Initio Molecular Dynamics

Understanding electrochemical interfaces at the atomic level is essential for optimizing catalytic performance in energy conversion and storage technologies. This study introduces a computational framework based on ab initio molecular dynamics (AIMD) simulations to predict the potential of maximum entropy (PME) a descriptor of electric double layer disorder and charge transfer efficiency. By integrating AIMD with the generalized computational hydrogen electrode, it is systematically investigated how electrolyte composition, cation identity, and pH effect the position of PME. The approach reproduces experimental shifts in PME for Au and Pt electrodes and provides unprecedented insights into the emergence of multiple PME values in mixed-cation systems. The findings challenge conventional models of electrolyte structuring by revealing the presence of multiple PME values within mixed-cation systems. This suggests a more complex interplay between cations, adsorbates, and interfacial disorder than previously assumed. The computational framework developed in this study provides a predictive tool for understanding these interactions, offering new strategies for tuning electrocatalytic activity.