Harmony-Search-Based Global Optimization
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Scalable Prediction of Complex Surface Reconstructions under Operating Conditions via Harmony-Search-Based Global Optimization
Announce Type: cross Abstract: The dynamic structural evolution of catalyst surfaces under operating conditions dictates catalytic performance, yet capturing these reconstructions atomically remains challenging. Global optimization based on machine learning interatomic potentials (MLIPs) is promising, but scaling to large-scale, low-symmetry operando systems is hindered by expansive search spaces and potential energy surface (PES) inaccuracies. Herein, we present Harmony-search-based Atomic...