Continuous transition from palladium clusters to nanocrystals simulated by machine learning potential

Understanding the atomic evolution from cluster to nanocrystal has long been a challenge in nanoscience. Here, an accurate machine learning potential (MLP) of elemental Pd was developed. The large-scale capacity of this MLP affords long-time simulated annealing for a cross-scale study of Pd${}_{n}$ nanostructures ($n$=12 - 21856), revealing a continuous transition from discrete clusters to bulk-like nanocrystals and the critical size at which the transition occurs. This study paves the way for studies on other clusters.