Beyond energetics, the dynamic evolution of these nanoclusters is another important factor from a materials design perspective. In several applications (e.g. catalysis or energy storage), these clusters often undergo structural and dynamical phase transitions from a stable configuration to another. One of the popular approaches to probe the dynamics of these clusters is Ab-Initio Molecular Dynamics (AIMD) . But despite the advancements in computational resources both in terms of hardware and software, the AIMD simulations are limited in the timescales and length-scales that they can access. This also limits the use of high-fidelity calculations such as DFT, in the use of exhaustive structure searches even with the most efficient sampling methods (e.g., evolutionary algo-rithms, basin-hopping, etc.). However, in classical molecular dynamics the atomistic and molecular interactions is such nanoscale systems continues to be described by models that were originally trained to bulk properties.