On-the-fly machine learning force field generation: Application to melting points

Understand

An efficient and robust on-the-fly machine learning force field method is developed and integrated into an electronic-structure code.

• This method realizes automatic generation of machine learning force fields on the basis of Bayesian inference during molecular dynamics simulations, where the first principles calculations are only executed, when new configurations out of already sampled datasets appear.
• The developed method is applied to the calculation of melting points of Al, Si, Ge, Sn and MgO.
• The applications indicate that more than 99 \% of the first principles calculations are bypassed during the force field generation.