Uncertainty quantification of Kinetic Monte Carlo models constructed on-the-fly using molecular dynamics

Kinetic Monte Carlo (KMC) models of complex materials and biomolecules are increasingly being constructed using molecular dynamics (MD). A KMC model contains a catalog of states and kinetic pathways, which enables study of the dynamics. The completeness of the catalog is crucial to the model accuracy and is linked to the quality of the MD data used for model construction. Therefore, quantifying the uncertainty clue to missing states and pathways is important. A review on computational procedures available for on-the-fly KMC model construction using MD, uncertainty measurement, and algorithms for guiding further MD sampling in an accelerated manner is presented