Abstract

The atomic trajectories of condensed phase systems often reduce to long periods of thermal vibration interspersed by transitions between local free energy minima. The resultant rare event dynamics are exponentially sensitive to the catalog of available transitions, meaning incomplete models can make catastrophically erroneous predictions. This review summarises some recent efforts towards quantifying this uncertainty. I show that Bayesian methods can rigorously measure sampling incompleteness, be propagated to yield a quantified prediction uncertainty and autonomously manage massively parallel simulations. These methods allow uncertainty-controlled investigation of complex atomistic processes with minimal end-user supervision, facilitating high-throughput workflows. For individual transitions rates, I also show how the activation free energy can be evaluated with full treatment of anharmonic thermal vibrations. The developed methods, all freely available, are demonstrated on a wide range of challenging materials science problems.

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