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Seeking kinetic pathways relevant to the structural evolution of metal nanoparticles

Understanding the kinetic pathways that cause metal nanoparticles to structurally evolve over time is essential for predicting their shape and size distributions and catalytic properties. Consequently, we need detailed kinetic models that can provide such information. Most kinetic Monte Carlo models used for metal systems contain a fixed catalogue of atomic moves; the catalogue is largely constructed based on our physical understanding of the material. In some situations, it is possible that an incorrect picture of the overall dynamics is obtained when kinetic pathways that are relevant to the dynamics are missing from the catalogue. Hence, a computational framework that can systematically determine the relevant pathways is required. This work intends to fulfil this requirement. Examples involving an Ag nanoparticle are studied to illustrate how molecular dynamics (MD) calculations can be employed to find the relevant pathways in a system. Since pathways that are unlikely to be selected at short timescales can become relevant at longer times, the accuracy of the catalogue is maintained by continually seeking these pathways using MD. We discuss various aspects of our approach, namely, defining the relevance of atomic moves to the dynamics and determining when additional MD is required to ensure the desired accuracy, as well as physical insights into the Ag nanoparticle.