Computational Approach to the Muon Dynamics in Materials
Abstract
We develop ways to simulate the muon dynamics in energy-storage materials and organic oligomers taking into account the thermal effects at ambient temperatures with the use of machine learning or related techniques. We try to establish new techniques how to calculate the dynamic motion of the muon which is trapped at local minimum potential positions within energy-storage materials. We also aim to reproduce changes in hyperfine field at muon positions against temperature in the case of that the attached muon to oligomer molecules is vibrating with the molecule following its dynamics motion.
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