Machine-learning interatomic potentials (GAP, MACE) combined with lattice dynamics and NEMD predict thermal boundary resistance at silicon grain boundaries that is sensitive to interfacial roughness and differs substantially from classical potential predictions at high roughness.
Chen,Nanoscale Energy Transport and Conversion(Oxford University Press, 2005)
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Phonon-Mediated Thermal Transport in Nanocrystalline Silicon Using Machine-Learning Interatomic Potentials
Machine-learning interatomic potentials (GAP, MACE) combined with lattice dynamics and NEMD predict thermal boundary resistance at silicon grain boundaries that is sensitive to interfacial roughness and differs substantially from classical potential predictions at high roughness.