Atomistic simulations of Au-alkane-Au junctions reveal coexisting ballistic and diffusive heat transport with conductivity diverging as L^{1/3} up to micrometer lengths at room temperature.
Highly opti- mized embedded-atom-method potentials for fourteen fcc metals,
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ML model using ideal entropy plus simulation features (energy above hull, heat capacity change, icosahedral fraction) predicts metallic glass critical cooling rates with R²=0.78 in leave-one-chemical-system-out cross-validation on 34 alloys.
citing papers explorer
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Coexisting Ballistic and Diffusive Heat Transport in Micrometer-Long Molecular Junctions
Atomistic simulations of Au-alkane-Au junctions reveal coexisting ballistic and diffusive heat transport with conductivity diverging as L^{1/3} up to micrometer lengths at room temperature.
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Machine learning metallic glass critical cooling rates through elemental and molecular simulation based featurization
ML model using ideal entropy plus simulation features (energy above hull, heat capacity change, icosahedral fraction) predicts metallic glass critical cooling rates with R²=0.78 in leave-one-chemical-system-out cross-validation on 34 alloys.