Kavli Affiliate: Zhiting Tian
| First 5 Authors: Jaeyun Moon, Zhiting Tian, , ,
| Summary:
Thermal transport properties of amorphous carbon has attracted increasing
attention due to its extreme thermal properties: It has been reported to have
among the highest thermal conductivity for bulk amorphous solids up to $sim$
37 Wmtextsuperscript{-1}Ktextsuperscript{-1}, comparable to crystalline
sapphire ($alpha$-Altextsubscript{2}Otextsubscript{3}). Further, large
density dependence in thermal conductivity demonstrates a potential for largely
tunable thermal conductivity. However, mechanism behind the high thermal
conductivity and its large density dependence remains elusive due to many
variables at play. In this work, we perform large-scale ($sim$
10textsuperscript{5} atoms) molecular dynamics simulations utilizing a machine
learning potential based on neural networks. Through spectral decomposition of
thermal conductivity which enables a quantum correction to classical heat
capacity, we find that propagating vibrational excitations govern thermal
transport in amorphous carbon ($sim$ 100 % of thermal conductivity) in sharp
contrast to the conventional wisdom that diffusive vibrational excitations
dominate thermal transport in amorphous solids. Instead, this remarkable
behavior resembles thermal transport in simple crystals. Moreover, our
temperature dependent spectral diffusivity and velocity current correlation
analyses reveal that the density dependent thermal conductivity originates from
anharmonicity sensitive propagating excitations. Our work suggests a novel
insight and design principle into developing mechanically hard, thermally
conductive amorphous solids.
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