Crystal-like thermal transport in amorphous carbon
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arXiv
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| Format: | Preprint |
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2024
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| _version_ | 1866929340985376768 |
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| author | Moon, Jaeyun Tian, Zhiting |
| author_facet | Moon, Jaeyun Tian, Zhiting |
| contents | 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 Wm\textsuperscript{-1}K\textsuperscript{-1}, comparable to crystalline sapphire ($α$-Al\textsubscript{2}O\textsubscript{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 ($\sim$ 10\textsuperscript{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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2405_07298 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Crystal-like thermal transport in amorphous carbon Moon, Jaeyun Tian, Zhiting Disordered Systems and Neural Networks Materials Science 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 Wm\textsuperscript{-1}K\textsuperscript{-1}, comparable to crystalline sapphire ($α$-Al\textsubscript{2}O\textsubscript{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 ($\sim$ 10\textsuperscript{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. |
| title | Crystal-like thermal transport in amorphous carbon |
| topic | Disordered Systems and Neural Networks Materials Science |
| url | https://arxiv.org/abs/2405.07298 |