Carbon, volume 192, pages 179-186
Atomistic structure and anomalous heat capacity of low-density liquid carbon: Molecular dynamics study with machine learning potential
Orekhov Nikita D.
1, 2, 3
,
Logunov Mikhail V.
2, 3
Publication type: Journal Article
Publication date: 2022-06-01
General Chemistry
General Materials Science
Abstract
Liquid carbon remains the source of several unsolved questions related to its structure and region of thermodynamic stability. Experiments demonstrate a drastic decrease in the density for liquid carbon along the graphite melting line in the pressure range P = 1–3 GPa and the nature of this phenomenon is unclear. A recent experimental study [A.M. Kondratyev and A.D. Rakhel, PRL (2019)] revealed another peculiar and still unexplained feature of the liquid carbon – its excessive heat capacity. Using classical molecular dynamics with machine learning potential GAP-20, we study the structural properties of liquid carbon and demonstrate that at P < 1–2 GPa it resembles a net of sp -hybridized chains, rather than a typical covalent liquid, with nanoscale porosity of this phase being responsible for the density decrease. We also show that excessive heat capacity could be a direct manifestation of a smooth transition from a high-density sp 2 -hybridized phase into a low-density sp -hybridized.
Citations by journals
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1
2
3
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Journal of Molecular Liquids
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Journal of Molecular Liquids
3 publications, 25%
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Carbon
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Carbon
1 publication, 8.33%
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JETP Letters
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JETP Letters
1 publication, 8.33%
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Journal of Chemical Physics
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Journal of Chemical Physics
1 publication, 8.33%
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Condensed Matter
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Condensed Matter
1 publication, 8.33%
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Modern Physics Letters B
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Modern Physics Letters B
1 publication, 8.33%
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Applied Physics Letters
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Applied Physics Letters
1 publication, 8.33%
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International Journal of Heat and Mass Transfer
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International Journal of Heat and Mass Transfer
1 publication, 8.33%
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High Temperature
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High Temperature
1 publication, 8.33%
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1
2
3
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Citations by publishers
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1
2
3
4
5
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Elsevier
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Elsevier
5 publications, 41.67%
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Pleiades Publishing
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Pleiades Publishing
2 publications, 16.67%
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American Institute of Physics (AIP)
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American Institute of Physics (AIP)
2 publications, 16.67%
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Multidisciplinary Digital Publishing Institute (MDPI)
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Multidisciplinary Digital Publishing Institute (MDPI)
1 publication, 8.33%
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IEEE
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IEEE
1 publication, 8.33%
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World Scientific
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World Scientific
1 publication, 8.33%
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1
2
3
4
5
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- We do not take into account publications that without a DOI.
- Statistics recalculated only for publications connected to researchers, organizations and labs registered on the platform.
- Statistics recalculated weekly.
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Orekhov N. D. et al. Atomistic structure and anomalous heat capacity of low-density liquid carbon: Molecular dynamics study with machine learning potential // Carbon. 2022. Vol. 192. pp. 179-186.
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Orekhov N. D., Logunov M. V. Atomistic structure and anomalous heat capacity of low-density liquid carbon: Molecular dynamics study with machine learning potential // Carbon. 2022. Vol. 192. pp. 179-186.
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TY - JOUR
DO - 10.1016/j.carbon.2022.02.058
UR - https://doi.org/10.1016%2Fj.carbon.2022.02.058
TI - Atomistic structure and anomalous heat capacity of low-density liquid carbon: Molecular dynamics study with machine learning potential
T2 - Carbon
AU - Orekhov, Nikita D.
AU - Logunov, Mikhail V.
PY - 2022
DA - 2022/06/01 00:00:00
PB - Elsevier
SP - 179-186
VL - 192
SN - 0008-6223
ER -
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@article{2022_Orekhov,
author = {Nikita D. Orekhov and Mikhail V. Logunov},
title = {Atomistic structure and anomalous heat capacity of low-density liquid carbon: Molecular dynamics study with machine learning potential},
journal = {Carbon},
year = {2022},
volume = {192},
publisher = {Elsevier},
month = {jun},
url = {https://doi.org/10.1016%2Fj.carbon.2022.02.058},
pages = {179--186},
doi = {10.1016/j.carbon.2022.02.058}
}