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source/_data/pub.bib

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@@ -576,3 +576,28 @@ @Article{Galib_Science_2021_v371_p921
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experimental observations.},
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doi = {10.1126/science.abd7716},
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}
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@Article{Miyagawa_ComputationalMaterialsScience_2022_v206_p111303,
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author = {Takeru Miyagawa and Kazuki Mori and Nobuhiko Kato and Akio Yonezu},
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title = {{Development of neural network potential for MD simulation and its
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application to TiN}},
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journal = {Computational Materials Science},
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year = 2022,
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volume = 206,
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pages = 111303,
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doi = {10.1016/j.commatsci.2022.111303},
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}
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@Article{Cao_PhysChemChemPhys_2022,
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author = {Liqun Cao and Jinzhe Zeng and Bo Wang and Tong Zhu and John Z.H. Zhang},
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title = {{Ab Initio Neural Network MD Simulation of Thermal Decomposition of
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High Energy Material CL-20/TNT}},
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journal = {Phys. Chem. Chem. Phys.},
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year = 2022,
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annote = {<jats:p>CL-20
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(2,4,6,8,10,12-hexanitro-2,4,6,8,10,12-hexaazaisowurtzitane, also
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known as HNIW) is one of the most powerful energetic materials.
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However, its high sensitivity to environmental stimuli greatly reduces
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its safety and severely limits its application....</jats:p>},
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doi = {10.1039/D2CP00710J},
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}

source/papers/deepmd-kit/index.md

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@@ -12,7 +12,9 @@ The following publications have used the DeePMD-kit software. Publications that
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Ding_MaterialsScienceinSemiconductorProcessing_2022_v143_p106513,
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Jiao_AdvSci_2022_v9_pe2105574,
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Wang_Carbon_2022_v186_p1,
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Yang_CatalysisToday_2022_v387_p143
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Yang_CatalysisToday_2022_v387_p143,
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Miyagawa_ComputationalMaterialsScience_2022_v206_p111303,
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Cao_PhysChemChemPhys_2022
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{% endpublications %}
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## 2021

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