Structure and pore size distribution in nanoporous carbon

We study the structural and mechanical properties of nanoporous (NP) carbon materials by extensive atomistic machine-learning (ML) driven molecular dynamics (MD) simulations. To this end, we retrain a ML Gaussian approximation potential (GAP) for carbon by recalculating the a-C structural database o...

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Bibliographic Details

Main Authors:	Yanzhou Wang, Zheyong Fan, Ping Qian, Tapio Ala-Nissila, Miguel A Caro
Format:	Default Article
Published:	2022
Subjects:	Science & Technology Physical Sciences Technology Chemistry, Physical Materials Science, Multidisciplinary Chemistry Materials Science FUNCTIONALIZATION APPROXIMATION POTENTIALS ALGORITHMS Materials Chemical Sciences Engineering
Online Access:	https://hdl.handle.net/2134/19714957.v1
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