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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https://hdl.handle.net/2134/19714957.v1

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