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A hybrid neural network model driver for multilayer two-dimensional materials developed by Wen and Tadmor (2019) v001
Description A hybrid neural network (NN) and Lennard-Jones (LJ) model driver for multilayer two-dimensional materials. The NN term models short-range intralayer and orbital overlap interactions and the theoretically-motivated LJ term models long-range dispersion.
A statement of applicability provided by the contributor, informing users of the intended use of this KIM Item.
Contributor Mingjian Wen
Maintainer Mingjian Wen
Published on KIM 2019
How to Cite

This Model Driver originally published in [1] is archived in OpenKIM [2-4].

[1] Wen M, Tadmor EB. Hybrid neural network potential for multilayer graphene. Physical Review B. 2019;100(19):195419. doi:10.1103/PhysRevB.100.195419

[2] A hybrid neural network model driver for multilayer two-dimensional materials developed by Wen and Tadmor (2019) v001. OpenKIM; 2019. doi:10.25950/9fa4935a

[3] Tadmor EB, Elliott RS, Sethna JP, Miller RE, Becker CA. The potential of atomistic simulations and the Knowledgebase of Interatomic Models. JOM. 2011;63(7):17. doi:10.1007/s11837-011-0102-6

[4] Elliott RS, Tadmor EB. Knowledgebase of Interatomic Models (KIM) Application Programming Interface (API). OpenKIM; 2011. doi:10.25950/ff8f563a

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Funding Not available
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Extended KIM ID
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DOI 10.25950/9fa4935a
KIM Item TypeModel Driver
KIM API Version2.0
Programming Language(s)
The programming languages used in the code and the percentage of the code written in each one.
97.72% C++
2.28% Shell
Previous Version hNN__MD_435082866799_000

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