| Title
A single sentence description.
|
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. |
| Disclaimer
A statement of applicability provided by the contributor, informing users of the intended use of this KIM Item.
|
None |
| Contributor |
Mingjian Wen |
| Maintainer |
Mingjian Wen |
| Developer |
Mingjian Wen Ellad B. Tadmor |
| 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] Wen M, Tadmor EB. 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 Click here to download the above citation in BibTeX format. |
| Funding | Not available |
| Short KIM ID
The unique KIM identifier code.
| MD_435082866799_001 |
| Extended KIM ID
The long form of the KIM ID including a human readable prefix (100 characters max), two underscores, and the Short KIM ID. Extended KIM IDs can only contain alpha-numeric characters (letters and digits) and underscores and must begin with a letter.
| hNN__MD_435082866799_001 |
| DOI |
10.25950/9fa4935a https://doi.org/10.25950/9fa4935a https://commons.datacite.org/doi.org/10.25950/9fa4935a |
| KIM Item Type | Model Driver |
| KIM API Version | 2.0 |
| 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 |
| hNN_WenTadmor_2019Grx_C__MO_421038499185_001 |
| hNN__MD_435082866799_001.txz | Tar+XZ | Linux and OS X archive |
| hNN__MD_435082866799_001.zip | Zip | Windows archive |
The Tunable Intrinsic Ductility Potential (TIDP) of Rajan, Warner and Curtin is based on standard Morse potential. The ductility is tuned by altering the tail of \(\varphi(r)\) while leaving the energy well unchanged. The functional form is
\[\varphi(r)= \begin{cases} (1-\exp[-\alpha(r-1)])^2-1 & r \le r_1 \\ A_1 r^3 + B_1 r^2 + C_1 r + D_1 & r_1 < r \le r_2 \\ A_2 r^3 + B_2 r^2 + C_2 r + D_2 & r_2 < r \le r_3 \\ 0 & r_3 < r \end{cases}\]The TIDP model has 12 parameters:
\[\alpha, \quad r_1, \quad r_2, \quad r_3, \quad A_1, \quad B_1, \quad C_1, \quad D_1, \quad A_2, \quad B_2, \quad C_2, \quad D_2.\]