Exploring Phononic Properties of Two-Dimensional Materials using Machine Learning Interatomic Potentials
| Main Author: | Mortazavi, Bohayra |
|---|---|
| Other Authors: | Novikov, Ivan , Shapeev, Alexander |
| Format: | Dataset |
| Terbitan: |
Mendeley
, 2020
|
| Subjects: | |
| Online Access: |
https:/data.mendeley.com/datasets/7ppcf7cs27 |
| ctrlnum |
0.17632-7ppcf7cs27.1 |
|---|---|
| fullrecord |
<?xml version="1.0"?>
<dc><creator>Mortazavi, Bohayra</creator><title>Exploring Phononic Properties of Two-Dimensional Materials using Machine Learning Interatomic Potentials </title><publisher>Mendeley</publisher><description>In this manual we provide a guide on the practical implementation and reproduction of the results presented in our publication entitled: "Exploring Phononic Properties of Two-Dimensional Materials using Machine Learning Interatomic Potentials". We specifically discuss the repository https://gitlab.com/ivannovikov/mlip_phonopy with the MLIP_PHONOPY code—a C++ interface between the MLIP code and the PHONOPY software—which allows one to calculate phonon spectra, group velocities, thermal properties, etc., of a two-dimensional material. Along with the repository description, this manual contains an instruction on quick installation of the stable branch of the MLIP code, a description of VASP input files for ab initio molecular dynamics (AIMD) calculations (namely, the
folders Structures and VASP-inputs) and training set preparation, an instruction on passive training of MomentTensor Potentials (MTPs) using the MLIP code. Finaly, we describe the folders Untrained-MTPs and Exampleswith the additional files available here: http://dx.doi.org/10.17632/7ppcf7cs27.1.</description><subject>Physics</subject><subject>Machine Learning Algorithm</subject><subject>Molecular Dynamics</subject><subject>Phonon Density of State</subject><contributor>Novikov, Ivan </contributor><contributor>Shapeev, Alexander</contributor><type>Other:Dataset</type><identifier>10.17632/7ppcf7cs27.1</identifier><rights>Creative Commons Attribution 4.0 International</rights><rights>http://creativecommons.org/licenses/by/4.0</rights><relation>https:/data.mendeley.com/datasets/7ppcf7cs27</relation><date>2020-01-27T14:32:24Z</date><recordID>0.17632-7ppcf7cs27.1</recordID></dc>
|
| format |
Other:Dataset Other |
| author |
Mortazavi, Bohayra |
| author2 |
Novikov, Ivan Shapeev, Alexander |
| title |
Exploring Phononic Properties of Two-Dimensional Materials using Machine Learning Interatomic Potentials |
| publisher |
Mendeley |
| publishDate |
2020 |
| topic |
Physics Machine Learning Algorithm Molecular Dynamics Phonon Density of State |
| url |
https:/data.mendeley.com/datasets/7ppcf7cs27 |
| contents |
In this manual we provide a guide on the practical implementation and reproduction of the results presented in our publication entitled: "Exploring Phononic Properties of Two-Dimensional Materials using Machine Learning Interatomic Potentials". We specifically discuss the repository https://gitlab.com/ivannovikov/mlip_phonopy with the MLIP_PHONOPY code—a C++ interface between the MLIP code and the PHONOPY software—which allows one to calculate phonon spectra, group velocities, thermal properties, etc., of a two-dimensional material. Along with the repository description, this manual contains an instruction on quick installation of the stable branch of the MLIP code, a description of VASP input files for ab initio molecular dynamics (AIMD) calculations (namely, the
folders Structures and VASP-inputs) and training set preparation, an instruction on passive training of MomentTensor Potentials (MTPs) using the MLIP code. Finaly, we describe the folders Untrained-MTPs and Exampleswith the additional files available here: http://dx.doi.org/10.17632/7ppcf7cs27.1. |
| id |
IOS7969.0.17632-7ppcf7cs27.1 |
| institution |
Universitas Islam Indragiri |
| affiliation |
onesearch.perpusnas.go.id |
| institution_id |
804 |
| institution_type |
library:university library |
| library |
Teknologi Pangan UNISI |
| library_id |
2816 |
| collection |
Artikel mulono |
| repository_id |
7969 |
| city |
INDRAGIRI HILIR |
| province |
RIAU |
| shared_to_ipusnas_str |
1 |
| repoId |
IOS7969 |
| first_indexed |
2020-04-08T08:19:39Z |
| last_indexed |
2020-04-08T08:19:39Z |
| recordtype |
dc |
| _version_ |
1686587544929566720 |
| score |
17.538404 |