├── .gitattributes
├── .gitignore
├── COF
├── DAAQ_TFP_COF
│ ├── AA_stacking
│ │ ├── ML_AB
│ │ └── ML_FF
│ └── AB_stacking
│ │ ├── ML_AB
│ │ └── ML_FF
├── README.md
└── Tp_Azo_COF
│ ├── AA_stacking
│ ├── ML_AB
│ └── ML_FF
│ └── AB_stacking
│ ├── ML_AB
│ └── ML_FF
├── LICENSE
├── Li3N
├── ML_ABN
├── ML_FF
└── README.md
└── README.md
/.gitattributes:
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2 | ML_FF filter=lfs diff=lfs merge=lfs -text
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4 |
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1 | # [Covalent Organic Frameworks](COF)
2 |
3 | _Details:_ Gaussian Approximation Potential (GAP)-style MLFF trained using on-the-fly sampling of reference configurations in [VASP](https://www.vasp.at/wiki/index.php/Category:Machine-learned_force_fields).
4 |
5 | _Publication:_ [Room-temperature stacking disorder in layered covalent-organic frameworks from machine-learning force fields (Materials Horizons,2023)](https://pubs.rsc.org/en/content/articlelanding/2023/MH/D3MH00314K)
6 |
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/LICENSE:
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1 | MIT License
2 |
3 | Copyright (c) 2023 Materials Design Group
4 |
5 | Permission is hereby granted, free of charge, to any person obtaining a copy
6 | of this software and associated documentation files (the "Software"), to deal
7 | in the Software without restriction, including without limitation the rights
8 | to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
9 | copies of the Software, and to permit persons to whom the Software is
10 | furnished to do so, subject to the following conditions:
11 |
12 | The above copyright notice and this permission notice shall be included in all
13 | copies or substantial portions of the Software.
14 |
15 | THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
16 | IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
17 | FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
18 | AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
19 | LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
20 | OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
21 | SOFTWARE.
22 |
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/Li3N/README.md:
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1 | # [Li3N](Li3N)
2 |
3 | _Details:_ Gaussian Approximation Potential (GAP)-style MLFF trained using on-the-fly sampling of reference configurations in [VASP 6.3.0](https://www.vasp.at/wiki/index.php/Category:Machine-learned_force_fields) on the [Michael](https://www.rc.ucl.ac.uk/docs/Clusters/Michael/) computing cluster.
4 |
5 | _Publication:_ [Nature of the Superionic Phase Transition of Lithium Nitride from Machine Learning Force Fields (Chemistry of Materials,2023)](https://pubs.acs.org/doi/10.1021/acs.chemmater.3c01271)
6 |
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/README.md:
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1 | # MLFF
2 |
3 | A collection of files related to machine learning force fields (MLFF) within our research group. Training data, scripts, and forcefields are included where appropriate.
4 |
5 | ## Utilities
6 |
7 | * ML_AB file manipulation: https://github.com/utf/pymlff
8 | * Diffusion coefficient calculations: https://github.com/bjmorgan/kinisi
9 | * Perovskite structure analysis: https://github.com/WMD-group/PDynA
10 |
11 | ## [Li3N](Li3N)
12 |
13 | _Details:_ Gaussian Approximation Potential (GAP)-style MLFF trained using on-the-fly sampling of reference configurations in [VASP](https://www.vasp.at/wiki/index.php/Category:Machine-learned_force_fields).
14 |
15 | _Publication:_ [Nature of the Superionic Phase Transition of Lithium Nitride from Machine Learning Force Fields (Chemistry of Materials, 2023)](https://pubs.acs.org/doi/10.1021/acs.chemmater.3c01271)
16 |
17 | ## [Covalent Organic Frameworks](COF)
18 |
19 | _Details:_ Gaussian Approximation Potential (GAP)-style MLFF trained using on-the-fly sampling of reference configurations in [VASP](https://www.vasp.at/wiki/index.php/Category:Machine-learned_force_fields).
20 |
21 | _Publication:_ [Room-temperature stacking disorder in layered covalent-organic frameworks from machine-learning force fields (Materials Horizons, 2023)](https://pubs.rsc.org/en/content/articlelanding/2023/MH/D3MH00314K)
22 |
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