Commit ·
c80250b
1
Parent(s): 492b180
nit
Browse files
README.md
CHANGED
|
@@ -6,12 +6,12 @@ license: mit
|
|
| 6 |
|
| 7 |
SimPoly is a fast and scalable machine learning force field (MLFF) for ab initio prediction of polymer properties. This repository contains the trained model weights and benchmark datasets from our paper. Refer to the accompanying GitHub repository for instructions and usage examples.
|
| 8 |
|
| 9 |
-
**Key Features
|
| 10 |
- Accurately predicts polymer densities and glass transition temperatures without experimental fitting
|
| 11 |
- Outperforms classical force fields for a broad range of polymers
|
| 12 |
- Includes benchmark data: experimental bulk properties for 130 polymers and quantum-chemical training datasets
|
| 13 |
|
| 14 |
-
**Resources
|
| 15 |
- [GitHub Code](https://github.com/microsoft/simpoly)
|
| 16 |
- [Paper on arXiv](https://arxiv.org/abs/2510.13696)
|
| 17 |
|
|
|
|
| 6 |
|
| 7 |
SimPoly is a fast and scalable machine learning force field (MLFF) for ab initio prediction of polymer properties. This repository contains the trained model weights and benchmark datasets from our paper. Refer to the accompanying GitHub repository for instructions and usage examples.
|
| 8 |
|
| 9 |
+
**Key Features**
|
| 10 |
- Accurately predicts polymer densities and glass transition temperatures without experimental fitting
|
| 11 |
- Outperforms classical force fields for a broad range of polymers
|
| 12 |
- Includes benchmark data: experimental bulk properties for 130 polymers and quantum-chemical training datasets
|
| 13 |
|
| 14 |
+
**Resources**
|
| 15 |
- [GitHub Code](https://github.com/microsoft/simpoly)
|
| 16 |
- [Paper on arXiv](https://arxiv.org/abs/2510.13696)
|
| 17 |
|