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# gRASPA-DeepPotential version
This is an implementation of ML potential in gRASPA. Depending on ML models, it requires TensorFlow C++ API, CppFlow package, and LibTorch.
# gRASPA
gRASPA (pronounced “gee raspa”) is a GPU-accelerated Monte Carlo simulation software built for molecular adsorption in nanoporous materials, such as zeolites and metal-organic frameworks (MOFs).

# Documentation is available at
* [https://zhaoli2042.github.io/gRASPA-mkdoc](https://zhaoli2042.github.io/gRASPA-mkdoc)
## Authors
* Zhao Li (Northwestern University, Purdue University)
* Kaihang Shi (Northwestern University, University at Buffalo)
* David Dubbeldam (University of Amsterdam)
* Mark Dewing (Argonne National Laboratory)
* Christopher Knight (Argonne National Laboratory)
* Alvaro Vazquez Mayagoitia (Argonne National Laboratory)
* Randall Q. Snurr (Northwestern University)

# NOTES:
* To install gRASPA on various clusters, check out [Cluster-Setup](Cluster-Setup/)
# Reference:
* gRASPA paper is currently in progress. Please kindly cite it when it is published.
## Installation
### Installation in clusters
To install gRASPA on NERSC (DOE) and QUEST (Northwestern) clusters, check out [Cluster-Setup](Cluster-Setup/)

# TABLE of Code Capabilities
### Compatible GPUs
* For NVIDIA GPUs, gRASPA is currently compatible with NVHPC 22.5 & 22.7. gRASPA code has been tested on the following NVIDIA GPUs: A40, A100, RTX 3080 Ti, RTX 3090, RTX 4090.

## gRASPA Online Manual
gRASPA online manual is available [here](https://zhaoli2042.github.io/gRASPA-mkdoc)

## Reference
gRASPA paper is currently in progress. Please kindly cite it when it is published.

## Table of Code Capabilities
| Functionalities | gRASPA | gRASPA-fast | gRASPA-HTC |
| :---------------: | :---------------------: | :-----------------------: | :-----------------------: |
| ***Simulation Types*** |||
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| Peng-Robinson Equation of State | :heavy_check_mark: |
| Automatic Determination<br>of # unit cells | | | :heavy_check_mark: |


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