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Emerald01 authored Aug 2, 2024
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# rlchemists

This is the source code folder for the research project published on Nature Communications ...
This is the source code folder for the research project published on Nature Communications: https://www.nature.com/articles/s41467-024-50531-6/figures/3

## structure
1. `en_array`: energy landscape mesh from DFT
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## installation
1. setup GPU environment and install `warpdrive` package as instructed
2. under the root directory of `rlchemists`, run `bash setenv.sh` to setup the Python path for this project

## CUDA kernel for environment
Please contact the authors for the kernel functions as this is not OSS.

## run
We simply choose the environment and type to run a particular training, the supported ones are all included
in the `run_configs` folders, for example, `run_configs/single_agent_one_atom_diffusion2d` can be run by
`python example_training_script_numba.py --env single_agent_one_atom --type diffusion2d`

## cite
If you're using this study in your research or applications, please cite using this BibTeX:
```
@article{lan2024,
title = {Enabling high throughput deep reinforcement learning with first principles to investigate catalytic reaction mechanisms.},
author = {Lan, Tian and Wang, Huan and An, Qi},
year = 2024,
journal = {Nature Communications},
volume = {15},
number = {6281},
}
```

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