- The activity data generation step will update later...
- The slab generation code task is under the
Shell_repo/ocp/slab_generation/
See installation instructions.
- Install specific versions of ipykernel, pymongo and mpi-client:
pip install pymongo ipykernel mp-api - Install Catkit from Github:
pip install git+https://github.com/ulissigroup/CatKit.git catkit - Clone this repo and
cd ./Open-Catalyst-Dataset-OC22_dataset/ocdata/, install with:pip install -e ..
- This work is an extension work based on OCP dataset, machine learning model and most of the scripts.
ocp is the Open Catalyst Project's
library of state-of-the-art machine learning algorithms for catalysis.
It provides training and evaluation code for tasks and models that take arbitrary chemical structures as input to predict energies / forces / positions, and can be used as a base scaffold for research projects. For an overview of tasks, data, and metrics, please read our papers:
ocp is released under the MIT license.
If you use this codebase in your work, please consider citing:
@article{ocp_dataset,
author = {Chanussot*, Lowik and Das*, Abhishek and Goyal*, Siddharth and Lavril*, Thibaut and Shuaibi*, Muhammed and Riviere, Morgane and Tran, Kevin and Heras-Domingo, Javier and Ho, Caleb and Hu, Weihua and Palizhati, Aini and Sriram, Anuroop and Wood, Brandon and Yoon, Junwoong and Parikh, Devi and Zitnick, C. Lawrence and Ulissi, Zachary},
title = {Open Catalyst 2020 (OC20) Dataset and Community Challenges},
journal = {ACS Catalysis},
year = {2021},
doi = {10.1021/acscatal.0c04525},
}