Skip to content

Chemical reactions are one approach to convert intermittently available renewable energy, such as solar or wind, to other fuels, like hydrogen. Learn how ML can discover low-cost catalysts to drive these reactions at high rates.

License

Notifications You must be signed in to change notification settings

climatechange-ai-tutorials/open-catalyst-project

Repository files navigation

Open Catalyst Project: An Introduction to Machine Learning for Material Discovery

Chemical reactions are one approach to convert intermittently available renewable energy, such as solar or wind, to other fuels, like hydrogen. Learn how ML can discover low-cost catalysts to drive these reactions at high rates.

Author(s):

Originally presented at NeurIPS 2021

Access this tutorial

We recommend executing this notebook in a Colab environment to gain access to GPUs and to manage all necessary dependencies. Open In Colab

Estimated time to execute end-to-end: 30 minutes

Contribute to this tutorial

Please refer to these GitHub instructions to open a pull request via the "fork and pull request" workflow.

Pull requests will be reviewed by members of the Climate Change AI Tutorials team for relevance, accuracy, and conciseness.

Climate Change AI Tutorials

Check out the tutorials page on our website for a full list of tutorials demonstrating how AI can be used to tackle problems related to climate change.

License

Usage of this tutorial is subject to the MIT License.

Cite

Plain Text

Kolluru, A., Shuaibi, M., Das, A., Wood, B., Lan, J., Sriram, A., Ulissi, Z., & Zitnick, L. (2021). Open Catalyst Project: An Introduction to Machine Learning for Material Discovery [Tutorial]. In Conference on Neural Information Processing Systems. Climate Change AI. https://doi.org/10.5281/zenodo.11622236

BibTeX

@misc{kolluru2021open,
  title={Open Catalyst Project: An Introduction to Machine Learning for Material Discovery},
  author={Kolluru, Adeesh and Shuaibi, Muhammed and Das, Abhishek and Wood, Brandon and Lan, Janice and Sriram, Anuroop and Ulissi, Zachary and Zitnick, Larry},
  year={2021},
  organization={Climate Change AI},
  type={Tutorial},
  doi={https://doi.org/10.5281/zenodo.11622236},
  booktitle={Conference on Neural Information Processing Systems},
  howpublished={\url{https://github.com/climatechange-ai-tutorials/open-catalyst-project}}
}

About

Chemical reactions are one approach to convert intermittently available renewable energy, such as solar or wind, to other fuels, like hydrogen. Learn how ML can discover low-cost catalysts to drive these reactions at high rates.

Resources

License

Stars

Watchers

Forks

Packages

No packages published