Big News: Our Research Published in Science Advances! 📣
I’m incredibly excited to announce that our latest work on multistage machine learning for catalyst discovery has been published in Science Advances! 🥂
What’s the breakthrough? ⚡
In this paper, we introduced a multistage machine learning framework that integrates three powerful techniques:
- Data mining 🔍
- Active learning 🔄
- Domain adaptation 🔀
This integrated approach helps us streamline the discovery of multimetallic catalysts - materials that are essential for clean energy technologies.
How does it work? 🤔
Our framework leverages different data modalities through specialized ML modules. This allows us to objectively navigate an enormous candidate space of possible catalyst combinations.
The result? We identified a promising catalyst with excellent performance in wet-lab testing and real commercial potential! 💰
The whole paper is intuitive but relatively extensive in labor. So recommended to read the full text.
Read the full paper 📝
Check out our paper: Leveraging Data Mining, Active Learning, and Domain Adaptation in a Multi-Stage, Machine Learning-Driven Approach for the Efficient Discovery of Advanced Acidic Oxygen Evolution Electrocatalysts
Preprint available on arXiv: arXiv:2407.04877
Huge thanks to my amazing collaborators especially my advisors Yuxin Chen, and Junhong Chen! 🙏