It is challenging to design machine learning potentials for heterogeneous catalysis that are universal, reactive and have high accuracy. Now, an element-based machine learning potential relying on a random exploration via an imaginary chemicals optimization sampling strategy is put forward, and is successfully demonstrated for a range of applications.
- Changxi Yang
- Chenyu Wu
- P. Hu
