An artificial intelligence-driven robotic chemist that integrates generative machine-learning models incorporating spectroscopic descriptors with automated experimentation is developed, enabling the inverse design of high-entropy catalysts and offering a generalizable strategy for the design of diverse complex materials.
- Donglai Zhou
- Ruyu Yang
- Jun Jiang
