This study reports on an AI-powered autonomous experimentation platform that overcomes data scarcity in electronic materials discovery by using an AI advisor for real-time progress monitoring, data analysis and interactive human–AI collaboration. Applied to mixed ion–electron conducting polymers, it rapidly optimized performance in 64 experimental trials, revealing morphology–property relationships and an unreported polymer polymorph.
- Yahao Dai
- Henry Chan
- Jie Xu