Materials science in the era of AI: recent trends in autonomous experimental systems and the changing role of scientists
Abstract
Abstract Self-driving laboratories (SDLs) bring a paradigm shift to materials science by accelerating material development through autonomous exploration. This review explores recent SDL advances, including the evolution of search algorithms, hardware improvements, and expanded autonomy via large language model-based artificial intelligence (AI) agents. Research process transformations are discussed based on a data-acquisition “small loop” and a hypothesis-generation “large loop.” As AI increasingly controls experimentation and optimization (the “small loop”), researchers need to collaborate with AI, focusing on generating overarching hypotheses and strategies (the “large loop”). Finally, from the perspective of the patent system, we argue that the conception of and responsibility for inventions ultimately remain with researchers.
Fields of Study & Subjects
Machine Learning in Materials Science
Artificial Intelligence in Healthcare and Education
Electronic and Structural Properties of Oxides
Publication details
- Journal / source
- Applied Physics Express
- Publisher
- IOP Publishing
- Volume
- 19
- Issue
- 7
- Pages
- 070102–070102
- Publication date
- 21 May 2026
- Language
- EN