Human-AI-Machine Collaboration to Accelerate Materials Research with Autonomous Labs

Despite significant advancements in artificial intelligence (AI) over the past decade, its trustworthy implementation for materials research remains challenging. In this talk, I will present our recent work on trustworthy AI for materials research by bridging the gap between the digital and physical worlds with autonomous labs. I will discuss the importance of <i>optimal</i> human-AI-machine (robot) collaboration to truly accelerate (and not <i>decelerate</i>) research in materials science. I will discuss the ideal traits of autonomous labs where novel materials are proposed by human-AI teams and synthesized and refined by robots within a few weeks (or days). I will present how closed-loop integration of <i>AI co-pilots</i> with lab automation (robotic material synthesis) can enable human scientists to rapidly navigate the design-make-test-analyze cycle of materials research and accelerate the timeframe for discovering new advanced functional materials by 100x–1000x as compared to the <i>status quo.</i>