Autonomous materials design laboratory

The development of autonomous laboratories represents a paradigm shift in materials research by automating the entire experimental process—from planning and execution to analysis and iteration. In this talk I will discsus three approaches to laboratory autonomy and how they can be implemented to accelerate scientific discovery. The first approach is developing an all-in-one automated platform, where the "brain" (AI agent) directs the workflow, and the "eyes" (computer vision feedback) inform decision-making algorithms in real-time. The second method focuses on modular integration, allowing flexibility through the addition of robotic arms and components. This approach replaces high-fidelity characterization with lower-fidelity proxies with human in the loop. Lastly, open-source hardware is discussed as a means of democratizing science with customized automation setups. Labs can be tailored to specific research needs at a lower cost, making advanced automation accessible to more scientists. Through these three approaches, I will discuss how to build a fully functional self-driving lab from the ground up, revolutionizing how experiments are conducted and accelerating materials design across length scales.