Autonomous Synthesis of Materials (ASyMo)

Self-driving laboratories represent a revolutionary approach in scientific research, leveraging the power of automation and artificial intelligence (AI) to accelerate the discovery and development processes across various scientific fields. These laboratories are equipped with robotic systems and AI algorithms that can autonomously perform experiments, analyze data, and even adjust hypotheses based on experimental outcomes. This not only speeds up the research cycle but also enables the exploration of a vast experimental space that would be impractical for human scientists to cover due to time and resource constraints.

The core idea behind self-driving laboratories is to integrate advanced technologies such as machine learning, robotics, and data analytics to create an automated environment where experiments can be designed, conducted, and iterated upon without human intervention. This approach allows for more efficient use of resources, reduces the likelihood of human error, and significantly accelerates the pace of innovation. Self-driving laboratories herald a new era of scientific research where the synergy between humans and machines can lead to breakthroughs at an unprecedented pace, offering vast potential to address some of the most pressing challenges of our time.

This project in the Jayan Lab for Energy Research in CMU Mechanical Engineering seeks a fearless Engineering student who loves to tinker with hardware and some software (interface with Generative models like ChatGPT). They will help us continue to build on our self-driving lab robot prototype (ASyMo) and optimize ASyMo for making materials for Energy applications like batteries. Eventually, we want ASyMo to run 24/7, as they explore new materials with desired properties for use in batteries.

Previous lab experience would be nice, but not necessary.