Last week, nearly 130 researchers convened on the 17th floor of the Duan Family Center for Computing & Data Sciences at Boston University for the tenth annual Materials Day. The event, titled “From Automation to Collaboration: The Future of Self-Driving Labs,” emphasized the role of automation in materials discovery.
Sponsored by the Materials Science & Engineering division of Boston University”s College of Engineering and the Rafik B. Hariri Institute for Computing and Computational Science & Engineering, the workshop featured presentations from nine faculty members from various institutions, complemented by brief talks from graduate students.
In her opening remarks, Elise Morgan, Dean of the College of Engineering, highlighted the integration of diverse approaches in materials research. She stated, “We think that convergent approach really helps address the complex challenges that aren”t solvable by single-discipline thinking alone.” Morgan noted the transformative potential of self-driving labs to democratize materials research and enhance its societal impact.
A self-driving lab (SDL) utilizes robotic systems to conduct numerous experiments with the guidance of human scientists. One notable example is the lab led by Keith Brown, who organized Materials Day. Brown”s lab employs a system known as the Bayesian experimental autonomous researcher (BEAR), which combines additive manufacturing, robotics, and machine learning to optimize material discovery processes.
Brown explained that his lab successfully identified an innovative material for energy absorption through extensive experimentation. He remarked on the need for both thoughtful methodology and automation, stating, “The term “Edisonian” has in some ways come to mean a brute-force approach that doesn”t leave room for thought.” He emphasized the importance of leveraging automation to conduct more intelligent experiments.
Douglas Densmore, a professor at the university, underscored the primary advantage of automated labs as their ability to replicate experiments consistently. He explained, “Higher throughput is great, lower cost is great, but it”s really reproducibility.” Densmore”s lab has proven its efficiency by processing thousands of COVID-19 tests daily, highlighting its capability to support synthetic biology research.
During the event, Joerg Werner, an assistant professor, discussed the compatibility of his polymer research with SDLs. He noted the importance of processing parameters in determining the properties of polymers, making it an ideal candidate for automation.
Various speakers from esteemed institutions like MIT and Cornell addressed topics such as Bayesian optimization and the challenges posed by atomic systems to machine learning. Additionally, student lightning talks provided a platform for sharing recent research and fostering collaboration.
The event also featured a community ideation exercise where attendees engaged in discussions about open questions and challenges in their fields. This interactive component encouraged networking and potential future partnerships.
Overall, Materials Day showcased the promising landscape of self-driving labs and their role in revolutionizing materials research, reinforcing the value of community and collaboration in scientific advancement.
