Let the Laboratory Do Its Own Work

Self-driving laboratories can use robotics and AI to automate some routine parts of experiments. What impact could that have?

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To accelerate progress in labs all over the world, quantum mechanic Alán Aspuru-Guzik wants researchers to embrace laboratories that can make smart decisions all on their own. He calls them self-driving laboratories, and they combine chemistry with robotics and artificial intelligence to automate experiments, all the way down to automating decisions on what conditions to try next.

Aspuru-Guzik is the principal investigator of the Matter Lab at the University of Toronto and is cross appointed to both the Department of Chemistry and the Department of Computer Science. His multidisciplinary approach is one he hopes will spread.

“All of us scientists, we don’t take advantage of automation as much as we could,” says Aspuru-Guzik.

“So in my lab, we have been thinking a lot about how robotics and artificial intelligence can combine with chemistry to create something that we like to call self-driving laboratories: basically, a laboratory where, as much as possible, the mundane decisions of what the experiment to be done next, the next conditions to try, are actually optimized using artificial intelligence.”

Automating labs saves reagents, time, and other resources. Manually running experiments and stopping to analyze the data slows down progress, so automation fundamentally change the way we approach science.

He is starting with energy technology. From solar cells to batteries, every sustainable energy technology involves thin films of materials. So he built a machine to manufacture and test thin films made under different conditions to maximize their performance.

“Within five years, I would like my lab and my collaborators around the world to be able to demonstrate that these self-driving laboratories not only are successful, but they actually have positive change in the energy ecosystem,” adds Aspuru-Guzik.

He envisions that a laboratory in Taiwan might take his technology and find a better way to filter water, or that a scientists in Mexico might find a better molecule for energy regeneration. Worldwide reach would have limitless possibilities for rapid discovery.

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Alán Aspuru-Guzik’s research lies at the interface of computer science with chemistry and physics. He works in the integration of robotics, machine learning and high-throughput quantum chemistry for the development of materials acceleration platforms.

These “self-driving laboratories” promise to accelerate the rate of scientific discovery, with applications to clean energy and optoelectronic materials. Aspuru-Guzik also develops quantum computer algorithms for quantum machine learning and has pioneered quantum algorithms for the simulation of matter.

He is jointly appointed as a Professor of Chemistry and Computer Science at the University of Toronto. He is a faculty member of the Vector Institute for Artificial Intelligence. Previously, he was a full professor at Harvard University where he started his career in 2006.

Aspuru-Guzik is currently the Canada 150 Research Chair in Quantum Chemistry as well as a CIFAR AI Chair at the Vector Institute. Amongst other awards, he is a recipient of the Google Focused Award in Quantum Computing, the MIT Technology Review 35 under 35, and the Sloan and Camille and Henry Dreyfus Fellowships. He is also a fellow of the American Association of the Advancement of Science and the American Physical Society. He is a co-founder of Zapata Computing and Kebotix, two early-stage ventures in quantum computing and self-driving laboratories respectively.

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