When Alán Aspuru-Guzik, a Mexico City–born, Toronto-based chemist, looks at climate-change models, his eyes gravitate to the error bars, which show the range of uncertainty surrounding any given prediction. “As scientists,” he says, “we have a duty to contemplate worst-case scenarios.” If climate change proceeds as expected, humanity might have a couple of decades or so to come up with materials that don’t yet exist: molecules that enable us to quickly and cheaply capture carbon, and batteries—made of something other than lithium, a metal that is costly and difficult to mine—to store the global supply of renewable energy.
And what if the situation gets worse than we expected it to? The need for new materials will go from urgent to extremely urgent to dire. Could we quickly come up with the things we need?
Aspuru-Guzik (one of
MIT Technology Review’s 35 Innovators Under 35 in 2010) has devoted much of his life to versions of this question. Materials discovery—the science of creating and developing useful new substances—often moves at a frustratingly slow pace. The typical trial-and-error approach, whereby scientists produce new molecules and then test each one sequentially for the desired properties, takes an average of two decades, making it too expensive and risky for most companies to pursue.
Aspuru-Guzik’s objective—which he shares with a growing number of computer-savvy chemists—is to shrink that interval to a matter of months or years, enabling humanity to quickly amass an arsenal of resources for fighting climate change, like batteries and carbon-capture filters. The goal is to revive the moribund materials industry by incorporating digital simulations, robotics, data science, artificial intelligence, and even quantum computing into the discovery process.
Imagine computer programs that use precise knowledge of molecules’ electronic structure to create new designs; imagine robots that make and test these molecules. And imagine the software and robots working together—testing molecules, tweaking designs, and testing again—until they produce a material with the properties we’re looking for.
That’s the idea, at least. Actually executing it is another matter. The structures of molecules are mind-bogglingly complex, and chemical synthesis is often more art than science, defying efforts to automate the process. But advances in AI, robotics, and computing are
bringing new life to the vision.
Aspuru-Guzik cochaired a 2017 workshop in Mexico City where 133 participants—including Nobel Prize–winning scientists and representatives from 17 national governments—came together to focus the global research community on this goal. The conference was a pivotal moment, helping take the field of accelerated materials discovery from a niche area of inquiry to a worldwide priority for many of those attendees. After the event, Canada, India, and the EU, among others, began investing in initiatives to speed up material research.
The work itself is ambitious and technically difficult because it spans so many disciplines. But as a chemist, software engineer, AI pioneer, quantum computer programmer, robotics enthusiast, and serial entrepreneur, Aspuru-Guzik just may have the right mix of computational expertise and imagination to connect the multiple tools essential to making it happen. He has emerged as one of the more convincing evangelists for the new way of doing chemistry.
“Alán can see beyond what people think is possible,” says
Joshua Schrier, a Fordham University chemist and frequent collaborator. He is the kind of innovator, says Schrier, who changes the way everybody around him practices science.
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https://www.technologyreview.com/2021/10/27/1037114/materials-discovery-ai-chemistry-computing
