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Accelerating science with AI and simulations

For more than a decade, MIT Associate Professor Rafael Gómez-Bombarelli has used artificial intelligence to create new materials. As the technology has expanded, so have his ambitions.Now, the newly tenured professor in materials science and engineering believes AI is poised to transform science in ways never before possible. His work at MIT and beyond is […]

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How generative AI can help scientists synthesize complex materials

Generative artificial intelligence models have been used to create enormous libraries of theoretical materials that could help solve all kinds of problems. Now, scientists just have to figure out how to make them.In many cases, materials synthesis is not as simple as following a recipe in the kitchen. Factors like the temperature and length of

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The brain power behind sustainable AI

How can you use science to build a better gingerbread house?That was something Miranda Schwacke spent a lot of time thinking about. The MIT graduate student in the Department of Materials Science and Engineering (DMSE) is part of Kitchen Matters, a group of grad students who use food and kitchen tools to explain scientific concepts through short videos

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MIT Energy Initiative conference spotlights research priorities amidst a changing energy landscape

“We’re here to talk about really substantive changes, and we want you to be a participant in that,” said Desirée Plata, the School of Engineering Distinguished Professor of Climate and Energy in MIT’s Department of Civil and Environmental Engineering, at Energizing@MIT: the MIT Energy Initiative’s (MITEI) Annual Research Conference that was held on Sept. 9-10.Plata’s

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Printable aluminum alloy sets strength records, may enable lighter aircraft parts

MIT engineers have developed a printable aluminum alloy that can withstand high temperatures and is five times stronger than traditionally manufactured aluminum.The new printable metal is made from a mix of aluminum and other elements that the team identified using a combination of simulations and machine learning, which significantly pruned the number of possible combinations

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DOE selects MIT to establish a Center for the Exascale Simulation of Coupled High-Enthalpy Fluid–Solid Interactions

The U.S. Department of Energy’s National Nuclear Security Administration (DOE/NNSA) recently announced that it has selected MIT to establish a new research center dedicated to advancing the predictive simulation of extreme environments, such as those encountered in hypersonic flight and atmospheric re-entry. The center will be part of the fourth phase of NNSA’s Predictive Science Academic Alliance

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AI system learns from many types of scientific information and runs experiments to discover new materials

Machine-learning models can speed up the discovery of new materials by making predictions and suggesting experiments. But most models today only consider a few specific types of data or variables. Compare that with human scientists, who work in a collaborative environment and consider experimental results, the broader scientific literature, imaging and structural analysis, personal experience

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