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MIT.nano has announced that 16 startups became active participants in its START.nano program in 2025, more than doubling the number of new companies from the previous year. Aimed at speeding the transition of hard-tech innovation to market, START.nano supports new ventures through the discounted use of MIT.nano shared facilities and a guided access to the […]
In biology, defects are generally bad. But in materials science, defects can be intentionally tuned to give materials useful new properties. Today, atomic-scale defects are carefully introduced during the manufacturing process of products like steel, semiconductors, and solar cells to help improve strength, control electrical conductivity, optimize performance, and more.But even as defects have become
MIT researchers use AI to uncover atomic defects in materials Read More »
Proteins are far more than nutrients we track on a food label. Present in every cell of our bodies, they work like nature’s molecular machines. They walk, stretch, bend, and flex to do their jobs, pumping blood, fighting disease, building tissue, and many other jobs too small for the eye to see. Their power doesn’t
MIT engineers design proteins by their motion, not just their shape Read More »
Curiosity-driven research has long sparked technological transformations. A century ago, curiosity about atoms led to quantum mechanics, and eventually the transistor at the heart of modern computing. Conversely, the steam engine was a practical breakthrough, but it took fundamental research in thermodynamics to fully harness its power. Today, artificial intelligence and science find themselves at a
3 Questions: On the future of AI and the mathematical and physical sciences Read More »
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
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
How generative AI can help scientists synthesize complex materials Read More »
MIT researchers have developed a new fabrication method that could enable the production of more energy efficient electronics by stacking multiple functional components on top of one existing circuit.In traditional circuits, logic devices that perform computation, like transistors, and memory devices that store data are built as separate components, forcing data to travel back and
New materials could boost the energy efficiency of microelectronics Read More »
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
Printable aluminum alloy sets strength records, may enable lighter aircraft parts Read More »
Manufacturing better batteries, faster electronics, and more effective pharmaceuticals depends on the discovery of new materials and the verification of their quality. Artificial intelligence is helping with the former, with tools that comb through catalogs of materials to quickly tag promising candidates.But once a material is made, verifying its quality still involves scanning it with
Checking the quality of materials just got easier with a new AI tool Read More »
The artificial intelligence models that turn text into images are also useful for generating new materials. Over the last few years, generative materials models from companies like Google, Microsoft, and Meta have drawn on their training data to help researchers design tens of millions of new materials.But when it comes to designing materials with exotic
New tool makes generative AI models more likely to create breakthrough materials Read More »
