Artificial intelligence (AI) may have more to offer science than accurate predictions. The patterns it learns could point researchers towards new, testable explanations of how complex systems function. A new Perspective co-authored by Assistant Professor Gianmarco Mengaldo from the Department of Mechanical Engineering under the College of Design and Engineering at the National University of Singap
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Environment & ClimateWashington University in St. Louis
Imagine swimming in open water and feeling slime brush against your leg. Most people might shake it off without a second thought. But what if the surface of a boat could do the same? Researchers from Washington University in St. Louis’ McKelvey School of Engineering are about to find out, thanks to a $750,000 grant from the U.S. Department of Defense to develop materials that incorporate soft robo
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Graphene is an exceptionally useful material for creating batteries, catalysts, and electronic devices. Yet producing graphene typically requires temperatures as high as 900°C, limiting energy efficiency and making structural control difficult. To make graphene production more practical, a recent study has overcome this long-standing temperature barrier. In a study published in the Journal of the
Prof Ong hopes the AI Foundry can compress discovery cycles for new materials from months or years to weeks. Professor Shyue Ping Ong wants AI to do more than predict whether a material might work. His vision is a discovery system that can propose new materials for a specific purpose, identify the most useful experiments to run, learn from every result and help scientists understand why a material
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Environment & ClimateWashington University in St. Louis
Machine learning doesn’t replace human intelligence, but it can outlast human endurance, which makes it a very helpful tool for chemistry and material discovery. Scientists know the machine learning models can make predictions based on the vast reams of data it is trained on, but can it take it a step further and massively scale up testing out those predictions? “We already see that AI is powerful
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UAlbany sophomore Collin Flynn spent his summer studying the electrical properties of moon soil in support of ongoing efforts to get humans back to the moon, thanks to a 10-week research opportunity provided through the College of Nanotechnology, Science, and Engineering's Summer Undergraduate Research Program.
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Environment & ClimateQueen Mary University of London
The four projects, funded by the Leverhulme Trust and Wellcome , span all areas of the University and cover topics ranging from healthcare and artificial intelligence to waste management, pollution and sustainable technology. Funded by the Leverhulme Trust, the first of these DTPS will train the next generation of researchers to tackle the global waste crisis through interdisciplinary research and
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Kidney disease is silent in its early stages, progressing without symptoms until the disease is advanced. Researchers in the McKelvey School of Engineering at Washington University in St. Louis, in collaboration with researchers at WashU Medicine and at Texas A&M University, have been developing a minimally invasive method to improve diagnosis in earlier stages. New research from the lab of Srikan
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