Cornell chemistry researchers have designed a light-powered, reusable catalyst that’s pre-charged by electricity and capable of driving challenging reactions, with applications including drug development and environmental clean-up.
Researchers developed machine-learning models that can sift through cell-free RNA and identify key biomarkers for chronic fatigue syndrome, a debilitating disease that is difficult to confirm in patients because its symptoms can be easily confused with those of other illnesses.
A team of Cornell computer science researchers has developed a way to “watermark” light in videos, which they can use to detect if video is fake or has been manipulated, another potential tool in the fight against misinformation.
Cornell researchers have developed a two-phase liquid crystal system that can rapidly change – and hold – its shape, transforming from a transparent thin liquid film to an opaque emulsion, and then back again, all with a brief jolt of a high-frequency electric field.
Cornell researchers have been building decision-support tools, optimization methods and artificial intelligence approaches to help the U.S. Navy and Marines quickly and effectively transport people and supplies – including blood for transfusions – in the event of an overseas conflict or humanitarian disaster.
Cornell chemistry and chemical biology researchers have found a new and potentially more accurate way to see what proteins are doing inside living cells — using the cells’ own components as built-in sensors.
