USC leads national AI research project to accelerate scientific discovery
Grant and Award Announcement
Updates every hour. Last Updated: 1-Nov-2026 23:16 ET (2-Nov-2026 04:16 GMT/UTC)
USC is among the first universities selected to help lead the U.S. Department of Energy’s Genesis Mission, a national initiative that unites the country’s 17 national laboratories, universities and industry to explore artificial intelligence for scientific discovery.
Using a small molecule first synthesized by Cold Spring Harbor Laboratory’s Moses lab, researchers have restored the effectiveness of the last-resort antibiotic vancomycin against drug-resistant bacteria. By restoring the power of existing medications, the findings suggest that fundamental chemistry may be our most promising weapon against the growing threat of antibiotic resistance.
Chemists from Otto von Guericke University Magdeburg have achieved an important research success in the fight against resistant bacteria - the team led by scientist Professor Dr. Dieter Schinzer from the Institute of Chemistry have succeeded for the first time in producing key building blocks of the naturally occurring Neosorangicin A in the laboratory. This means that it is now possible to develop Neosorangicin A in a targeted manner as a highly promising reserve antibiotic candidate with a view to combating antibiotic resistance in future.
Researchers at Westlake University have developed a new anion exchange membrane for water electrolysis that combines long-term chemical stability with easier large-scale manufacturing. The material reduces reliance on corrosive superacids during synthesis and performs efficiently in both lab-scale devices and kilowatt-scale hydrogen-producing stacks.
Spectral imaging allows materials to be identified without contact, but compact systems often struggle to preserve enough information for accurate reconstruction. Researchers from Zhejiang Normal University, Zhejiang University, and Westlake University have introduced a geometry-driven spectral encoding strategy based on the Euclidean Distance of Encoding space (EDE). Instead of optimizing only the statistical properties of an encoding matrix, EDE directly maximizes the separation between encoded spectral responses in measurement space. The team combined genetic algorithms, automatic differentiation, and transfer-matrix modeling to design manufacturable TiO₂/SiO₂ multilayer thin-film encoders. The resulting system improves reconstruction performance over random, correlation-optimized, and coherence-optimized benchmarks, and enables high-fidelity spectral recovery across the visible to short-wave infrared range. The work establishes a new geometric design paradigm for compact, intelligent computational optical systems.