A multidisciplinary ORNL team used expertise in synthetic biology, AI-driven analysis, chemistry, neutrons and materials science to identify new members of a family of enzymes with a natural affinity for degrading synthetic nylon polymers.
A multidisciplinary team of researchers from Oak Ridge National Laboratory (ORNL) and other institutions created a Machine Learning (ML) library for the training of classifiers on spectrographic chemical data.
Evaluate the historical performance and future projections of compound heatwave and drought (CHD) extremes across the contiguous United States using CMIP6 global climate models, providing insights for regional adaptation strategies in response to
The objective of this study is to explore and analyze the spatial patterning of sociodemographic disparities in extreme heat exposure across multiple scales within the Conterminous United States (CONUS).
A numerical weather forecasting model (WRF) was used to simulate 120 storms over the Alabama-Coosa-Tallapoosa (ACT) river basin to explore the effect of climate change on probable maximum precipitation (PMP).
Researchers proposed a cryogenic memory cell design that has a potential to substantially outperform the existing memory cells, achieve much faster access times and lower access and dissipation energies, and reduce the size of the memory cell.
Inside Science has published a story about a recent experiment by ORNL researchers Brian Williams, Ron Sadlier, and Travis Humble.