To Track Turbulence in Tokamaks, Researchers Turn to Machine Learning
Machine learning techniques track turbulent blobs in millions of frames of video from tokamak experiments.
Machine learning techniques track turbulent blobs in millions of frames of video from tokamak experiments.
Temperature and Nutrient Availability Affect Microbial Food Webs in Unexpected Ways
Viruses may have unanticipated consequences for ecosystem responses to climate change
Physicists use a detector under an Italian mountain to search for rare nuclear processes to explain why our Universe has more matter than antimatter.
Researchers perform a global analysis of lead-lead collisions, finding that agreement with the reaction rate requires a much smaller nucleus.
Researchers demonstrate a real-world large-scale application of deep neural network models for discovering novel protein-protein interactions.
By confining the transport of electrons and ions in a patterned thin film, scientists alter the material's properties for next-generation electronics.
Researchers combined crystallographic data and computational studies to investigate plutonium-ligand bonding within a hybrid material construct.
Scientists find a new approach to access unusual excited nuclear levels.
Researchers use particle-resolved model simulations to quantify errors in simulations’ simplified optical properties.
The MINERvA experiment in the NuMI beam at Fermilab has made the first accurate image of the proton using neutrinos instead of light as the probe.
Experiment shows that even large, old, and presumably stable stores of soil carbon are vulnerable to warming and could amplify climate change.