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.
Understanding how methanogenic bacteria can “bio-mine” minerals advances biotechnology and helps scientists understand the Earth’s geological history.
Powerful statistical tools, simulations, and supercomputers explore a billion different nuclear forces and predict properties of the very-heavy lead-208 nucleus.
Patterned arrays of nanomagnets produce X-ray beams with a switchable rotating wavefront twist.
Nuclear physicists test whether next generation artificial intelligence and machine learning tools can process experimental data in real time.
Particles choose partners for short-range correlations differently when farther apart in light nuclei versus when packed closer together in heavy nuclei.
As machine learning tools gain momentum, a review of machine learning projects reveals these tools are already in use throughout nuclear physics.
