91����

Scientists at ORNL have developed 3-D-printed collimator techniques that can be used to custom design collimators that better filter out noise during different types of neutron scattering experiments

Currently, the biggest hurdle for electric vehicles, or EVs, is the development of advanced battery technology to extend driving range, safety and reliability.

Using neutrons to see the additive manufacturing process at the atomic level, scientists have shown that they can measure strain in a material as it evolves and track how atoms move in response to stress.

In 2023, the National School on X-ray and Neutron Scattering, or NXS, marked its 25th year during its annual program, held August 6–18 at the Department of Energy’s Oak Ridge and Argonne National Laboratories.   

The Department of Energy’s Office of Science has selected three ORNL research teams to receive funding through DOE’s new Biopreparedness Research Virtual Environment initiative.

Researchers at the Department of Energy’s 91���� were the first to use neutron reflectometry to peer inside a working solid-state battery and monitor its electrochemistry.

Scientists have long sought to better understand the “local structure” of materials, meaning the arrangement and activities of the neighboring particles around each atom. In crystals, which are used in electronics and many other applications, most of the atoms form highly ordered lattice patterns that repeat. But not all atoms conform to the pattern.

Warming a crystal of the mineral fresnoite, ORNL scientists discovered that excitations called phasons carried heat three times farther and faster than phonons, the excitations that usually carry heat through a material.

Researchers from Yale University and ORNL collaborated on neutron scattering experiments to study hydrogen atom locations and their effects on iron in a compound similar to those commonly used in industrial catalysts.

While studying how bio-inspired materials might inform the design of next-generation computers, scientists at ORNL achieved a first-of-its-kind result that could have big implications for both edge computing and human health.