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Even small movements of hydrogen, shown in yellow, were found to cause large energy shifts in the attached iron atoms, shown in silver, which could be of interest in creating novel chemical reactions. Credit: Jill Hemman/ORNL, U.S. Dept. of Energy

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.

A pure lipid membrane formed using lipid-coated water droplets exhibits long-term potentiation, or LTP, associated with learning and memory, emulating hippocampal LTP observed in the brains of mammals and birds. Credit: Jill Hemman/ORNL, U.S. Dept. of Energy

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.

ORNL postdoctoral researcher Runming Tao, pictured with a coin cell battery, led an effort to discover new anode materials for fast-charging lithium-ion batteries. Credit: ORNL/Genevieve Martin, U.S. Dept. of Energy

Researchers at ORNL and the University of Tennessee, Knoxville, discovered a key material needed for fast-charging lithium-ion batteries. The commercially relevant approach opens a potential pathway to improve charging speeds for electric vehicles.

The AI-driven HyperCT platform has three primary points of articulation that can rotate a sample in almost any direction, eliminating the need for human intervention and significantly reducing lengthy experiment times. Credit: Genevieve Martin, ORNL/U.S. Dept. of Energy

Oak Ridge National Laboratory researchers are developing a first-of-its-kind artificial intelligence device for neutron scattering called Hyperspectral Computed Tomography, or HyperCT.

Magnetic quantum material broadens platform for probing next-gen information technologies

Scientists at ORNL used neutron scattering to determine whether a specific material’s atomic structure could host a novel state of matter called a spiral spin liquid.

Oak Ridge National Laboratory’s Leah Broussard shows a neutron-absorbing "wall" that stops all neutrons but in theory would allow hypothetical mirror neutrons to pass through. Credit: Genevieve Martin/ORNL, U.S. Dept. of Energy

To solve a long-standing puzzle about how long a neutron can “live” outside an atomic nucleus, physicists entertained a wild but testable theory positing the existence of a right-handed version of our left-handed universe.

A material’s spins, depicted as red spheres, are probed by scattered neutrons. Applying an entanglement witness, such as the QFI calculation pictured, causes the neutrons to form a kind of quantum gauge. This gauge allows the researchers to distinguish between classical and quantum spin fluctuations. Credit: Nathan Armistead/ORNL, U.S. Dept. of Energy

A team led by the U.S. Department of Energy’s Oak Ridge National Laboratory demonstrated the viability of a “quantum entanglement witness” capable of proving the presence of entanglement between magnetic particles, or spins, in a quantum material.

ORNL researchers used neutrons at the lab’s Spallation Neutron Source to analyze modified high-entropy metal alloys with enhanced strength and ductility, or the ability to stretch, under high-stress without failing. Credit: Rui Feng/ORNL, U.S. Dept. of Energy
Researchers at Oak Ridge National Laboratory have developed a method of adding nanostructures to high-entropy metal alloys, or HEAs, that enhance both strength and ductility, which is the ability to deform or stretch
From top to bottom respectively, alloys were made without nanoprecipitates or with coarse or fine nanoprecipitates to assess effects of their sizes and spacings on mechanical behavior. Credit: Michelle Lehman/ORNL, U.S. Dept. of Energy

Scientists at ORNL and the University of Tennessee, Knoxville, have found a way to simultaneously increase the strength and ductility of an alloy by introducing tiny precipitates into its matrix and tuning their size and spacing.

An ORNL-led team comprising researchers from multiple DOE national laboratories is using artificial intelligence and computational screening techniques – in combination with experimental validation – to identify and design five promising drug therapy approaches to target the SARS-CoV-2 virus. Credit: Michelle Lehman/ORNL, U.S. Dept. of Energy

An ORNL-led team comprising researchers from multiple DOE national laboratories is using artificial intelligence and computational screening techniques – in combination with experimental validation – to identify and design five promising drug therapy approaches to target the SARS-CoV-2 virus.