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ORNL seismic researcher Chengping Chai placed seismic sensors on the ground at various distances from an ORNL nuclear reactor to learn whether they could detect its operating state. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

Like most scientists, Chengping Chai is not content with the surface of things: He wants to probe beyond to learn what’s really going on. But in his case, he is literally building a map of the world beneath, using seismic and acoustic data that reveal when and where the earth moves.

ORNL researchers, from left, Yang Liu, Xiaohan Yang and Torik Islam, collaborated on the development of a new capability to insert multiple genes simultaneously for fast, efficient transformation of plants into better bioenergy feedstocks. Credit: Genevieve Martin/ORNL, U.S. Dept. of Energy

In a discovery aimed at accelerating the development of process-advantaged crops for jet biofuels, scientists at ORNL developed a capability to insert multiple genes into plants in a single step.

ORNL researchers have developed a new pressing method, shown as blue circle on right, that produces a more uniform solid electrolyte than the traditionally processed material with more voids, shown as gray circle on left. The material can be integrated into a battery system, center, for improved stability and rate performance. Credit: Andy Sproles/ORNL, U.S. Dept. of Energy

ORNL scientists found that a small tweak created big performance improvements in a type of solid-state battery, a technology considered vital to broader electric vehicle adoption.

Rigoberto Advincula

Rigoberto Advincula, a renowned scientist at ORNL and professor of Chemical and Biomolecular Engineering at the University of Tennessee, has won the Netzsch North American Thermal Analysis Society Fellows Award for 2023.

Neutron scattering experiments at the Spallation Neutron Source revealed how the dynamics between copper and oxygen make a special type of enzyme excel at breaking down biomass. Insights could lead to lowering the cost of biofuel production. Credit: Jill Hemman/ORNL, U.S. Dept. of Energy

Nonfood, plant-based biofuels have potential as a green alternative to fossil fuels, but the enzymes required for production are too inefficient and costly to produce. However, new research is shining a light on enzymes from fungi that could make biofuels economically viable.

Carinata, pictured in full bloom at a producer’s field in Georgia, is a winter cover crop of interest as a feedstock for sustainable aviation fuel. Credit: Southeast Partnership for Advanced Renewables from Carinata

Oak Ridge National Laboratory scientists led the development of a supply chain model revealing the optimal places to site farms, biorefineries, pipelines and other infrastructure for sustainable aviation fuel production.

Mickey Wade, associate laboratory director for the Fusion and Fission Energy and Science Directorate, addresses attendees of an event to celebrate the licensing of an augmented reality technology to Teletrix. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

A method using augmented reality to create accurate visual representations of ionizing radiation, developed at ORNL, has been licensed by Teletrix, a firm that creates advanced simulation tools to train the nation’s radiation control workforce.

Marm Dixit, a Weinberg Distinguished Staff Fellow at Oak Ridge National Laboratory, was honored for his work on imaging techniques for solid state batteries. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

Marm Dixit, a Weinberg Distinguished Staff Fellow at ORNL has received the 2023 Rosalind Franklin Young Investigator Award.

ORNL scientists mutated amino acids in a receptor protein, shown in green, which diminished interaction with the SARS-CoV-2 virus spike protein, shown in red. Mutating the receptor protein hampered the virus’s ability to infect host cells. Credit: ORNL, U.S. Dept. of Energy

Oak Ridge National Laboratory scientists exploring bioenergy plant genetics have made a surprising discovery: a protein domain that could lead to new COVID-19 treatments.

An AI-generated image representing atoms and artificial neural networks. Credit: Maxim Ziatdinov, ORNL

Researchers at ORNL have developed a machine-learning inspired software package that provides end-to-end image analysis of electron and scanning probe microscopy images.