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Oak Ridge National Laboratory researchers used an invertible neural network, a type of artificial intelligence that mimics the human brain, to select the most suitable materials for desired properties, such as flexibility or heat resistance, with high chemical accuracy. The study could lead to more customizable materials design for industry.

A study led by researchers at ORNL could help make materials design as customizable as point-and-click.

Researchers at Oak Ridge National Laboratory demonstrated center-of-mass scanning transmission electron microscopy to observe lithium along with heavier elements in battery materials at atomic resolution. Credit: Chad Malone/ORNL, U.S. Dept. of Energy

Oak Ridge National Laboratory researchers demonstrated an electron microscopy technique for imaging lithium in energy storage materials, such as lithium ion batteries, at the atomic scale.

ORNL scientists created a new microbial trait mapping process that improves on classical protoplast fusion techniques to identify the genes that trigger desirable genetic traits like improved biomass processing. Credit: Nathan Armistead/ORNL, U.S. Dept. of Energy. Reprinted with the permission of Oxford University Press, publisher of Nucleic Acids Research

ORNL scientists had a problem mapping the genomes of bacteria to better understand the origins of their physical traits and improve their function for bioenergy production.

Scientists, from left, Parans Paranthaman, Tina Summers and Merlin Theodore at the DOE’s Carbon Fiber Technology Facility at ORNL are partnering with industry and university to develop antiviral materials for N95 masks. Credit: Genevieve Martin/ORNL, U.S. Dept. of Energy

Oak Ridge National Laboratory researchers collaborated with Iowa State University and RJ Lee Group to demonstrate a safe and effective antiviral coating for N95 masks. The coating destroys the COVID-19-causing coronavirus and could enable reuse of masks made from various fabrics.

This image illustrates lattice distortion, strain, and ion distribution in metal halide perovskites, which can be induced by external stimuli such as light and heat. Image credit: Stephen Jesse/ORNL

A study by researchers at the ORNL takes a fresh look at what could become the first step toward a new generation of solar batteries.

An artist's rendering of the Ultium Cells battery cell production facility to be built in Spring Hill, Tennessee, which will employ 1,300 people. Recognizing the unique expertise of their organizations, ORNL, TVA, and the Tennessee Department of Economic and Community Development have been working together for several years to bring startups developing battery technologies for EVs and established automotive firms to Tennessee. Credit: Ultium Cells

ORNL, TVA and TNECD were recognized by the Federal Laboratory Consortium for their impactful partnership that resulted in a record $2.3 billion investment by Ultium Cells, a General Motors and LG Energy Solution joint venture, to build a battery cell manufacturing plant in Spring Hill, Tennessee.

Nancy Dudney elected NAE fellow

Materials scientist and chemist Nancy Dudney has been elected to the National Academy of Engineering for her groundbreaking research and development of high-performance solid-state rechargeable batteries.

Govindarajan Muralidharan has been elected a fellow of the National Academy of Inventors.

Muralidharan was recognized for “a highly prolific spirit of innovation in creating or facilitating outstanding inventions that have made a tangible impact on the quality of life, economic development and welfare of society.”

A new process developed by Oak Ridge National Laboratory leverages deep learning techniques to study cell movements in a simulated environment, guided by simple physics rules similar to video-game play. Credit: MSKCC and UTK

Scientists have developed a novel approach to computationally infer previously undetected behaviors within complex biological environments by analyzing live, time-lapsed images that show the positioning of embryonic cells in C. elegans, or roundworms. Their published methods could be used to reveal hidden biological activity. 

ORNL scientists used an electron beam for precision machining of nanoscale materials. Cubes were milled to change their shape and could also be removed from an array. Credit: Kevin Roccapriore/ORNL, U.S. Dept. of Energy

Drilling with the beam of an electron microscope, scientists at ORNL precisely machined tiny electrically conductive cubes that can interact with light and organized them in patterned structures that confine and relay light’s electromagnetic signal.