Skip to main content
Students from UC Merced collect water samples at Guadalupe Reservoir in Santa Clara County, California. Credit: UC Merced

Environmental scientists at ORNL have recently expanded collaborations with minority-serving institutions and historically Black colleges and universities across the nation to broaden the experiences and skills of student scientists while bringing fresh insights to the national lab’s missions.

ORNL will use its land surface modeling tools to determine Baltimore’s climate risk and analyze green infrastructure improvements that can help mitigate impacts on underserved communities as part of a DOE Urban Integrated Field Laboratory project. Source: Google Earth, accessed Sept. 12, 2022

ORNL researchers are deploying their broad expertise in climate data and modeling to create science-based mitigation strategies for cities stressed by climate change as part of two U.S. Department of Energy Urban Integrated Field Laboratory projects.

ORNL’s RapidCure improves lithium-ion electrode production by producing electrodes faster, reducing the energy necessary for manufacturing and eliminating the need for a solvent recycling unit. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

Researchers at the Department of Energy’s Oak Ridge National Laboratory and their technologies have received seven 2022 R&D 100 Awards, plus special recognition for a battery-related green technology product.

MDF Exterior

ORNL scientists will present new technologies available for licensing during the annual Technology Innovation Showcase. The event is 9 a.m. to 3 p.m. Thursday, June 16, at the Manufacturing Demonstration Facility at ORNL’s Hardin Valley campus.

A smart approach to microscopy and imaging developed at Oak Ridge National Laboratory could drive discoveries in materials for future technologies. Credit: Adam Malin/ORNL, U.S. Dept. of Energy

Researchers at ORNL are teaching microscopes to drive discoveries with an intuitive algorithm, developed at the lab’s Center for Nanophase Materials Sciences, that could guide breakthroughs in new materials for energy technologies, sensing and computing.

The ORNL researchers’ findings may enable better detection of uranium tetrafluoride hydrate, a little-studied byproduct of the nuclear fuel cycle, and better understanding of how environmental conditions influence the chemical behavior of fuel cycle materials. Credit: Kevin Pastoor/Colorado School of Mines

ORNL researchers used the nation’s fastest supercomputer to map the molecular vibrations of an important but little-studied uranium compound produced during the nuclear fuel cycle for results that could lead to a cleaner, safer world.

ORNL, VA and Harvard researchers developed a sparse matrix full of anonymized information on what is thought to be the largest cohort of healthcare data used for this type of research in the U.S. The matrix can be probed with different methods, such as KESER, to gain new insights into human health. Credit: Nathan Armistead/ORNL, U.S. Dept. of Energy

A team of researchers has developed a novel, machine learning–based  technique to explore and identify relationships among medical concepts using electronic health record data across multiple healthcare providers.

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.

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.

Genetic analysis revealed connections between inflammatory activity and development of atomic dermatitis, according to researchers from the UPenn School of Medicine, the Perelman School of Medicine, and Oak Ridge National Laboratory. Credit: Kang Ko/UPenn

University of Pennsylvania researchers called on computational systems biology expertise at Oak Ridge National Laboratory to analyze large datasets of single-cell RNA sequencing from skin samples afflicted with atopic dermatitis.