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From left, researchers Syed Islam and Ramesh Bhave discuss the nickel sulfate recovered from end-of-life lithium-ion batteries using the membrane solvent extraction process they co-invented at ORNL. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

Scientists at ORNL have developed a technique for recovering and recycling critical materials that has garnered special recognition from a peer-reviewed materials journal and received a new phase of funding for research and development.

The Department of Energy’s latest Fuel Economy Guide includes 2024 model vehicle fuel efficiency data compiled by ORNL researchers, as well as a tool for mapping the most economical driving route. Credit: ORNL/U.S. Dept. of Energy

Oak Ridge National Laboratory researchers have identified the most energy-efficient 2024 model year vehicles available in the United States, including electric and hybrids, in the latest edition of the Department of Energy’s Fuel Economy Guide.

ORNL scientist Zhijia Du, white coat, former ORNL scientist Jianlin Li, blue coat, and Ateios CEO Rajan Kumar inspect battery components during a pilot production run. Credit: Kurt Weiss/ORNL, U.S. Dept of Energy

Ateios Systems licensed an ORNL technology for solvent-free battery component production using electron curing. Through Innovation Crossroads, Ateios continues to work with ORNL to enable readiness for production-quality battery components. 

Environmental Sciences Division Director Eric Pierce presented the organization’s 2023 Distinguished Achievement awards at a December 7 all-hands meeting. From left: Megan Johnson, Michael Jones, Maria Colberg, Rachel Pilla, Eric Pierce, Rocio Uria-Martinez, Gbadebo Oladosu and Paul Leiby. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

ORNL Environmental Sciences Division Director Eric Pierce presented the division’s 2023 Distinguished Achievement Awards at the organization’s December all-hands meeting.

Photo by James Wainscoat on Unsplash.

A team of researchers from the University of Southern California, the Renaissance Computing Institute at the University of North Carolina, and Oak Ridge, Lawrence Berkeley and Argonne National Laboratories have received a grant from the U.S. Department of Energy to develop the fundamentals of a computational platform that is fault tolerant, robust to various environmental conditions and adaptive to workloads and resource availability.

A researcher plays checkers against an AI-powered robotic arm in 1984. Credit: ORNL, U.S. Dept. of Energy

Despite its futuristic essence, artificial intelligence has a history that can be traced through several decades, and the ORNL has played a major role. From helping to drive fundamental and applied AI research from the field’s early days focused on expert systems, computer programs that rely on AI, to more recent developments in deep learning, a form of AI that enables machines to make evidence-based decisions, the lab’s AI research spans the spectrum.

Alex May, pictured above, is the first and only full-time data curator at the Department of Energy’s Oak Ridge Leadership Computing Facility. Credit: Carlos Jones and Wikimedia Commons, background/ORNL, U.S. Dept. of Energy
Alex May is the first and only full-time data curator at the Department of Energy’s Oak Ridge Leadership Computing Facility, evaluating datasets developed by computational scientists before they are made public through the OLCF’s Constellation portal for open data exchange.
Debjani Pal’s photo “Three-Dimensional Breast Cancer Spheroids” won the Director’s Choice Award in Oak Ridge National Laboratory’s Art of Science photo competition. It will be displayed at the American Museum of Science and Energy in Oak Ridge, Tenn. Credit: Debjani Pal/ORNL, U.S. Dept. of Energy
“Three-Dimensional Breast Cancer Spheroids” submitted by radiotherapeutics researcher Debjani Pal is stunning. Brilliant blue dots pop from an electric sphere threaded with bright colors: greens, aqua, hot pink and red.
The AI agent, incorporating a language model-based molecular generator and a graph neural network-based molecular property predictor, processes a set of user-provided molecules (green) and produces/suggests new molecules (red) with desired chemical/physical properties (i.e. excitation energy). Image credit: Pilsun You, Jason Smith/ORNL, U.S. DOE

A team of computational scientists at ORNL has generated and released datasets of unprecedented scale that provide the ultraviolet visible spectral properties of over 10 million organic molecules. 

ORNL researchers contributed biomass resources analysis to a new report that says carbon dioxide removal targets can be reached by 2050 using existing technology. Source: Jason Richards/ORNL, U.S. Dept. of Energy

Scientists from more than a dozen institutions have completed a first-of-its-kind high-resolution assessment of carbon dioxide removal potential in the United States, charting a path to achieve a net-zero greenhouse gas economy by 2050.