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The 2023 Billion-Ton Report identifies feedstocks that could be available to produce biofuels to decarbonize the transportation and industrial sectors while potentially tripling the U.S. bioeconomy. The map indicates a mature market scenario, including emerging resources. Credit: ORNL/U.S. Dept. of Energy

The United States could triple its current bioeconomy by producing more than 1 billion tons per year of plant-based biomass for renewable fuels, while meeting projected demands for food, feed, fiber, conventional forest products and exports, according to the DOE’s latest Billion-Ton Report led by ORNL.

: ORNL climate modeling expertise contributed to an AI-backed model that assesses global emissions of ammonia from croplands now and in a warmer future, while identifying mitigation strategies. This map highlights croplands around the world. Credit: U.S. Geological Survey

ORNL climate modeling expertise contributed to a project that assessed global emissions of ammonia from croplands now and in a warmer future, while also identifying solutions tuned to local growing conditions.

ORNL’s Janet Meier presents her lightning talk about designing more sustainable materials for EVs at the inaugural National Lab Research SLAM on Capitol Hill. Credit: Blaise Douros, Lawrence Livermore National Laboratory

ORNL’s Janet Meier won the Energy Security category of the U.S. Department of Energy’s inaugural National Lab Research SLAM on Capitol Hill.

Rigoberto Advincula is a UT-ORNL Governor's Chair and leads the lab's Macromolecular Nanomaterials group. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

Rigoberto “Gobet” Advincula, a scientist at the Department of Energy’s Oak Ridge National Laboratory, has been appointed a Fellow of the Institute of Materials, Minerals and Mining.

Researchers at Corning have found that understanding the stability of the rings of atoms in glass materials can help predict the performance of glass products.

Corning uses neutron scattering to study the stability of different types of glass. Recently, researchers for the company have found that understanding the stability of the rings of atoms in glass materials can help predict the performance of glass products.

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.

Rigoberto “Gobet” Advincula, a scientist at the Department of Energy’s Oak Ridge National Laboratory, has been named a 2023 Fellow of the National Academy of Inventors, or NAI.

Rigoberto “Gobet” Advincula, a scientist at the Department of Energy’s Oak Ridge National Laboratory, has been named a 2023 Fellow of the National Academy of Inventors. Advincula has been recognized for his 14 patents and 21 published filings related to nanomaterials, smart coatings and films, solid-state device fabrication and chemical additives.

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. 

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.
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.