Skip to main content
The AI for Energy Report provides a framework for using AI to accelerate decarbonization of the U.S. economy. Credit: Argonne National Laboratory

Groundbreaking report provides ambitious framework for accelerating clean energy deployment while minimizing risks and costs in the face of climate change.

The transportation and industrial sectors together account for more than 50% of the country’s carbon footprint. Defossilization could help reduce new emissions from these and other difficult-to-electrify segments of the U.S. economy.

Scientists at Oak Ridge National Laboratory and six other Department of Energy national laboratories have developed a United States-based perspective for achieving net-zero carbon emissions. 

DOE national laboratory scientists led by Oak Ridge National Laboratory have developed the first tree dataset of its kind, bridging molecular information about the poplar tree microbiome to ecosystem-level processes. Credit: Andy Sproles, ORNL/U.S. Dept. of Energy

A first-ever dataset bridging molecular information about the poplar tree microbiome to ecosystem-level processes has been released by a team of DOE scientists led by ORNL. The project aims to inform research regarding how natural systems function, their vulnerability to a changing climate and ultimately how plants might be engineered for better performance as sources of bioenergy and natural carbon storage.

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

Two different teams that included Oak Ridge National Laboratory employees were honored Feb. 20 with Secretary’s Honor Achievement Awards from the Department of Energy. This is DOE's highest form of employee recognition. 

A multidirectorate group from ORNL attended AGU23 and came away inspired for the year ahead in geospatial, earth and climate science

ORNL scientists and researchers attended the annual American Geophysical Union meeting and came away inspired for the year ahead in geospatial, earth and climate science. 

ORNL’s Tomás Rush examines a culture as part of his research into the plant-fungus relationship that can help or hinder ecosystem health. Credit: Genevieve Martin/ORNL, U.S. Dept. of Energy

New computational framework speeds discovery of fungal metabolites, key to plant health and used in drug therapies and for other uses. 
 

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.

The illustration depicts ocean surface currents simulated by MPAS-Ocean. Credit: Los Alamos National Laboratory, E3SM, U.S. Dept. of Energy

A team from DOE’s Oak Ridge, Los Alamos and Sandia National Laboratories has developed a new solver algorithm that reduces the total run time of the Model for Prediction Across Scales-Ocean, or MPAS-Ocean, E3SM’s ocean circulation model, by 45%. 

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.