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As part of the Next-Generation Ecosystem Experiments Arctic project, scientists are gathering and incorporating new data about the Alaskan tundra into global models that predict the future of our planet. Credit: ORNL/U.S. Dept. of Energy

Improved data, models and analyses from ORNL scientists and many other researchers in the latest global climate assessment report provide new levels of certainty about what the future holds for the planet 

ORNL is designing a neutronic research engine to evaluate new materials and designs for advanced vehicles using the facilities at the Spallation Neutron Source at ORNL. Credit: Jill Hemman/ORNL, U.S. Dept of Energy, and  Southwest Research Institute.

In the quest for advanced vehicles with higher energy efficiency and ultra-low emissions, ORNL researchers are accelerating a research engine that gives scientists and engineers an unprecedented view inside the atomic-level workings of combustion engines in real time.

Distinguished Inventors

Six scientists at the Department of Energy’s Oak Ridge National Laboratory were named Battelle Distinguished Inventors, in recognition of obtaining 14 or more patents during their careers at the lab.

ORNL researchers in advanced manufacturing, materials science and engineering collaborated to produce face shields and reusable mask molds so that industry can quickly mass produce. Credit: Carlos Jones/Oak Ridge National Laboratory, U.S. Dept. of Energy

The University of Texas at San Antonio (UTSA) has formally launched the Cybersecurity Manufacturing Innovation Institute (CyManII), a $111 million public-private partnership.

Researcher Chase Joslin uses Peregrine software to monitor and analyze a component being 3D printed at the Manufacturing Demonstration Facility at ORNL. Credit: Luke Scime/ORNL, U.S. Dept. of Energy.

Oak Ridge National Laboratory researchers have developed artificial intelligence software for powder bed 3D printers that assesses the quality of parts in real time, without the need for expensive characterization equipment.

Cars and coronavirus

Oak Ridge National Laboratory researchers have developed a machine learning model that could help predict the impact pandemics such as COVID-19 have on fuel demand in the United States.

An organic solvent and water separate and form nanoclusters on the hydrophobic and hydrophilic sections of plant material, driving the efficient deconstruction of biomass. Credit: Michelle Lehman/ORNL, U.S. Dept. of Energy

Scientists at ORNL used neutron scattering and supercomputing to better understand how an organic solvent and water work together to break down plant biomass, creating a pathway to significantly improve the production of renewable

Map with focus on sub-saharan Africa

Researchers at Oak Ridge National Laboratory developed a method that uses machine learning to predict seasonal fire risk in Africa, where half of the world’s wildfire-related carbon emissions originate.

Computational biophysicist Ada Sedova is using experiments and high-performance computing to explore the properties of biological systems and predict their form and function, including research to accelerate drug discovery for COVID-19. Photo credit: Jason Richards, Oak Ridge National Laboratory, U.S. Dept. of Energy.

Ada Sedova’s journey to Oak Ridge National Laboratory has taken her on the path from pre-med studies in college to an accelerated graduate career in mathematics and biophysics and now to the intersection of computational science and biology

The protease protein is both shaped like a heart and functions as one, allowing the virus replicate and spread. Inhibiting the protease would block virus reproduction. Credit: Andrey Kovalevsky/ORNL, U.S. Dept. of Energy

A team of researchers has performed the first room-temperature X-ray measurements on the SARS-CoV-2 main protease — the enzyme that enables the virus to reproduce.