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Clouds of gray smoke in the lower left are funneled northward from wildfires in Western Canada, reaching the edge of the sea ice covering the Arctic Ocean. A second path of thick smoke is visible at the top center of the image, emanating from wildfires in the boreal areas of Russia’s Far East, in this image captured on July 13, 2023. Credit: NASA MODIS

Wildfires have shaped the environment for millennia, but they are increasing in frequency, range and intensity in response to a hotter climate. The phenomenon is being incorporated into high-resolution simulations of the Earth’s climate by scientists at the Department of Energy’s Oak Ridge National Laboratory, with a mission to better understand and predict environmental change.

Jerry Parks leads the Molecular Biophysics group at ORNL, leveraging his expertise in computational chemistry and bioinformatics to unlock the inner workings of proteins—molecules that govern cellular structure and function and are essential to life. Credit: Genevieve Martin, ORNL/U.S. Dept. of Energy

When reading the novel Jurassic Park as a teenager, Jerry Parks found the passages about gene sequencing and supercomputers fascinating, but never imagined he might someday pursue such futuristic-sounding science.

Researchers Melissa Cregger, left, and Xiaohan Yang examine plants in an ORNL greenhouse where biosensors are installed to accelerate plant transformations. Credit: Genevieve Martin/ORNL, U.S. Dept. of Energy.

Nature-based solutions are an effective tool to combat climate change triggered by rising carbon emissions, whether it’s by clearing the skies with bio-based aviation fuels or boosting natural carbon sinks.

This newly manufactured fixed guide vane of a hydropower turbine system was printed at the DOE Manufacturing Demonstration Facility at ORNL. Credit: Genevieve Martin/ORNL, U.S Dept. of Energy

A new report published by ORNL assessed how advanced manufacturing and materials, such as 3D printing and novel component coatings, could offer solutions to modernize the existing fleet and design new approaches to hydropower.

ORNL researchers led by Michael Garvin, left, and David Kainer discovered genetic mutations called structural variants and linked them to autism spectrum disorders, demonstrating an approach that could be used to develop better diagnostics and drug therapies. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

ORNL researchers discovered genetic mutations that underlie autism using a new approach that could lead to better diagnostics and drug therapies.

ORNL scientists created a new microbial trait mapping process that improves on classical protoplast fusion techniques to identify the genes that trigger desirable genetic traits like improved biomass processing. Credit: Nathan Armistead/ORNL, U.S. Dept. of Energy. Reprinted with the permission of Oxford University Press, publisher of Nucleic Acids Research

ORNL scientists had a problem mapping the genomes of bacteria to better understand the origins of their physical traits and improve their function for bioenergy production.

ORNL’s Brenda Pracheil, left, and Kristine Moody collect water samples at Melton Hill Lake using a sophisticated instrument that collects DNA in the water to determine fish species and number of fish in the water, which could prove useful for monitoring hydropower impacts. Credit: Carlos Jones, ORNL/U.S Dept. of Energy

Researchers at Oak Ridge National Laboratory are using a novel approach in determining environmental impacts to aquatic species near hydropower facilities, potentially leading to smarter facility designs that can support electrical grid reliability.

A new process developed by Oak Ridge National Laboratory leverages deep learning techniques to study cell movements in a simulated environment, guided by simple physics rules similar to video-game play. Credit: MSKCC and UTK

Scientists have developed a novel approach to computationally infer previously undetected behaviors within complex biological environments by analyzing live, time-lapsed images that show the positioning of embryonic cells in C. elegans, or roundworms. Their published methods could be used to reveal hidden biological activity. 

This protein drives key processes for sulfide use in many microorganisms that produce methane, including Thermosipho melanesiensis. Researchers used supercomputing and deep learning tools to predict its structure, which has eluded experimental methods such as crystallography.  Credit: Ada Sedova/ORNL, U.S. Dept. of Energy

A team of scientists led by the Department of Energy’s Oak Ridge National Laboratory and the Georgia Institute of Technology is using supercomputing and revolutionary deep learning tools to predict the structures and roles of thousands of proteins with unknown functions.

Nicholas Peters and Raphael Pooser

Of the $61 million recently announced by the U.S. Department of Energy for quantum information science studies, $17.5 million will fund research at DOE’s Oak Ridge National Laboratory. These projects will help build the foundation for the quantum internet, advance quantum entanglement capabilities — which involve sharing information through paired particles of light called photons — and develop next-generation quantum sensors.