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Hydrologist Jesus Gomez-Velez brings his expertise in river systems and mathematics to ORNL’s modeling and simulation research to better understand flow and transport processes in the nation’s watersheds. Credit: Genevieve Martin/ORNL, U.S. Dept. of Energy

Hydrologist Jesús “Chucho” Gomez-Velez is in the right place at the right time with the right tools and colleagues to explain how the smallest processes within river corridors can have a tremendous impact on large-scale ecosystems.

Oak Ridge National Laboratory’s Dave Weston works in a chamber at the DOE SPRUCE whole ecosystem experiment site in the peatlands of northern Minnesota. Credit: Kyle Pearson/ORNL, U.S. Dept. of Energy

A quest to understand how Sphagnum mosses facilitate the storage of vast amounts of carbon in peatlands led scientists to a surprising discovery: the plants have sex-based differences that appear to impact the carbon-storing process.

Jason Gardner, Sandra Davern and Peter Thornton have been elected fellows of AAAS. Credit: Laddy Fields/ORNL, U.S. Dept. of Energy

Three scientists from the Department of Energy’s Oak Ridge National Laboratory have been elected fellows of the American Association for the Advancement of Science, or AAAS.

Computational systems biologists at ORNL worked with the U.S. Department of Veterans Affairs and other institutions to identify 139 locations across the human genome tied to risk factors for varicose veins, marking a first step in the development of new treatments. Credit: Andy Sproles/ORNL, U.S. Dept. of Energy

As part of a multi-institutional research project, scientists at ORNL leveraged their computational systems biology expertise and the largest, most diverse set of health data to date to explore the genetic basis of varicose veins.

Hybrid poplar trees such as these shown in an ORNL greenhouse were engineered with the REVEILLE1 gene to delay dormancy and produce more biomass. The research was led by the Center for Bioenergy Innovation at ORNL with the Joint Genome Institute, Brookhaven National Laboratory, the HudsonAlpha Institute for Biotechnology, the University of Connecticut and other partners. Credit: Genevieve Martin/ORNL, U.S. Dept. of Energy

A team of scientists led by ORNL discovered the gene in agave that governs when the plant goes dormant and used it to create poplar trees that nearly doubled in size, increasing biomass yield for biofuels production

Erica Prates is using her skills as a computational systems biologist to link the smallest molecules to their impact on large ecosystems. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

Erica Prates has found a way to help speed the pursuit of healthier ecosystems by linking the function of the smallest molecules to their effects on large-scale processes, leveraging a combination of science, math and computing.

Using as much as 50 percent lignin by weight, a new composite material created at ORNL is well suited for use in 3D printing.

Scientists at the Department of Energy’s Oak Ridge National Laboratory have created a recipe for a renewable 3D printing feedstock that could spur a profitable new use for an intractable biorefinery byproduct: lignin.

Omar Demerdash

Attracted to biology, math, and physics as a young student, Omar Demerdash decided that when the time came to narrow his academic interests he wouldn’t pick and choose: he’d pursue them all. Today he’s using his expertise in computational biophysics to model and analyze how molecules interact with p...

Esther Parish

Esther Parish’s holistic approach to life is apparent not only in her environmental research at Oak Ridge National Laboratory, but in her careful cultivation of a future crop of young scientists. Her expertise as a geographer coupled with a keen interest in the natural world drives Parish’s resea...

Oak Ridge National Laboratory bioinformatics researcher Dan Jacobson plugs AI, deep learning into biosystems.

Dan Jacobson is illuminating the workings of biological systems from the molecular scale up by leveraging Oak Ridge National Laboratory’s supercomputing resources to create machine- and deep-learning techniques more easily understood by humans