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red and green sphagnum moss

A type of peat moss has surprised scientists with its climate resilience: Sphagnum divinum is actively speciating in response to hot, dry conditions. 

Saubhagya Rathore uses his modeling, hydrology and engineering expertise to improve understanding of the nation’s watersheds to better predict the future climate and to guide resilience strategies. Credit: Genevieve Martin/ORNL, U.S. Dept. of Energy

Growing up exploring the parklands of India where Rudyard Kipling drew inspiration for The Jungle Book left Saubhagya Rathore with a deep respect and curiosity about the natural world. He later turned that interest into a career in environmental science and engineering, and today he is working at ORNL to improve our understanding of watersheds for better climate prediction and resilience.

JungHyun Bae portrait

JungHyun Bae is a nuclear scientist studying applications of particles that have some beneficial properties: They are everywhere, they are unlimited, they are safe.

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.

ORNL scientists mutated amino acids in a receptor protein, shown in green, which diminished interaction with the SARS-CoV-2 virus spike protein, shown in red. Mutating the receptor protein hampered the virus’s ability to infect host cells. Credit: ORNL, U.S. Dept. of Energy

Oak Ridge National Laboratory scientists exploring bioenergy plant genetics have made a surprising discovery: a protein domain that could lead to new COVID-19 treatments.

Samantha Peters co-designed and conducted experiments using ORNL’s high-performance mass spectrometry techniques to prove that bacteriophages deploy genetic code-switching to overwhelm and destroy host bacteria. Credit: Genevieve Martin, ORNL/U.S. Dept. of Energy

Scientists at ORNL have confirmed that bacteria-killing viruses called bacteriophages deploy a sneaky tactic when targeting their hosts: They use a standard genetic code when invading bacteria, then switch to an alternate code at later stages of

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.

ORNL’s Tomás Rush explores the secret lives of fungi and plants for insights into the interactions that determine plant health. Credit: Genevieve Martin/ORNL, U.S. Dept. of Energy

Tomás Rush began studying the mysteries of fungi in fifth grade and spent his college intern days tromping through forests, swamps and agricultural lands searching for signs of fungal plant pathogens causing disease on host plants.

Shown here is the structure of the NEMO protein. A team from ORNL conducted extensive molecular dynamics work on Summit by using both quantum mechanics and machine-learning methods to look at the binding affinity of NEMO and 3CLpro in humans and other species and to consider the structural models derived from the sequences of other coronaviruses. Image courtesy Nature Communications, Dan Jacobson/ORNL.

A new paper published in Nature Communications adds further evidence to the bradykinin storm theory of COVID-19’s viral pathogenesis — a theory that was posited two years ago by a team of researchers at the Department of Energy’s Oak Ridge National Laboratory.

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.