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Artificial intelligence is becoming an increasingly valuable tool for ORNL researchers tackling the many mysteries of cancer. Credit: Getty Images.

A team of researchers from ORNL was recognized by the National Cancer Institute in March for their unique contributions in the fight against cancer.

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

Quantum information scientists at ORNL hope to harness beams of light, or photons, as qubits for quantum networking. Credit: ORNL/Carlos Jones

ORNL’s next major computing achievement could open a new universe of scientific possibilities accelerated by the primal forces at the heart of matter and energy.

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.

ORNL will use its land surface modeling tools to determine Baltimore’s climate risk and analyze green infrastructure improvements that can help mitigate impacts on underserved communities as part of a DOE Urban Integrated Field Laboratory project. Source: Google Earth, accessed Sept. 12, 2022

ORNL researchers are deploying their broad expertise in climate data and modeling to create science-based mitigation strategies for cities stressed by climate change as part of two U.S. Department of Energy Urban Integrated Field Laboratory projects.

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.

Scientists at ORNL have created a rhizosphere-on-a-chip research platform, a miniaturized environment to study the ecosystem around poplar tree roots for insights into plant health and soil carbon sequestration. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

Scientists at ORNL have created a miniaturized environment to study the ecosystem around poplar tree roots for insights into plant health and soil carbon sequestration.

Giri Prakash, director of the ARM Data Center, works with the latest ARM computing cluster at ORNL. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

The Atmospheric Radiation Measurement Data Center is shepherding changes to its operations to make the treasure trove of data more easily available accessible and useful to scientists studying Earth’s climate.

The ORNL researchers’ findings may enable better detection of uranium tetrafluoride hydrate, a little-studied byproduct of the nuclear fuel cycle, and better understanding of how environmental conditions influence the chemical behavior of fuel cycle materials. Credit: Kevin Pastoor/Colorado School of Mines

ORNL researchers used the nation’s fastest supercomputer to map the molecular vibrations of an important but little-studied uranium compound produced during the nuclear fuel cycle for results that could lead to a cleaner, safer world.

ORNL, VA and Harvard researchers developed a sparse matrix full of anonymized information on what is thought to be the largest cohort of healthcare data used for this type of research in the U.S. The matrix can be probed with different methods, such as KESER, to gain new insights into human health. Credit: Nathan Armistead/ORNL, U.S. Dept. of Energy

A team of researchers has developed a novel, machine learning–based  technique to explore and identify relationships among medical concepts using electronic health record data across multiple healthcare providers.