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ORNL's Communications team works with news media seeking information about the laboratory. Media may use the resources listed below or send questions to news@ornl.gov.

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Illustration of melting point of lithium chloride, which is shown with green and blue structures in two rows.

Scientists have developed a new machine learning approach that accurately predicted critical and difficult-to-compute properties of molten salts, materials with diverse nuclear energy applications. 

ORNL researcher Priya Ranjan standing outside in front of brick pillars

From decoding plant genomes to modeling microbial behavior, computational biologist Priya Ranjan builds computational tools that turn extensive biological datasets into real-world insights. These tools transform the way scientists ask and answer complex biological questions that advance biotechnology breakthroughs and support cultivation of better crops for energy and food security. 

Illustration of an amino acid molecule that is going through a process from air to water with three phases, split into bubbles

Using the now-decommissioned Summit supercomputer, researchers at ORNL ran the largest and most accurate molecular dynamics simulations yet of the interface between water and air during a chemical reaction. The simulations have uncovered how water controls such chemical reactions by dynamically coupling with the molecules involved in the process. 

Illustration of the GRETA detector, a spherical array of metal cylinders. The detector is divided into two halves to show the inside of the machine. Both halves are attached to metal harnesses, displayed against a black and green cyber-themed background.

Analyzing massive datasets from nuclear physics experiments can take hours or days to process, but researchers are working to radically reduce that time to mere seconds using special software being developed at the Department of Energy’s Lawrence Berkeley and Oak Ridge national laboratories.  

Scientist standing beside mass spectrometry equipment in a laboratory, with instrumentation panels and analysis tools visible in the background

Robert “Bob” Hettich, an ORNL Corporate Fellow, is a pioneer in using mass spectrometry to uncover how microbes interact within complex environments and influence larger systems like plants and humans. A founder of the field of metaproteomics, he leads research that supports bioenergy, environmental resilience and health through advanced protein analysis.

Research scientist Daniel Jacobson is standing with his arms crossed with a dark black backdrop

Daniel Jacobson, distinguished research scientist in the Biosciences Division at ORNL, has been elected a Fellow of the American Institute for Medical and Biological Engineering, or AIMBE, for his achievements in computational biology. 

Researcher is sitting in bio lab surrounded with plants

Dave Weston studies how microorganisms influence plant health and stress tolerance, using the Advanced Plant Phenotyping Laboratory to accelerate research on plant-microbe interactions and develop resilient crops for advanced fuels, chemicals and 

Large group of over 30 students gather in conference room for a presentation, seated with their laptops

Not only did ORNL take home top honors at the 2024 International Conference for High Performance Computing, Networking, Storage, and Analysis (SC24), but the lab’s computing staff also shared career advice and expertise with students eager to enter the world of supercomputing.

Neus Domingo Marimon, ORNL scientist, poses for a photo in black with hair down

Neus Domingo Marimon, leader of the Functional Atomic Force Microscopy group at the Center for Nanophase Materials Sciences of ORNL, has been elevated to senior member of the Institute of Electrical and Electronics Engineers.

the foreground shows new macromolecules that could be made using a process invented by Oak Ridge National Laboratory chemists to upcycle the polymers from discarded plastics.

By editing the polymers of discarded plastics, ORNL chemists have found a way to generate new macromolecules with more valuable properties than those of the starting material.