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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. 

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. 

Five scientists and one in a boat are conducting fish sampling for the biological monitoring program on the DOE Oak Ridge Reservation.

ORNL’s Biological Monitoring and Abatement Program, or BMAP, is marking 40 years of helping steward the DOE’s 33,476 acres of land on which some of the nation’s most powerful science and technology missions are carried out. 

A 3D printing nozzle wrapped in insulation extrudes black composite material into a small square mold on a green and white flat surface in a lab setting. Inset shows a close-up of a pressure gauge connected to brass valves and tubing.

Scientists at ORNL have developed a vacuum-assisted extrusion method that reduces internal porosity by up to 75% in large-scale 3D-printed polymer parts. This new technique addresses the critical issue of porosity in large-scale prints but also paves the way for stronger composites. 

Illustration of a glowing black box emitting digital particles that form into a 3D model of an electrical grid infrastructure, set against a background of binary code and data visualizations.

Researchers at Oak Ridge National Laboratory have developed a modeling method that uses machine learning to accurately simulate electric grid behavior while protecting proprietary equipment details. The approach overcomes a key barrier to accurate grid modeling, helping utilities plan for future demand and prevent blackouts. 

 

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.

Four researchers are standing next to a research rector that is glowing blue

A team from ORNL, joined by university students, recently traveled to the Ohio State University Research Reactor to conduct a novel experiment on nuclear thermal rocket fuel coatings — one that could help propel NASA’s astronauts to Mars faster and more efficiently. 

Two cylinders on each side of the photo are pointing to bright glowing orb in the center.

Scientists at ORNL have developed a method that can track chemical changes in molten salt in real time — helping to pave the way for the deployment of molten salt reactors for energy production.

Different groups of proteins shown in different colors combine and attach to a broken strand of DNA.

Researchers at Georgia State University used the Summit supercomputer to study an elaborate molecular pathway called nucleotide excision repair. Decoding NER’s sophisticated sequence of events and the role of PInC in the pathway could provide key insights into developing novel treatments and preventing conditions that lead to premature aging and certain types of cancer.

Secretary Wright leans over red computer door, signing with silver sharpie as ORNL Director Stephen Streiffer looks on

During his first visit to Oak Ridge National Laboratory, Energy Secretary Chris Wright compared the urgency of the Lab’s World War II beginnings to today’s global race to lead in artificial intelligence, calling for a “Manhattan Project 2.”