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Image with a grey and black backdrop - in front is a diamond with two circles coming out from it, showing the insides.

The world’s fastest supercomputer helped researchers simulate synthesizing a material harder and tougher than a diamond — or any other substance on Earth. The study used Frontier to predict the likeliest strategy to synthesize such a material, thought to exist so far only within the interiors of giant exoplanets, or planets beyond our solar system.

Dmytro Bykov, left, and Hector Corzo participate in a value proposition development exercise as part Energy I-Corps

Two ORNL teams recently completed Cohort 18 of Energy I-Corps, an immersive two-month training program where the scientists define their technology’s value propositions, conduct stakeholder discovery interviews and develop viable market pathways.

Man is leaning against the window, arms crossed in a dark navy button up.

Brian Sanders is focused on impactful, multidisciplinary science at Oak Ridge National Laboratory, developing solutions for everything from improved imaging of plant-microbe interactions that influence ecosystem health to advancing new treatments for cancer and viral infections. 

Oak Ridge National Laboratory building and sign for the Computing and Computational Sciences Directorate.

The contract will be awarded to develop the newest high-performance computing system at the Oak Ridge Leadership Computing Facility.

Researcher Brittany Rodriguez works with an ORNL-developed Additive Manufacturing/Compression Molding system that 3D prints large-scale, high-volume parts made from lightweight composites. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

Brittany Rodriguez never imagined she would pursue a science career at a Department of Energy national laboratory. However, after some encouraging words from her mother, input from key mentors at the University of Texas Rio Grande Valley, or UTRGV, and a lot of hard work, Rodriguez landed at DOE’s Manufacturing Demonstration Facility, or MDF, at Oak Ridge National Laboratory.

Digital image of molecules would look like. There are 10 clusters of these shapes in grey, red and blue with a teal blue background

Oak Ridge National Laboratory scientists have developed a method leveraging artificial intelligence to accelerate the identification of environmentally friendly solvents for industrial carbon capture, biomass processing, rechargeable batteries and other applications.

Rectangular box being lifted by a red pully system up the left side of the building

Researchers at ORNL and the University of Maine have designed and 3D-printed a single-piece, recyclable natural-material floor panel tested to be strong enough to replace construction materials like steel. 

Three team members looking at plants stand in front of a mountain scene, two are in orange safety vests.

When Oak Ridge National Laboratory's science mission takes staff off-campus, the lab’s safety principles follow. That’s true even in the high mountain passes of Washington and Oregon, where ORNL scientists are tracking a tree species — and where wildfires have become more frequent and widespread.

Man in blue shirt and grey pants holds laptop and poses next to a green plant in a lab.

John Lagergren, a staff scientist in Oak Ridge National Laboratory’s Plant Systems Biology group, is using his expertise in applied math and machine learning to develop neural networks to quickly analyze the vast amounts of data on plant traits amassed at ORNL’s Advanced Plant Phenotyping Laboratory.

ORNL researcher Felicia Gilliland loads experiment samples into position for the newly installed UR5E robotic arm at the BIO-SANS instrument. The industrial-grade robot changes samples automatically, reducing the need for human assistance and improving sample throughput. Credit: Jeremy Rumsey/ORNL, U.S. Dept. of Energy

The BIO-SANS instrument, located at Oak Ridge National Laboratory’s High Flux Isotope Reactor, is the latest neutron scattering instrument to be retrofitted with state-of-the-art robotics and custom software. The sophisticated upgrade quadruples the number of samples the instrument can measure automatically and significantly reduces the need for human assistance.