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Daryl Yang standing on a bridge overlooking a pond covered in water lillies

Daryl Yang is coupling his science and engineering expertise to devise new ways to measure significant changes going on in the Arctic, a region that’s warming nearly four times faster than other parts of the planet. The remote sensing technologies and modeling tools he develops and leverages for the Next-Generation Ecosystem Experiments in the Arctic project, or NGEE Arctic, help improve models of the ecosystem to better inform decision-making as the landscape changes.

Wavy photo representing high performance computing

Office of Science to announce a new research and development opportunity led by ORNL to advance technologies and drive new capabilities for future supercomputers. This industry research program worth $23 million, called New Frontiers, will initiate partnerships with multiple companies to accelerate the R&D of critical technologies with renewed emphasis on energy efficiency for the next generation of post-exascale computing in the 2029 and beyond time frame.

Bryan Maldonado

As a mechanical engineer in building envelope materials research at ORNL, Bryan Maldonado sees opportunities to apply his scientific expertise virtually everywhere he goes, from coast to coast. As an expert in understanding how complex systems operate, he’s using machine learning methods to control the process and ultimately optimize performance. 

The Frontier supercomputer simulated magnetic responses inside calcium-48, depicted by red and blue spheres. Insights into the nucleus’s fundamental forces could shed light on supernova dynamics.

Nuclear physicists at the Department of Energy’s Oak Ridge National Laboratory recently used Frontier, the world’s most powerful supercomputer, to calculate the magnetic properties of calcium-48’s atomic nucleus. 

digital construction platform

A digital construction platform in development at Oak Ridge National Laboratory is boosting the retrofitting of building envelopes and giving builders the tools to automate the process from design to installation with the assistance of a cable-driven robotic crane.

ORNL researchers Tom Beck, left, Sarp Oral and Rafael Ferreira da Silva have proposed a strategy for integrating classical supercomputers such as Frontier, the world’s first exascale computer, with the emerging field of quantum computing.

A study by more than a dozen scientists at the Department of Energy’s Oak Ridge National Laboratory examines potential strategies to integrate quantum computing with the world’s most powerful supercomputing systems in the pursuit of science.

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.

This is an image of a man sitting at a computer with three screens.

Researchers conduct largest, most accurate molecular dynamics simulations to date of two million correlated electrons using Frontier, the world’s fastest supercomputer. The simulation, which exceed an exaflop using full double precision, is 1,000 times greater in size and speed than any quantum chemistry simulation of it's kind.

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.

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.