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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.

Conceptual art shown here depicts a ligand adapting to its environment.

Researchers at the Department of Energy’s Oak Ridge National Laboratory have found a chemical “chameleon” that could improve the process used to purify rare-earth metals used in clean energy, medical and national security applications.

ORNL scientists used molecular dynamics simulations, exascale computing, lab testing and analysis to accelerate the development of an energy-saving method to produce nanocellulosic fibers.

A team led by scientists at ORNL identified and demonstrated a method to process a plant-based material called nanocellulose that reduced energy needs by a whopping 21%, using simulations on the lab’s supercomputers and follow-on analysis.

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. 

Illustration of oscillating UCI3 bonds

Researchers for the first time documented the specific chemistry dynamics and structure of high-temperature liquid uranium trichloride salt, a potential nuclear fuel source for next-generation reactors. 

solid-state electrolyte to double as energy storage in a car

To speed the arrival of the next-generation solid-state batteries that will power electric vehicles and other technologies, scientists led by ORNL advanced the development of flexible, durable sheets of electrolytes. They used a polymer to create a strong yet springy thin film that binds electrolytic particles and at least doubles energy storage. 

The seven entrepreneurs for Cohort 2024

Seven entrepreneurs comprise the next cohort of Innovation Crossroads, a DOE Lab-Embedded Entrepreneurship Program node based at ORNL. The program provides energy-related startup founders from across the nation with access to ORNL’s unique scientific resources and capabilities, as well as connect them with experts, mentors and networks to accelerate their efforts to take their world-changing ideas to the marketplace.

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.

Frankie White, male in a black suite with a white shirt, is standing crossing his arms.

Early career scientist Frankie White's was part of two major isotope projects at the same time he was preparing to be a father. As co-lead on a team that achieved the first synthesis and characterization of a radium compound using single crystal X-ray diffraction and part of a team that characterized the properties of promethium, White reflects on the life-changing timeline at work, and at home. 

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.