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Most Promising Engineer of the Year honor goes to Sandia scientist

DOE/Sandia National Laboratories
Grant and Award Announcement

Sandia National Laboratories research and development manager Bishnu Khanal was recently honored with the Most Promising Asian American Engineer of the Year award for his work in next-generation optical lithography process development for numerous technologies, along with his deep-reaching community service.

Propelling wind energy innovation

DOE/Sandia National Laboratories

Motivated by the need to eliminate expensive rare-earth magnets in utility-scale direct-drive wind turbines, Sandia National Laboratories researchers developed a fundamentally new type of rotary electrical contact. Sandia is now ready to partner with the renewable energy industry to develop the next generation of direct-drive wind turbines.

Observations confirm model predictions of sea-level change from Greenland melt

DOE/Los Alamos National Laboratory
Peer-Reviewed Publication

Rising sea levels from melting glaciers and ice sheets pose an increasing threat to coastal communities worldwide. A new analysis of high-resolution satellite observations takes a major step forward in assessing this risk by confirming theoretical predictions and computational models of sea-level changes used to forecast climate-change-driven impacts.

Journal: Science
Funder: Los Alamos National Laboratory

Scientists chip away at a metallic mystery, one atom at a time

DOE/Sandia National Laboratories

Based at Sandia National Laboratories, a team of scientists believes the key to preventing large-scale, catastrophic failures in bridges, airplanes and power plants is to look — very closely — at damage as it first appears at the atomic and nanoscale levels.

Journal: Science Advances

New method for comparing neural networks exposes how artificial intelligence works

DOE/Los Alamos National Laboratory
Reports and Proceedings

A team at Los Alamos National Laboratory has developed a novel approach for comparing neural networks that looks within the “black box” of artificial intelligence to help researchers understand neural network behavior. Neural networks recognize patterns in datasets; they are used everywhere in society, in applications such as virtual assistants, facial recognition systems and self-driving cars.

Through the quantum looking glass

DOE/Sandia National Laboratories
Peer-Reviewed Publication

An ultrathin invention could make future computing, sensing and encryption technologies remarkably smaller and more powerful by helping scientists control a strange but useful phenomenon of quantum mechanics, according to new research recently published in the journal Science.

Journal: Science

New research sheds light on when Mars may have had water

DOE/Los Alamos National Laboratory
Peer-Reviewed Publication

Scientists on NASA’s Perseverance mission made a surprising discovery about the composition of rock in Jezero Crater, one that will help them get a better idea of when water existed on Mars, and ultimately, help them understand if the red planet was ever habitable to microbial life.

Pipelines for progress

DOE/Sandia National Laboratories
Business Announcement

Sandia National Laboratories is sharpening its recruiting focus on select historically Black colleges and universities with its Securing Top Academic Research and Talent, or START, program.

Snow research fills gap in understanding Arctic climate

DOE/Los Alamos National Laboratory
Peer-Reviewed Publication

Comprehensive data from several seasons of field research in the Alaskan Arctic will address uncertainties in Earth-system and climate-change models about snow cover across the region and its impacts on water and the environment.

Journal: The Cryosphere
Funder: DOE/US Department of Energy

Quantum annealing can beat classical computing in limited cases

DOE/Los Alamos National Laboratory

Recent research proves that under certain conditions, quantum annealing computers can run algorithms—including the well-known Shor’s algorithm—more quickly than classical computers. In most cases, however, quantum annealing does not provide a speed-up compared to classical computing when time is limited, according to a study in Nature Communications.

Journal: Nature Communications
Funder: U.S. Department of Energy, Office of Science, Basic Energy Sciences, DOE/US Department of Energy

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