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2023 Top Science Achievements at SNS & HFIR

The 2023 top science achievements from HFIR and SNS feature a broad range of materials research published in high impact journals such as Nature and Advanced Materials.

The Department of Energy’s latest Fuel Economy Guide includes 2024 model vehicle fuel efficiency data compiled by ORNL researchers, as well as a tool for mapping the most economical driving route. Credit: ORNL/U.S. Dept. of Energy

Oak Ridge National Laboratory researchers have identified the most energy-efficient 2024 model year vehicles available in the United States, including electric and hybrids, in the latest edition of the Department of Energy’s Fuel Economy Guide.

Summit debuted in 2018 at No.1 on the TOP500 list of the world’s most powerful supercomputers with a peak performance of 200 petaflops. Since then, nearly 5,000 users have used Summit to conduct research on climate, energy, public health and national security.

The U.S. Department of Energy’s Oak Ridge Leadership Computing Facility has informed the recipients of high-performance computing time through the SummitPLUS allocation program, which extends the operation of the Summit supercomputer through October 2024. 

The illustration depicts ocean surface currents simulated by MPAS-Ocean. Credit: Los Alamos National Laboratory, E3SM, U.S. Dept. of Energy

A team from DOE’s Oak Ridge, Los Alamos and Sandia National Laboratories has developed a new solver algorithm that reduces the total run time of the Model for Prediction Across Scales-Ocean, or MPAS-Ocean, E3SM’s ocean circulation model, by 45%. 

Domenick Leto poses near assessment equipment for nuclear materials. Credit: Lena Shoemaker/ORNL, U.S. Dept. of Energy

Drawing from his experience during the pandemic, Domenick Leto recognizes the need for the United States to have inexpensive, reliable capabilities to combat any type of disruption to national security, including nationwide medical emergencies. Leto and colleagues received a patent for a simple, inexpensive way to sterilize masks, plastic, and medical equipment from the COVID-19 virus.

Wire arc additive manufacturing allowed this robot arm at ORNL to transform metal wire into a complete steam turbine blade like those used in power plants. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

Researchers at ORNL became the first to 3D-print large rotating steam turbine blades for generating energy in power plants.

ORNL retiree Duane Starr and his wife, Nancy, pose with the critical frequencies demo unit Duane designed, built and donated to the laboratory to support nuclear workshops.  Credit: Carlos Jones/ORNL, Dept. of Energy

For years, Duane Starr led workshops at ORNL to help others from across the U.S. government understand uranium processing technologies. After his retirement, Starr donated a 5-foot-tall working model, built in his garage, that demonstrates vibration harmonics, consistent with operation of a super critical gas centrifuge rotor, a valuable resource to ongoing ORNL-led workshops. 

Alex May, pictured above, is the first and only full-time data curator at the Department of Energy’s Oak Ridge Leadership Computing Facility. Credit: Carlos Jones and Wikimedia Commons, background/ORNL, U.S. Dept. of Energy
Alex May is the first and only full-time data curator at the Department of Energy’s Oak Ridge Leadership Computing Facility, evaluating datasets developed by computational scientists before they are made public through the OLCF’s Constellation portal for open data exchange.
Debjani Pal’s photo “Three-Dimensional Breast Cancer Spheroids” won the Director’s Choice Award in Oak Ridge National Laboratory’s Art of Science photo competition. It will be displayed at the American Museum of Science and Energy in Oak Ridge, Tenn. Credit: Debjani Pal/ORNL, U.S. Dept. of Energy
“Three-Dimensional Breast Cancer Spheroids” submitted by radiotherapeutics researcher Debjani Pal is stunning. Brilliant blue dots pop from an electric sphere threaded with bright colors: greens, aqua, hot pink and red.
The AI agent, incorporating a language model-based molecular generator and a graph neural network-based molecular property predictor, processes a set of user-provided molecules (green) and produces/suggests new molecules (red) with desired chemical/physical properties (i.e. excitation energy). Image credit: Pilsun You, Jason Smith/ORNL, U.S. DOE

A team of computational scientists at ORNL has generated and released datasets of unprecedented scale that provide the ultraviolet visible spectral properties of over 10 million organic molecules.