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Environmental Sciences Division Director Eric Pierce presented the organization’s 2023 Distinguished Achievement awards at a December 7 all-hands meeting. From left: Megan Johnson, Michael Jones, Maria Colberg, Rachel Pilla, Eric Pierce, Rocio Uria-Martinez, Gbadebo Oladosu and Paul Leiby. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

ORNL Environmental Sciences Division Director Eric Pierce presented the division’s 2023 Distinguished Achievement Awards at the organization’s December all-hands meeting.

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%. 

Photo by James Wainscoat on Unsplash.

A team of researchers from the University of Southern California, the Renaissance Computing Institute at the University of North Carolina, and Oak Ridge, Lawrence Berkeley and Argonne National Laboratories have received a grant from the U.S. Department of Energy to develop the fundamentals of a computational platform that is fault tolerant, robust to various environmental conditions and adaptive to workloads and resource availability.

A researcher plays checkers against an AI-powered robotic arm in 1984. Credit: ORNL, U.S. Dept. of Energy

Despite its futuristic essence, artificial intelligence has a history that can be traced through several decades, and the ORNL has played a major role. From helping to drive fundamental and applied AI research from the field’s early days focused on expert systems, computer programs that rely on AI, to more recent developments in deep learning, a form of AI that enables machines to make evidence-based decisions, the lab’s AI research spans the spectrum.

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.

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.
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. 

ORNL researchers contributed biomass resources analysis to a new report that says carbon dioxide removal targets can be reached by 2050 using existing technology. Source: Jason Richards/ORNL, U.S. Dept. of Energy

Scientists from more than a dozen institutions have completed a first-of-its-kind high-resolution assessment of carbon dioxide removal potential in the United States, charting a path to achieve a net-zero greenhouse gas economy by 2050.

Image of circuitry representing AI.

Research performed by a team, including scientists from ORNL and Argonne National Laboratory, has resulted in a Best Paper Award at the 19th IEEE International Conference on eScience.

Frontier’s exascale power enables the Simple Cloud-Resolving E3SM Atmosphere Model to run years’ worth of climate simulations at unprecedented speed and scale. Credit: Ben Hillman/Sandia National Laboratories, U.S. Dept. of Energy

A 19-member team of scientists from across the national laboratory complex won the Association for Computing Machinery’s 2023 Gordon Bell Special Prize for Climate Modeling for developing a model that uses the world’s first exascale supercomputer to simulate decades’ worth of cloud formations.