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ORNL’s additive manufacturing compression molding, or AMCM, technology can produce composite-based, lightweight finished parts for airplanes, drones or vehicles in minutes and could acclerate decarbonization for the automobile and aeropsace industries. 

An Oak Ridge National Laboratory-developed advanced manufacturing technology, AMCM, was recently licensed by Orbital Composites and enables the rapid production of composite-based components, which could accelerate the decarbonization of vehicles

Photo collage with text that reads " A New era of discovery"

ORNL, a bastion of nuclear physics research for the past 80 years, is poised to strengthen its programs and service to the United States over the next decade if national recommendations of the Nuclear Science Advisory Committee, or NSAC, are enacted.

ORNL researcher Sreenivasa Jaldanki was recently elevated to IEEE senior member. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

Sreenivasa Jaldanki, a researcher in the Grid Systems Modeling and Controls group at the Department of Energy’s Oak Ridge National Laboratory, was recently elevated to senior membership in the Institute of Electrical and Electronics Engineers, or IEEE.

ORNL’s David Sholl is director of the new DOE Energy Earthshot Non-Equilibrium Energy Transfer for Efficient Reactions center to help decarbonize the industrial chemical industry. Credit: Genevieve Martin, ORNL/U.S. Dept. of Energy

ORNL has been selected to lead an Energy Earthshot Research Center, or EERC, focused on developing chemical processes that use sustainable methods instead of burning fossil fuels to radically reduce industrial greenhouse gas emissions to stem climate change and limit the crisis of a rapidly warming planet.
 

Benefit breakdown, 3D printed vs. wood molds

Oak Ridge National Laboratory researchers have conducted a comprehensive life cycle, cost and carbon emissions analysis on 3D-printed molds for precast concrete and determined the method is economically beneficial compared to conventional wood molds.

Connecting  wires to the interface of the topological insulator and superconductor enables probing of novel electronic properties. Researchers aim for qubits based on theorized Majorana particles. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

Quantum computers process information using quantum bits, or qubits, based on fragile, short-lived quantum mechanical states. To make qubits robust and tailor them for applications, researchers from the Department of Energy’s Oak Ridge National Laboratory sought to create a new material system.

Conceptual art depicts an atomic nucleus and merging neutron stars, respectively, areas of study in ORNL-led projects called NUCLEI and ENAF within the Scientific Discovery through Advanced Computing, or SciDAC, program. Credit: Adam Malin/ORNL, U.S. Dept. of Energy

ORNL is leading two nuclear physics research projects within the Scientific Discovery through Advanced Computing, or SciDAC, program from the Department of Energy Office of Science.

Steven Hamilton, an R&D scientist in the HPC Methods for Nuclear Applications group at ORNL, leads the ExaSMR project. ExaSMR was developed to run on the Oak Ridge Leadership Computing Facility’s exascale-class supercomputer, Frontier. Credit: Genevieve Martin/ORNL, U.S. Dept. of Energy

The Exascale Small Modular Reactor effort, or ExaSMR, is a software stack developed over seven years under the Department of Energy’s Exascale Computing Project to produce the highest-resolution simulations of nuclear reactor systems to date. Now, ExaSMR has been nominated for a 2023 Gordon Bell Prize by the Association for Computing Machinery and is one of six finalists for the annual award, which honors outstanding achievements in high-performance computing from a variety of scientific domains.  

ORNL researchers are demonstrating an automation system for this portable system, currently based in Colorado, for treatment of non-traditional water sources to drinking water standards. Credit: Tzahi Cath/Colorado School of Mines

Researchers at ORNL are developing advanced automation techniques for desalination and water treatment plants, enabling them to save energy while providing affordable drinking water to small, parched communities without high-quality water supplies.

ZEISS Head of Additive Manufacturing Technology Claus Hermannstaedter, left, and ORNL Interim Associate Laboratory Director for Energy Science and Technology Rick Raines sign a licensing agreement that allows ORNL’s machine-learning algorithm, Simurgh, to be used for rapid evaluations of 3D-printed components with industrial X-ray computed tomography, or CT. Using machine learning in CT scanning is expected to reduce the time and cost of inspections of 3D-printed parts by more than ten times.

A licensing agreement between the Department of Energy’s Oak Ridge National Laboratory and research partner ZEISS will enable industrial X-ray computed tomography, or CT, to perform rapid evaluations of 3D-printed components using ORNL’s machine