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Hilda Klasky, an R&D staff member in the Scalable Biomedical Modeling group at ORNL, has been selected as a senior member of the Association of Computing Machinery, or ACM.
Currently, the biggest hurdle for electric vehicles, or EVs, is the development of advanced battery technology to extend driving range, safety and reliability.
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.
When opportunity meets talent, great things happen. The laser comb developed at ORNL serves as such an example.
Nonfood, plant-based biofuels have potential as a green alternative to fossil fuels, but the enzymes required for production are too inefficient and costly to produce. However, new research is shining a light on enzymes from fungi that could make biofuels economically viable.
For decades, scientists sought a way to apply the outstanding analytical capabilities of neutrons to materials under pressures approaching those surrounding the Earth’s core.
Warming a crystal of the mineral fresnoite, ORNL scientists discovered that excitations called phasons carried heat three times farther and faster than phonons, the excitations that usually carry heat through a material.
Researchers from Yale University and ORNL collaborated on neutron scattering experiments to study hydrogen atom locations and their effects on iron in a compound similar to those commonly used in industrial catalysts.
Neutron scattering techniques were used as part of a study of a novel nanoreactor material that grows crystalline hydrogen clathrates, or HCs, capable of storing hydrogen.
A multi-lab research team led by ORNL's Paul Kent is developing a computer application called QMCPACK to enable precise and reliable predictions of the fundamental properties of materials critical in energy research.