Quantum precision reached in modeling molten salt behavior
Scientists have developed a new machine learning approach that accurately predicted critical and difficult-to-compute properties of molten salts, materials with diverse nuclear energy applications.
Researchers at Oak Ridge National Laboratory have developed a new automated testing capability for semiconductor devices, which is newly available to researchers and industry partners in the Grid Research Integration and Deployment Center.
Researchers at Stanford University, the European Center for Medium-Range Weather Forecasts, or ECMWF, and ORNL used the lab’s Summit supercomputer to better understand atmospheric gravity waves, which influence significant weather patterns that are difficult to forecast.
A digital construction platform in development at Oak Ridge National Laboratory is boosting the retrofitting of building envelopes and giving builders the tools to automate the process from design to installation with the assistance of a cable-driven robotic crane.
Researchers at Oak Ridge National Laboratory have opened a new virtual library where visitors can check out waveforms instead of books. So far, more than 350 users worldwide have utilized the library, which provides vital understanding of an increasingly complex grid.
Oak Ridge National Laboratory scientists have developed a method leveraging artificial intelligence to accelerate the identification of environmentally friendly solvents for industrial carbon capture, biomass processing, rechargeable batteries and other applications.
An Oak Ridge National Laboratory team revealed how chemical species form in a highly reactive molten salt mixture of aluminum chloride and potassium chloride by unraveling vibrational signatures and observing ion exchanges.
ORNL scientists develop a sample holder that tumbles powdered photochemical materials within a neutron beamline — exposing more of the material to light for increased photo-activation and better photochemistry data capture.
Groundwater withdrawals are expected to peak in about one-third of the world’s basins by 2050, potentially triggering significant trade and agriculture shifts, a new analysis finds.
To capitalize on AI and researcher strengths, scientists developed a human-AI collaboration recommender system for improved experimentation performance.