Katy Bradford: Cassette approach offers compelling construction solution
DOE commissioned a neutron imaging instrument, VENUS, at the Spallation Neutron Source in July. VENUS instrument scientists will use AI to deliver 3D models to researchers in half the time it typically takes.
Debjani Singh, a senior scientist at ORNL, leads the HydroSource project, which enhances hydropower research by making water data more accessible and useful. With a background in water resources, data science, and earth science, Singh applies innovative tools like AI to advance research. Her career, shaped by her early exposure to science in India, focuses on bridging research with practical applications.
John joined the MPEX project in 2019 and has served as project manager for several organizations within ORNL.
The award was given in “recognition of his lifelong leadership in fusion technology for plasma fueling systems in magnetically confined fusion systems.”
Prasanna Balaprakash, director of AI programs at the Department of Energy’s Oak Ridge National Laboratory, has been appointed to Tennessee’s Artificial Intelligence Advisory Council.
The world’s fastest supercomputer helped researchers simulate synthesizing a material harder and tougher than a diamond — or any other substance on Earth. The study used Frontier to predict the likeliest strategy to synthesize such a material, thought to exist so far only within the interiors of giant exoplanets, or planets beyond our solar system.
Two additive manufacturing researchers from ORNL received prestigious awards from national organizations. Amy Elliott and Nadim Hmeidat, who both work in the Manufacturing Science Division, were recognized recently for their early career accomplishments.
Two ORNL teams recently completed Cohort 18 of Energy I-Corps, an immersive two-month training program where the scientists define their technology’s value propositions, conduct stakeholder discovery interviews and develop viable market pathways.
Researchers at the Department of Energy’s Oak Ridge National Laboratory and partner institutions have launched a project to develop an innovative suite of tools that will employ machine learning algorithms for more effective cybersecurity analysis of the U.S. power grid.
Power companies and electric grid developers turn to simulation tools as they attempt to understand how modern equipment will be affected by rapidly unfolding events in a complex grid.