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Media Contacts
Researchers at Oak Ridge National Laboratory have developed free data sets to estimate how much energy any building in the contiguous U.S. will use in 2100. These data sets provide planners a way to anticipate future energy needs as the climate changes.
When the Department of Energy’s Oak Ridge National Laboratory science mission takes staff off-campus, the lab’s safety principles follow. That’s true even in the high mountain passes of Washington and Oregon, where ORNL scientists are tracking a tree species — and where wildfires have become more frequent and widespread.
Purdue University hosted more than 100 attendees at the fourth annual Quantum Science Center summer school. Students and early-career members of the QSC —headquartered at ORNL — participated in lectures, hands-on workshops, poster sessions and panel discussions alongside colleagues from other DOE National Quantum Information Science Research Centers.
Erin Webb, lead for the Bioresources Science and Engineering group at Oak Ridge National Laboratory, has been elected a Fellow of the American Society of Agricultural and Biological Engineers — the society’s highest honor.
John Lagergren, a staff scientist in Oak Ridge National Laboratory’s Plant Systems Biology group, is using his expertise in applied math and machine learning to develop neural networks to quickly analyze the vast amounts of data on plant traits amassed at ORNL’s Advanced Plant Phenotyping Laboratory.
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.
A team of researchers including a member of the Quantum Science Center at ORNL has published a review paper on the state of the field of Majorana research. The paper primarily describes four major platforms that are capable of hosting these particles, as well as the progress made over the past decade in this area.
A team led by researchers at ORNL explored training strategies for one of the largest artificial intelligence models to date with help from the world’s fastest supercomputer. The findings could help guide training for a new generation of AI models for scientific research.
When scientists pushed the world’s fastest supercomputer to its limits, they found those limits stretched beyond even their biggest expectations. In the latest milestone, a team of engineers and scientists used Frontier to simulate a system of nearly half a trillion atoms — the largest system ever modeled and more than 400 times the size of the closest competition.
Joseph Chapman, a research scientist in quantum communications at ORNL, was given the Physical Review Applied Reviewer Excellence 2024 award for his work as a peer reviewer for the journal Physical Review Applied.