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.
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.
ORNL climate modeling expertise contributed to a project that assessed global emissions of ammonia from croplands now and in a warmer future, while also identifying solutions tuned to local growing conditions.
Alex May is the first and only full-time data curator at the Department of Energy’s Oak Ridge Leadership Computing Facility, evaluating datasets developed by computational scientists before they are made public through the OLCF’s Constellation portal for open data exchange.
Carl Dukes’ career as an adept communicator got off to a slow start: He was about 5 years old when he spoke for the first time. “I’ve been making up for lost time ever since,” joked Dukes, a technical professional at the Department of Energy’s Oak Ridge National Laboratory.
Mike Huettel is a cyber technical professional. He also recently completed the 6-month Cyber Warfare Technician course for the United States Army, where he learned technical and tactical proficiency leadership in operations throughout the cyber domain.
An advance in a topological insulator material — whose interior behaves like an electrical insulator but whose surface behaves like a conductor — could revolutionize the fields of next-generation electronics and quantum computing, according to scientists at ORNL.
Growing up in China, Yue Yuan stood beneath the world’s largest hydroelectric dam, built to harness the world’s third-longest river. Her father brought her to Three Gorges Dam every year as it was being constructed across the Yangtze River so she could witness its progress.
Oak Ridge National Laboratory researchers serendipitously discovered when they automated the beam of an electron microscope to precisely drill holes in the atomically thin lattice of graphene, the drilled holes closed up.
Researchers from ORNL, the University of Tennessee at Chattanooga and Tuskegee University used mathematics to predict which areas of the SARS-CoV-2 spike protein are most likely to mutate.