Artificial intelligence tools secure tomorrow’s electric grid
Scientists at ORNL developed a competitive, eco-friendly alternative made without harmful blowing agents.
ORNL researchers Ben Ollis and Max Ferrari will be in Adjuntas to join the March 18 festivities but also to hammer out more technical details of their contribution to the project: making the microgrids even more reliable.
When aging vehicle batteries lack the juice to power your car anymore, they may still hold energy. Yet it’s tough to find new uses for lithium-ion batteries with different makers, ages and sizes. A solution is urgently needed because battery recycling options are scarce.
Researchers at Oak Ridge National Laboratory have designed architecture, software and control strategies for a futuristic EV truck stop that can draw megawatts of power and reduce carbon emissions.
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.
John “Jack” Cahill is out to illuminate previously unseen processes with new technology, advancing our understanding of how chemicals interact to influence complex systems whether it’s in the human body or in the world beneath our feet.
Oak Ridge National Laboratory scientists designed a recyclable polymer for carbon-fiber composites to enable circular manufacturing of parts that boost energy efficiency in automotive, wind power and aerospace applications.
The Earth System Grid Federation, a multi-agency initiative that gathers and distributes data for top-tier projections of the Earth’s climate, is preparing a series of upgrades.
In human security research, Thomaz Carvalhaes says, there are typically two perspectives: technocentric and human centric. Rather than pick just one for his work, Carvalhaes uses data from both perspectives to understand how technology impacts the lives of people.
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.