Updated software improves slicing for large-format 3D printing
Researchers at Oak Ridge National Laboratory’s Spallation Neutron Source have developed a diamond anvil pressure cell that will enable high-pressure science currently not possible at any other neutron source in the world.
A method developed at Oak Ridge National Laboratory to print high-fidelity, passive sensors for energy applications can reduce the cost of monitoring critical power grid assets.
To better understand the spread of SARS-CoV-2, the virus that causes COVID-19, Oak Ridge National Laboratory researchers have harnessed the power of supercomputers to accurately model the spike protein that binds the novel coronavirus to a human cell receptor.
A new Department of Energy report produced by Oak Ridge National Laboratory details national and international trends in hydropower, including the role waterpower plays in enhancing the flexibility and resilience of the power grid.
Fuel economy can take a tumble when temperatures plummet, according to the Department of Energy’s 2021 Fuel Economy Guide. Compiled by researchers at Oak Ridge National Laboratory, the guide includes several tips to improve a vehicle’s fuel performance.
If air taxis become a viable mode of transportation, Oak Ridge National Laboratory researchers have estimated they could reduce fuel consumption significantly while alleviating traffic congestion.
Pauling’s Rules is the standard model used to describe atomic arrangements in ordered materials. Neutron scattering experiments at Oak Ridge National Laboratory confirmed this approach can also be used to describe highly disordered materials.
A UCLA-led team that discovered the first intrinsic ferromagnetic topological insulator – a quantum material that could revolutionize next-generation electronics – used neutrons at Oak Ridge National Laboratory to help verify their finding.
Oak Ridge National Laboratory researchers have developed a machine learning model that could help predict the impact pandemics such as COVID-19 have on fuel demand in the United States.
Researchers at Oak Ridge National Laboratory developed a method that uses machine learning to predict seasonal fire risk in Africa, where half of the world’s wildfire-related carbon emissions originate.