A team led by the U.S. Department of Energy’s Oak Ridge National Laboratory demonstrated the viability of a “quantum entanglement witness” capable of proving the presence of entanglement between magnetic particles, or spins, in a quantum material.
She may not wear a white coat or carry a stethoscope, but Christine Walker of ORNL spends her days diagnosing the energy health of buildings and figuring out how to improve their efficiency to achieve cost savings and reduce their carbon footprint.
A team from ORNL, Stanford University and Purdue University developed and demonstrated a novel, fully functional quantum local area network, or QLAN, to enable real-time adjustments to information shared with geographically isolated systems at ORNL
The daily traffic congestion along the streets and interstate lanes of Chattanooga could be headed the way of the horse and buggy with help from ORNL researchers.
As the United States transitions to clean energy, the country has an ambitious goal: cut carbon dioxide emissions in half by the year 2030, if not before. One of the solutions to help meet this challenge is found at ORNL as part of the Better Plants Program.
A new tool that simulates the energy profile of every building in America will give homeowners, utilities and companies a quick way to determine energy use and cost-effective retrofits that can reduce energy and carbon emissions.
Four first-of-a-kind 3D-printed fuel assembly brackets, produced at the Department of Energy’s Manufacturing Demonstration Facility at Oak Ridge National Laboratory, have been installed and are now under routine operating
Long before COVID-19’s rapid transmission led to a worldwide pandemic, Oak Ridge National Laboratory’s Jason DeGraw was performing computer modeling to better understand the impact of virus-laden droplets on indoor air quality
Oak Ridge National Laboratory researchers designed and field-tested an algorithm that could help homeowners maintain comfortable temperatures year-round while minimizing utility costs.
An ORNL-led team comprising researchers from multiple DOE national laboratories is using artificial intelligence and computational screening techniques – in combination with experimental validation – to identify and design five promising drug therapy approaches to target the SARS-CoV-2 virus.