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A multiport design allows a utility to easily interface with an EV truck stop to provide fast-charging at megawatt-scale. Credit: Andy Sproles/ORNL, U.S. Dept. of Energy

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.

ORNL researchers led by Michael Garvin, left, and David Kainer discovered genetic mutations called structural variants and linked them to autism spectrum disorders, demonstrating an approach that could be used to develop better diagnostics and drug therapies. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

ORNL researchers discovered genetic mutations that underlie autism using a new approach that could lead to better diagnostics and drug therapies.

This diagram demonstrates how a concentrating solar thermal plant could use molten salts to store solar energy that could later be used to generate electricity. Credit: Jaimee Janiga/ORNL, U.S. Dept. of Energy

Oak Ridge National Laboratory scientists recently demonstrated a low-temperature, safe route to purifying molten chloride salts that minimizes their ability to corrode metals. This method could make the salts useful for storing energy generated from the sun’s heat.

Researcher Sun Hongbin examines material changes to a battery made in the DOE’s Battery Manufacturing Facility using an ultrasound sensor. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

Scientists at Oak Ridge National Laboratory are using ultrasounds — usually associated with medical imaging — to check the health of an operating battery. The technique uses sensors as small as a thumbnail, which could be attached to a lithium-ion battery inside a car.

Researchers at Oak Ridge National Laboratory probed the chemistry of radium to gain key insights on advancing cancer treatments using radiation therapy. Credit: Adam Malin/ORNL, U.S. Dept. of Energy

Researchers at ORNL explored radium’s chemistry to advance cancer treatments using ionizing radiation.

Researchers used quantum Monte Carlo calculations to accurately render the structure and electronic properties of germanium selenide, a semiconducting nanomaterial. Credit: Paul Kent/ORNL, U.S. Dept. of Energy

A multi-lab research team led by ORNL's Paul Kent is developing a computer application called QMCPACK to enable precise and reliable predictions of the fundamental properties of materials critical in energy research.

Oak Ridge National Laboratory researchers developed an invertible neural network, a type of artificial intelligence that mimics the human brain, to improve accuracy in climate-change models and predictions. Credit: Getty Images

Oak Ridge National Laboratory researchers developed an invertible neural network, a type of artificial intelligence that mimics the human brain, to improve accuracy in climate-change models and predictions.

The online Fuel Economy Guide, compiled by ORNL researchers, provides simple tips to save at the pump including the Trip Calculator tool to better navigate vehicle choice and estimate mileage. Credit: Storyblocks

Oak Ridge National Laboratory researchers determined that for every 5 miles per hour that drivers travel over a 50-mph speed limit, fuel economy decreases by 7% and equates to paying an extra 28 cents per gallon at current.

Physicist Charles Havener uses the NASA end station at ORNL’s Multicharged Ion Research Facility to simulate the origin of X-ray emissions from space. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

Scientists are using Oak Ridge National Laboratory’s Multicharged Ion Research Facility to simulate the cosmic origin of X-ray emissions resulting when highly charged ions collide with neutral atoms and molecules, such as helium and gaseous hydrogen.

With seismic and acoustic data recorded by remote sensors near ORNL’s High Flux Isotope Reactor, researchers could predict whether the reactor was on or off with 98% accuracy. Credit: Nathan Armistead/ORNL, U.S. Dept. of Energy

An Oak Ridge National Laboratory team developed a novel technique using sensors to monitor seismic and acoustic activity and machine learning to differentiate operational activities at facilities from “noise” in the recorded data.