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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.

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.

From left to right, Cortney Piper, executive director of the Tennessee Advanced Energy Business Council; Susan Hubbard, ORNL deputy for science and technology; Dan Miller, innovation Crossroads program lead; and Mike Paulus, ORNL director of technology transfer, attend the Innovation Crossroads Showcase at the Knoxville Chamber on Sept. 22. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

A crowd of investors and supporters turned out for last week’s Innovation Crossroads Showcase at the Knoxville Chamber as part of Innov865 Week. Sponsored by ORNL and the Tennessee Advanced Energy Business Council, the event celebrated deep-tech entrepreneurs and the Oak Ridge Corridor as a growing energy innovation hub for the nation.

ORNL mechanical engineer Marm Dixit focuses his research on solid-state batteries and their potential use in electric vehicles. Credit: ORNL, U.S. Dept. of Energy

Mechanical engineer Marm Dixit’s work is all about getting electricity to flow efficiently from one end of a solid-state battery to the other. It’s a high-stakes problem

ORNL researchers worked with partners at the Colorado School of Mines and Baylor University to develop a new process optimization and control method for a closed-circuit reverse osmosis desalination system. The work is intended to support fully automated, decentralized water treatment plants. Credit: Andrew Sproles/ORNL, U.S. Dept. of Energy

Oak Ridge National Laboratory scientists worked with the Colorado School of Mines and Baylor University to develop and test control methods for autonomous water treatment plants that use less energy and generate less waste.

ORNL has developed the SolidPAC tool to help researchers design energy-dense, long-lived and safe solid-state batteries. Credit: Andy Sproles/ORNL, U.S. Dept. of Energy

Scientists can speed the design of energy-dense solid-state batteries using a new tool created by Oak Ridge National Laboratory.

ORNL researchers in advanced manufacturing, materials science and engineering collaborated to produce face shields and reusable mask molds so that industry can quickly mass produce. Credit: Carlos Jones/Oak Ridge National Laboratory, U.S. Dept. of Energy

The University of Texas at San Antonio (UTSA) has formally launched the Cybersecurity Manufacturing Innovation Institute (CyManII), a $111 million public-private partnership.

U.S. Department of Energy Deputy Secretary Mark Menezes (right) tours the DemeTECH N95 filter material production area with Xin Sun, ORNL interim associate laboratory director (center) and Craig Blue, ORNL advanced manufacturing program manager. Credit: US Dept. of Energy

A collaboration between the ORNL and a Florida-based medical device manufacturer has led to the addition of 500 jobs in the Miami area to support the mass production of N95 respirator masks.

Jianlin Li employs ORNL’s world-class battery research facility to validate the innovative safety technology. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

Soteria Battery Innovation Group has exclusively licensed and optioned a technology developed by Oak Ridge National Laboratory designed to eliminate thermal runaway in lithium ion batteries due to mechanical damage.

Cars and coronavirus

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.