Skip to main content
ORNL’s Sergei Kalinin and Rama Vasudevan (foreground) use scanning probe microscopy to study bulk ferroelectricity and surface electrochemistry -- and generate a lot of data. Credit: Jason Richards/ORNL, U.S. Dept. of Energy

At the Department of Energy’s Oak Ridge National Laboratory, scientists use artificial intelligence, or AI, to accelerate the discovery and development of materials for energy and information technologies.

Oak Ridge National Laboratory’s MENNDL AI software system can design thousands of neural networks in a matter of hours. One example uses a driving simulator to evaluate a network’s ability to perceive objects under various lighting conditions. Credit: ORNL, U.S. Dept. of Energy

The Department of Energy’s Oak Ridge National Laboratory has licensed its award-winning artificial intelligence software system, the Multinode Evolutionary Neural Networks for Deep Learning, to General Motors for use in vehicle technology and design.

Jianlin Li, leader of the Energy Storage and Conversion Manufacturing Group, directs the development of advanced manufacturing schemes and pilot-scale devices into emerging energy storage and conversion research. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

In his career focused on energy storage science, Jianlin Li has learned that discovering new ways to process and assemble batteries is just as important as the development of new materials.

Nuclear engineer Nesrin Ozgan Cetiner led ORNL’s collaboration with AMS Corp. to test instrument and control sensors for the next generation of nuclear power reactor technology. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

Toward the goal of bringing the next generation of nuclear power reactor technology online this decade, ORNL and Analysis and Measurement Services Corporation have successfully completed loop testing of instrument and control sensors for an advanced reactor design for small modular reactors.

ATOM logo

The Accelerating Therapeutics for Opportunities in Medicine , or ATOM, consortium today announced the U.S. Department of Energy’s Oak Ridge, Argonne and Brookhaven national laboratories are joining the consortium to further develop ATOM’s artificial intelligence, or AI-driven, drug discovery platform.

Kashif Nawaz, researcher and group leader for multifunctional equipment integration in buildings technologies, is developing a platform for the direct air capture of carbon dioxide that can be retrofitted to existing rooftop heating, ventilation and air conditioning units.  Credit: ORNL/U.S. Dept. of Energy

When Kashif Nawaz looks at a satellite map of the U.S., he sees millions of buildings that could hold a potential solution for the capture of carbon dioxide, a plentiful gas that can be harmful when excessive amounts are released into the atmosphere, raising the Earth’s temperature.

Urban climate modeling

Researchers at Oak Ridge National Laboratory have identified a statistical relationship between the growth of cities and the spread of paved surfaces like roads and sidewalks. These impervious surfaces impede the flow of water into the ground, affecting the water cycle and, by extension, the climate.

ORNL researchers combined additive manufacturing with conventional compression molding to produce high-performance thermoplastic composites, demonstrating the potential for the use of large-scale multimaterial preforms to create molded composites. Credit: ORNL/U.S. Dept. of Energy

Oak Ridge National Laboratory researchers combined additive manufacturing with conventional compression molding to produce high-performance thermoplastic composites reinforced with short carbon fibers.

Xin Sun

Xin Sun has been selected as the associate laboratory director for the Energy Science and Technology Directorate, or ESTD, at the Department of Energy’s Oak Ridge National Laboratory.

ORNL researchers are developing a method to print low-cost, high-fidelity, customizable sensors for monitoring power grid equipment. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

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.