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This image illustrates lattice distortion, strain, and ion distribution in metal halide perovskites, which can be induced by external stimuli such as light and heat. Image credit: Stephen Jesse/ORNL

ORNL multimodal study sheds new light on promising photovoltaic material

A study by researchers at the ORNL takes a fresh look at what could become the first step toward a new generation of solar batteries.

Mars Rover 2020

Secretary’s Honor Awards recognize dozens of ORNL employees

More than 50 current employees and recent retirees from ORNL received Department of Energy Secretary’s Honor Awards from Secretary Jennifer Granholm in January as part of project teams spanning the national laboratory system. The annual awards recognized 21 teams and three individuals for service and contributions to DOE’s mission and to the benefit of the nation.

This protein drives key processes for sulfide use in many microorganisms that produce methane, including Thermosipho melanesiensis. Researchers used supercomputing and deep learning tools to predict its structure, which has eluded experimental methods such as crystallography. Credit: Ada Sedova/ORNL, U.S. Dept. of Energy

Scientists use Summit supercomputer, deep learning to predict protein functions at genome scale

A team of scientists led by the Department of Energy’s Oak Ridge National Laboratory and the Georgia Institute of Technology is using supercomputing and revolutionary deep learning tools to predict the structures and roles of thousands of proteins with unknown functions.

Ten scientists from the Department of Energy’s Oak Ridge National Laboratory are among the world’s most highly cited researchers. Credit: ORNL, U.S. Dept. of Energy

Ten ORNL scientists among world’s most highly cited researchers

Ten scientists from the Department of Energy’s Oak Ridge National Laboratory are among the world’s most highly cited researchers, according to a bibliometric analysis conducted by the scientific publication analytics firm Clarivate.

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.

ORNL’s simulation tool creates digital twin of buildings from coast to coast

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.

Gina Accawi, ORNL’s group leader for digital manufacturing and analyses framework, is making sure advanced manufacturing software and systems keep pace in a secure cyberspace and 5G world. Credit: ORNL/U.S. Dept. of Energy

Gina Accawi: Designing software architecture for advanced manufacturing cybersecurity

As a computer engineer at Oak Ridge National Laboratory, Gina Accawi has long been the quiet and steady force behind some of the Department of Energy’s most widely used online tools and applications.

Scientists genetically engineered bacteria for itaconic acid production, creating dynamic controls that separate microbial growth and production phases for increased efficiency and acid yield. Credit: NREL

Microbes – Carbon to chemicals

A research team led by Oak Ridge National Laboratory bioengineered a microbe to efficiently turn waste into itaconic acid, an industrial chemical used in plastics and paints.

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

ORNL’s superb materials expertise, data and AI tools propel progress

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

ORNL licenses revolutionary AI system to General Motors for automotive use

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.

Heavy-duty vehicles contribute 23% of transportation emissions of greenhouse gases and account for almost one-quarter of the fuel consumed annually in the U.S. Credit: Chris Bair/Unsplash

Heavy-duty vehicles an ideal entry into hydrogen fuel cell use

Through a consortium of Department of Energy national laboratories, ORNL scientists are applying their expertise to provide solutions that enable the commercialization of emission-free hydrogen fuel cell technology for heavy-duty