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The Energy Exascale Earth System Model project reliably simulates aspects of earth system variability and projects decadal changes that will critically impact the U.S. energy sector in the future. A new version of the model delivers twice the performance of its predecessor. Credit: E3SM, Dept. of Energy

Updated exascale system for Earth simulations delivers twice the speed

A new version of the Energy Exascale Earth System Model, or E3SM, is two times faster than an earlier version released in 2018.

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.

Using quantum Monte Carlo methods, the researchers simulated bulk VO2. Yellow and turquoise represent changes in electron density between the excited and ground states of a compound composed of oxygen, in red, and vanadium, in blue, which allowed them to evaluate how an oxygen vacancy, in white, can alter the compound’s properties. Credit: Panchapakesan Ganesh/ORNL, U.S. Dept. of Energy

Artificially altered material could accelerate neuromorphic device development

Neuromorphic devices — which emulate the decision-making processes of the human brain — show great promise for solving pressing scientific problems, but building physical systems to realize this potential presents researchers with a significant

ORNL’s Melissa Allen-Dumas examines the ways global and regional climate models can shed light on local climate effects and inform equitable solutions. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

Melissa Allen-Dumas: Breaking down climate change, one neighborhood at a time

The world is full of “huge, gnarly problems,” as ORNL research scientist and musician Melissa Allen-Dumas puts it — no matter what line of work you’re in. That was certainly the case when she would wrestle with a tough piece of music.

Deeksha Rastogi uses high-performance computing to understand the human impacts of climate change. Credit: Carlos Jones, ORNL/U.S. Dept. of Energy

Deeksha Rastogi: Modeling climate extremes for community impact

An international problem like climate change needs solutions that cross boundaries, both on maps and among disciplines. Oak Ridge National Laboratory computational scientist Deeksha Rastogi embodies that approach.

As part of the Next-Generation Ecosystem Experiments Arctic project, scientists are gathering and incorporating new data about the Alaskan tundra into global models that predict the future of our planet. Credit: ORNL/U.S. Dept. of Energy

ORNL expertise supports latest IPCC report and efforts to understand, address climate change

Improved data, models and analyses from ORNL scientists and many other researchers in the latest global climate assessment report provide new levels of certainty about what the future holds for the planet 

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. Credit: Michelle Lehman/ORNL, U.S. Dept. of Energy

DOE scientists deploy creativity, speed to disrupt COVID-19

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.

ORNL and NASA’s Jet Propulsion Laboratory scientists studied the formation of amorphous ice like the exotic ice found in interstellar space and on Jupiter’s moon, Europa. Credit: NASA/JPL-Caltech

Neutrons – Space ice, un-Earthly cold

Researchers from NASA’s Jet Propulsion Laboratory and Oak Ridge National Laboratory successfully created amorphous ice, similar to ice in interstellar space and on icy worlds in our solar system. They documented that its disordered atomic behavior is unlike any ice on Earth.

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.

Neutron scattering experiments show electric charges, shown in red, blue and grey, in the SARS-CoV-2 main protease site where telaprevir binds to the structure. The experiments provide critical data for the design of small-molecule drugs to treat COVID-19. Credit: Jill Hemman and Michelle Lehman/ORNL, U.S. Dept. of Energy

Neutrons reveal unpredicted binding between SARS-CoV-2, hepatitis C antiviral drug

Scientists have found new, unexpected behaviors when SARS-CoV-2 – the virus that causes COVID-19 – encounters drugs known as inhibitors, which bind to certain components of the virus and block its ability to reproduce.