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A structural model of HgcA, shown in cyan, and HgcB, shown in purple, were created using metagenomic techniques to better understand the transformation of mercury into its toxic form, methylmercury. Photo credit: Connor Cooper/ORNL, U.S. Dept of Energy

A team led by ORNL created a computational model of the proteins responsible for the transformation of mercury to toxic methylmercury, marking a step forward in understanding how the reaction occurs and how mercury cycles through the environment.

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.

The hybrid inverter developed by ORNL is an intelligent power electronic inverter platform that can connect locally sited energy resources such as solar panels, energy storage and electric vehicles and interact efficiently with the utility power grid. Credit: Carlos Jones, ORNL/U.S. Dept of Energy.

ORNL researchers have developed an intelligent power electronic inverter platform that can connect locally sited energy resources such as solar panels, energy storage and electric vehicles and smoothly interact with the utility power grid.

The CrossVis application includes a parallel coordinates plot (left), a tiled image view (right) and other interactive data views. Credit: Chad Steed/Oak Ridge National Laboratory, U.S. Dept. of Energy

From materials science and earth system modeling to quantum information science and cybersecurity, experts in many fields run simulations and conduct experiments to collect the abundance of data necessary for scientific progress.

Map with focus on sub-saharan Africa

Researchers at Oak Ridge National Laboratory developed a method that uses machine learning to predict seasonal fire risk in Africa, where half of the world’s wildfire-related carbon emissions originate.

Computational biophysicist Ada Sedova is using experiments and high-performance computing to explore the properties of biological systems and predict their form and function, including research to accelerate drug discovery for COVID-19. Photo credit: Jason Richards, Oak Ridge National Laboratory, U.S. Dept. of Energy.

Ada Sedova’s journey to Oak Ridge National Laboratory has taken her on the path from pre-med studies in college to an accelerated graduate career in mathematics and biophysics and now to the intersection of computational science and biology

Coronavirus graphic

In the race to identify solutions to the COVID-19 pandemic, researchers at the Department of Energy’s Oak Ridge National Laboratory are joining the fight by applying expertise in computational science, advanced manufacturing, data science and neutron science.

Starch granules

Scientists at the Department of Energy’s Oak Ridge National Laboratory have developed a new method to peer deep into the nanostructure of biomaterials without damaging the sample. This novel technique can confirm structural features in starch, a carbohydrate important in biofuel production.

ORNL-developed cryogenic memory cell circuit designs fabricated onto these small chips by SeeQC, a superconducting technology company, successfully demonstrated read, write and reset memory functions. Credit: Carlos Jones/Oak Ridge National Laboratory, U.S. Dept. of Energy

Scientists at have experimentally demonstrated a novel cryogenic, or low temperature, memory cell circuit design based on coupled arrays of Josephson junctions, a technology that may be faster and more energy efficient than existing memory devices.

Smart Neighborhood homes

To better determine the potential energy cost savings among connected homes, researchers at Oak Ridge National Laboratory developed a computer simulation to more accurately compare energy use on similar weather days.