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Climate change often comes down to how it affects water, whether it’s for drinking, electricity generation, or how flooding affects people and infrastructure. To better understand these impacts, ORNL water resources engineer Sudershan Gangrade is integrating knowledge ranging from large-scale climate projections to local meteorology and hydrology and using high-performance computing to create a holistic view of the future.

Climate change often comes down to how it affects water, whether it’s for drinking, electricity generation, or how flooding affects people and infrastructure. To better understand these impacts, ORNL water resources engineer Sudershan Gangrade is integrating knowledge ranging from large-scale climate projections to local meteorology and hydrology and using high-performance computing to create a holistic view of the future.

Initially, Celeritas will accelerate simulation of data from the Compact Muon Solenoid detector (shown schematically) at CERN’s Large Hadron Collider. Credit: Seth Johnson/ORNL, U.S. Dept. of Energy

Scientists at the Department of Energy’s Oak Ridge National Laboratory are leading a new project to ensure that the fastest supercomputers can keep up with big data from high energy physics research.

When an electron beam drills holes in heated graphene, single-atom vacancies, shown in purple, diffuse until they join with other vacancies to form stationary structures and chains, shown in blue. Credit: Ondrej Dyck/ORNL, U.S. Dept. of Energy

Oak Ridge National Laboratory researchers serendipitously discovered when they automated the beam of an electron microscope to precisely drill holes in the atomically thin lattice of graphene, the drilled holes closed up.

ORNL researchers led by Michael Garvin, left, and David Kainer discovered genetic mutations called structural variants and linked them to autism spectrum disorders, demonstrating an approach that could be used to develop better diagnostics and drug therapies. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

ORNL researchers discovered genetic mutations that underlie autism using a new approach that could lead to better diagnostics and drug therapies.

ORNL’s RapidCure improves lithium-ion electrode production by producing electrodes faster, reducing the energy necessary for manufacturing and eliminating the need for a solvent recycling unit. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

Researchers at the Department of Energy’s Oak Ridge National Laboratory and their technologies have received seven 2022 R&D 100 Awards, plus special recognition for a battery-related green technology product.

Bobby Sumpter. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

ORNL Corporate Fellow and Center for Nanophase Materials Sciences researcher Bobby Sumpter has been named fellow of two scientific professional societies: the Institute of Physics and the International Association of Advanced Materials.

Magnetic quantum material broadens platform for probing next-gen information technologies

Scientists at ORNL used neutron scattering to determine whether a specific material’s atomic structure could host a novel state of matter called a spiral spin liquid.

ORNL biogeochemist Teri O’Meara is focused on improving how coastal systems are represented in global climate models, enabling better predictions about the future of these critical ecosystems. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

Surrounded by the mountains of landlocked Tennessee, Oak Ridge National Laboratory’s Teri O’Meara is focused on understanding the future of the vitally important ecosystems lining the nation’s coasts.

Results show change in annual aridity for the years 2071-2100 compared to 1985-2014. Brown shadings (negative numbers) indicate drier conditions. Black dots indicate statistical significance at the 90% confidence level. Credit: Jiafu Mao/ORNL, U.S. Dept. of Energy

A new analysis from Oak Ridge National Laboratory shows that intensified aridity, or drier atmospheric conditions, is caused by human-driven increases in greenhouse gas emissions. The findings point to an opportunity to address and potentially reverse the trend by reducing emissions.

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

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.