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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

Celeritas code will accelerate high energy physics simulations with supercomputers

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.

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

Genetic markers for autism, hiding in plain sight

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

Seven ORNL technologies win R&D 100 research awards

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

Bobby Sumpter named fellow of Institute of Physics, International Association of Advanced Materials

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.

A smart approach to microscopy and imaging developed at Oak Ridge National Laboratory could drive discoveries in materials for future technologies. Credit: Adam Malin/ORNL, U.S. Dept. of Energy

Self-driving microscopes discover shortcuts to new materials

Researchers at ORNL are teaching microscopes to drive discoveries with an intuitive algorithm, developed at the lab’s Center for Nanophase Materials Sciences, that could guide breakthroughs in new materials for energy technologies, sensing and computing.

ORNL scientists created a new microbial trait mapping process that improves on classical protoplast fusion techniques to identify the genes that trigger desirable genetic traits like improved biomass processing. Credit: Nathan Armistead/ORNL, U.S. Dept. of Energy. Reprinted with the permission of Oxford University Press, publisher of Nucleic Acids Research

Retro technique advances modern bacterial engineering for bioenergy

ORNL scientists had a problem mapping the genomes of bacteria to better understand the origins of their physical traits and improve their function for bioenergy production.

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

Teri O’Meara: Making a splash with coastal ecology

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

Climate — Drier air

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.

A new process developed by Oak Ridge National Laboratory leverages deep learning techniques to study cell movements in a simulated environment, guided by simple physics rules similar to video-game play. Credit: MSKCC and UTK

AI — Revealing hidden biology

Scientists have developed a novel approach to computationally infer previously undetected behaviors within complex biological environments by analyzing live, time-lapsed images that show the positioning of embryonic cells in C. elegans, or roundworms. Their published methods could be used to reveal hidden biological activity. 

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.