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Catherine Schuman, top right, spoke to Copper Ridge Elementary School fifth graders about her job as an ORNL computer scientist as part of the lab’s STEM outreach during the COVID-19 pandemic. Credit: Abby Bower/Oak Ridge National Laboratory, U.S. Dept. of Energy

With Tennessee schools online for the rest of the school year, researchers at ORNL are making remote learning more engaging by “Zooming” into virtual classrooms to tell students about their science and their work at a national laboratory.

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.

The image visualizes how the team’s multitask convolutional neural network classifies primary cancer sites. Image credit: Hong-Jun Yoon/ORNL

As the second-leading cause of death in the United States, cancer is a public health crisis that afflicts nearly one in two people during their lifetime.

This simulation of a fusion plasma calculation result shows the interaction of two counter-streaming beams of super-heated gas. Credit: David L. Green/Oak Ridge National Laboratory, U.S. Dept. of Energy

The prospect of simulating a fusion plasma is a step closer to reality thanks to a new computational tool developed by scientists in fusion physics, computer science and mathematics at ORNL.

The students analyzed diatom images like this one to compare wild and genetically modified strains of these organisms. Credit: Alison Pawlicki/Oak Ridge National Laboratory, US Department of Energy.

Students often participate in internships and receive formal training in their chosen career fields during college, but some pursue professional development opportunities even earlier.

Edmon Begoli

Artificial intelligence (AI) techniques have the potential to support medical decision-making, from diagnosing diseases to prescribing treatments. But to prioritize patient safety, researchers and practitioners must first ensure such methods are accurate.

International Conference on Neuromorphic Systems (ICONS)

Materials scientists, electrical engineers, computer scientists, and other members of the neuromorphic computing community from industry, academia, and government agencies gathered in downtown Knoxville July 23–25 to talk about what comes next in

Molecular dynamics simulations of the Fs-peptide revealed the presence of at least eight distinct intermediate stages during the process of protein folding. The image depicts a fully folded helix (1), various transitional forms (2–8), and one misfolded state (9). By studying these protein folding pathways, scientists hope to identify underlying factors that affect human health.

Using artificial neural networks designed to emulate the inner workings of the human brain, deep-learning algorithms deftly peruse and analyze large quantities of data. Applying this technique to science problems can help unearth historically elusive solutions.

Laminations such as these are compiled to form the core of modern electric vehicle motors. ORNL has developed a software toolkit to speed the development of new motor designs and to improve the accuracy of their real-world performance.

Oak Ridge National Laboratory scientists have created open source software that scales up analysis of motor designs to run on the fastest computers available, including those accessible to outside users at the Oak Ridge Leadership Computing Facility.

SmartTruck, a small business in Greenville, SC, recently completed its first detailed unsteady analysis using modeling and simulation at the OLCF and became the first company to request certification from the EPA through CFD. Image Credit: SmartTruck

Long-haul tractor trailers, often referred to as “18-wheelers,” transport everything from household goods to supermarket foodstuffs across the United States every year. According to the Bureau of Transportation Statistics, these trucks moved more than 10 billion tons of goods—70.6 ...