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Marthi receives IEEE senior member honor
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Keeping aging structures safe
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Building energy around changing climate

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

ORNL researchers develop ‘multitasking’ AI tool to extract cancer data in record time

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.

ORNL’s collaboration with Cincinati Children’s Hospital Medical Center will leverage the lab’s expertise in high-performance computing and safe, secure recordkeeping. Credit: Genevieve Martin/Oak Ridge National Laboratory, U.S. Dept. of Energy

Computing – Assessing mental health

Oak Ridge National Laboratory will partner with Cincinnati Children’s Hospital Medical Center to explore ways to deploy expertise in health data science that could more quickly identify patients’ mental health risk factors and aid in

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

Fusion – Squeezing the code

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.

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.

Modified deep-learning algorithms unveil features of shape-shifting proteins

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.