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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.

ORNL scientists are combining their expertise in environmental science, physics, sensors and additive manufacturing to create model fish for use in testing of hydropower turbine designs. The project supports healthy ecosystems and hydropower—the nation’s largest renewable energy resource. Photo credit: Oak Ridge National Laboratory, U.S. Dept. of Energy.

Hydropower developers must consider many factors when it comes time to license a new project or renew an existing one: How can environmental impacts be mitigated, including to fish populations?

Scientists created a novel polymer that is as effective as natural proteins in transporting protons through a membrane. Credit: ORNL/Jill Hemman

Biological membranes, such as the “walls” of most types of living cells, primarily consist of a double layer of lipids, or “lipid bilayer,” that forms the structure, and a variety of embedded and attached proteins with highly specialized functions, including proteins that rapidly and selectively transport ions and molecules in and out of the cell.

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.

Edge computing is both dependent on and greatly influencing a host of promising technologies including (clockwise from top left): quantum computing; high-performance computing; neuromorphic computing; and carbon nanotubes.

We have a data problem. Humanity is now generating more data than it can handle; more sensors, smartphones, and devices of all types are coming online every day and contributing to the ever-growing global dataset.

Examples from the ORNL Overhead Vehicle Dataset, generated with images captured by GRIDSMART cameras. Image: Thomas Karnowski/ORNL

Each year, approximately 6 billion gallons of fuel are wasted as vehicles wait at stop lights or sit in dense traffic with engines idling, according to US Department of Energy estimates.

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.

A new computational approach by ORNL can more quickly scan large-scale satellite images, such as these of Puerto Rico, for more accurate mapping of complex infrastructure like buildings. Credit: Maxar Technologies and Dalton Lunga/Oak Ridge National Laboratory, U.S. Dept. of Energy

A novel approach developed by scientists at ORNL can scan massive datasets of large-scale satellite images to more accurately map infrastructure – such as buildings and roads – in hours versus days. 

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.

Peter Wang

Peter Wang is focused on robotics and automation at the Department of Energy’s Manufacturing Demonstration Facility at ORNL, working on high-profile projects such as the MedUSA, a large-scale hybrid additive manufacturing machine.