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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.

Ben Betzler, a reactor physics nuclear engineer at Oak Ridge National Laboratory.

As a reactor physics nuclear engineer, Ben Betzler leverages and develops computational methods to solve questions across nuclear energy—whether it’s finding the best design of a reactor core or repurposing an old tool for a new analysis.

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.

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.

Chris Ellis is applying his expertise in computational biology and microbiology to explore the human and soil microbiomes for clues to degenerative brain disease, as well as pathways to improved bioenergy crops.

After several years in the private sector exploring the unknown origins of neurodegenerative brain disorders such as Alzheimer’s, Chris Ellis thinks one of the keys to solving the mystery is at Oak Ridge National Laboratory: the world’s most powerful supercomputer.

microscope lens and lithium battery prototype

The formation of lithium dendrites is still a mystery, but materials engineers study the conditions that enable dendrites and how to stop them.

Researchers in ORNL’s Quantum Information Science group summarized their significant contributions to quantum networking and quantum computing in a special issue of Optics & Photonics News. Image credit: Christopher Tison and Michael Fanto/Air Force Research Laboratory.

A team from the ORNL has conducted a series of experiments to gain a better understanding of quantum mechanics and pursue advances in quantum networking and quantum computing, which could lead to practical applications in cybersecurity and other areas.

Scanning probe microscopes use an atom-sharp tip—only a few nanometers thick—to image materials on a nanometer length scale. The probe tip, invisible to the eye, is attached to a cantilever (pictured) that moves across material surfaces like the tone arm on a record player. Credit: Genevieve Martin/Oak Ridge National Laboratory; U.S. Dept. of Energy.

Liam Collins was drawn to study physics to understand “hidden things” and honed his expertise in microscopy so that he could bring them to light.

The lithium-aluminum-layered double hydroxide chloride (LDH) sorbent being developed by ORNL targets recovery of lithium from geothermal brines—paving the way for increased domestic production of the material for today’s rechargeable batteries. Credit: Oak Ridge National Laboratory

In the quest for domestic sources of lithium to meet growing demand for battery production, scientists at ORNL are advancing a sorbent that can be used to more efficiently recover the material from brine wastes at geothermal power plants.