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forest under study in Panama

Scientists using high-resolution aerial scans and computational modeling concluded that wildfires, storms and selective logging have become key drivers behind rainforest carbon emissions, outpacing clear-cutting practices.

ORNL scientists used molecular dynamics simulations, exascale computing, lab testing and analysis to accelerate the development of an energy-saving method to produce nanocellulosic fibers.

A team led by scientists at ORNL identified and demonstrated a method to process a plant-based material called nanocellulose that reduced energy needs by a whopping 21%, using simulations on the lab’s supercomputers and follow-on analysis.

Beach to show impact of a hurricane

A study found that beaches with manmade fortifications recover more slowly from hurricanes than natural beaches, losing more sand and vegetation. The researchers used satellite images and light detection and ranging data, or LIDAR, to measure elevation changes and vegetation coverage. Changes in elevation showed how much sand was depleted during the storm and how much sand returned throughout the following year. 

The seven entrepreneurs for Cohort 2024

Seven entrepreneurs comprise the next cohort of Innovation Crossroads, a DOE Lab-Embedded Entrepreneurship Program node based at ORNL. The program provides energy-related startup founders from across the nation with access to ORNL’s unique scientific resources and capabilities, as well as connect them with experts, mentors and networks to accelerate their efforts to take their world-changing ideas to the marketplace.

The image depicts a molecule made up of 6 white balls, two smaller red balls and two larger grey balls. This molecule is against a pink, blue and purple background.

A research team led by the Department of Energy’s Oak Ridge National Laboratory demonstrated an effective and reliable new way to identify and quantify polyethylene glycols in various samples. 

Dmytro Bykov, left, and Hector Corzo participate in a value proposition development exercise as part Energy I-Corps

Two ORNL teams recently completed Cohort 18 of Energy I-Corps, an immersive two-month training program where the scientists define their technology’s value propositions, conduct stakeholder discovery interviews and develop viable market pathways.

Researcher Brittany Rodriguez works with an ORNL-developed Additive Manufacturing/Compression Molding system that 3D prints large-scale, high-volume parts made from lightweight composites. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

Brittany Rodriguez never imagined she would pursue a science career at a Department of Energy national laboratory. However, after some encouraging words from her mother, input from key mentors at the University of Texas Rio Grande Valley, or UTRGV, and a lot of hard work, Rodriguez landed at DOE’s Manufacturing Demonstration Facility, or MDF, at Oak Ridge National Laboratory.

This photo is of four men standing in front of a wall of monitors that are showing a tree looking image.

To better predict long-term flooding risk, scientists at the Department of Energy’s Oak Ridge National Laboratory developed a 3D modeling framework that captures the complex dynamics of water as it flows across the landscape. The framework seeks to provide valuable insights into which communities are most vulnerable as the climate changes, and was developed for a project that’s assessing climate risk and mitigation pathways for an urban area along the Southeast Texas coast.

Arial view of the Atchafalaya Basin

In the wet, muddy places where America’s rivers and lands meet the sea, scientists from the Department of Energy’s Oak Ridge National Laboratory are unearthing clues to better understand how these vital landscapes are evolving under climate change.

Rectangular box being lifted by a red pully system up the left side of the building

Researchers at ORNL and the University of Maine have designed and 3D-printed a single-piece, recyclable natural-material floor panel tested to be strong enough to replace construction materials like steel.