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ORNL’s particle entanglement machine is a precursor to the device that researchers at the University of Oklahoma are building, which will produce entangled quantum particles for quantum sensing to detect underground pipeline leaks. Credit: ORNL, U.S. Dept. of Energy

To minimize potential damage from underground oil and gas leaks, Oak Ridge National Laboratory is co-developing a quantum sensing system to detect pipeline leaks more quickly.

The REVISE-II modeling tool developed at ORNL supports decision-making for electric vehicle charging infrastructure development along interstate highways in support of intercity travel. Credit: Jason Richards/ORNL, U.S. Dept. of Energy

Researchers at Oak Ridge National Laboratory have developed a nationwide modeling tool to help infrastructure planners decide where and when to locate electric vehicle charging stations along interstate highways. The goal is to encourage the adoption of EVs for cross-country travel.

An algorithm developed and field-tested by ORNL researchers uses machine learning to maintain homeowners’ preferred temperatures year-round while minimizing energy costs. Credit: ORNL, U.S. Dept. of Energy

Oak Ridge National Laboratory researchers designed and field-tested an algorithm that could help homeowners maintain comfortable temperatures year-round while minimizing utility costs.

Heavy-duty vehicles contribute 23% of transportation emissions of greenhouse gases and account for almost one-quarter of the fuel consumed annually in the U.S. Credit: Chris Bair/Unsplash

Through a consortium of Department of Energy national laboratories, ORNL scientists are applying their expertise to provide solutions that enable the commercialization of emission-free hydrogen fuel cell technology for heavy-duty

Data from the ORNL Free Air CO2 Enrichment experiment were combined with observations from more than 100 other FACE sites for this analysis, which revealed new insights about the relationship between plant biomass growth and soil carbon storage. Credit: Jeff Warren/ORNL, U.S. Dept. of Energy

Oak Ridge National Laboratory was among an international team, led by Lawrence Livermore National Laboratory, who synthesized 108 elevated carbon dioxide, or CO2, experiments performed in various ecosystems to find out how much carbon is

Urban climate modeling

Researchers at Oak Ridge National Laboratory have identified a statistical relationship between the growth of cities and the spread of paved surfaces like roads and sidewalks. These impervious surfaces impede the flow of water into the ground, affecting the water cycle and, by extension, the climate.

Each point on the sphere of this visual representation of arbitrary frequency-bin qubit states corresponds to a unique quantum state, and the gray sections represent the measurement results. The zoomed-in view illustrates examples of three quantum states plotted next to their ideal targets (blue dots). Credit: Joseph Lukens/ORNL, U.S. Dept. of Energy

A team of researchers at Oak Ridge National Laboratory and Purdue University has taken an important step toward this goal by harnessing the frequency, or color, of light. Such capabilities could contribute to more practical and large-scale quantum networks exponentially more powerful and secure than the classical networks we have today.

Verónica Melesse Vergara speaks with third and fourth graders at East Side Intermediate School in Brownsville. Credit: ORNL, U.S. Dept. of Energy

Twenty-seven ORNL researchers Zoomed into 11 middle schools across Tennessee during the annual Engineers Week in February. East Tennessee schools throughout Oak Ridge and Roane, Sevier, Blount and Loudon counties participated, with three West Tennessee schools joining in.

The TRITON model provides a detailed visualization of the flooding that resulted when Hurricane Harvey stalled over Houston for four days in 2017. Credit: Mario Morales-Hernández/ORNL, U.S. Dept. of Energy

A new tool from Oak Ridge National Laboratory can help planners, emergency responders and scientists visualize how flood waters will spread for any scenario and terrain.

An X-ray CT image of a 3D-printed metal turbine blade was reconstructed using ORNL’s neural network and advanced algorithms. Credit: Amir Ziabari/ORNL, U.S. Dept. of Energy

Algorithms developed at Oak Ridge National Laboratory can greatly enhance X-ray computed tomography images of 3D-printed metal parts, resulting in more accurate, faster scans.