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Media Contacts
![An open-source code developed by an ORNL-led team could provide new insights into the everyday operation of the nation’s power grid. Credit: Pixabay](/sites/default/files/styles/list_page_thumbnail/public/2021-10/digitization-gef50ab16f_1920_0.jpg?h=e5aec6c8&itok=55oFYLLz)
Oak Ridge National Laboratory, University of Tennessee and University of Central Florida researchers released a new high-performance computing code designed to more efficiently examine power systems and identify electrical grid disruptions, such as
![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](/sites/default/files/styles/list_page_thumbnail/public/2021-07/IMG_20170706_154618586AK_0.jpg?h=61873cd7&itok=0OWbsNbu)
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.
![ORNL researchers are developing a method to print low-cost, high-fidelity, customizable sensors for monitoring power grid equipment. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2021-02/SAW%20sensors%202021-P01084_0.jpg?h=8f9cfe54&itok=H3Fe6A_G)
A method developed at Oak Ridge National Laboratory to print high-fidelity, passive sensors for energy applications can reduce the cost of monitoring critical power grid assets.
![Nuclear – Finally, a benchmark](/sites/default/files/styles/list_page_thumbnail/public/2020-05/67051_0.jpg?h=add82d74&itok=xR-EnPtz)
In the 1960s, Oak Ridge National Laboratory's four-year Molten Salt Reactor Experiment tested the viability of liquid fuel reactors for commercial power generation. Results from that historic experiment recently became the basis for the first-ever molten salt reactor benchmark.
![Kat Royston](/sites/default/files/styles/list_page_thumbnail/public/2020-04/Kat%20Royston%20profile_0.jpg?h=036a71b7&itok=WTyE2n4S)
As a teenager, Kat Royston had a lot of questions. Then an advanced-placement class in physics convinced her all the answers were out there.
![Smart Neighborhood homes](/sites/default/files/styles/list_page_thumbnail/public/2020-01/04.09.TD-SMartHome_0.jpg?h=5b5a5437&itok=22S5Tle1)
To better determine the potential energy cost savings among connected homes, researchers at Oak Ridge National Laboratory developed a computer simulation to more accurately compare energy use on similar weather days.
![Argon pellet injection text](/sites/default/files/styles/list_page_thumbnail/public/2019-11/13966_Ar_20degree_enhanced_0.jpg?h=8450e950&itok=tmff0GX_)
As scientists study approaches to best sustain a fusion reactor, a team led by Oak Ridge National Laboratory investigated injecting shattered argon pellets into a super-hot plasma, when needed, to protect the reactor’s interior wall from high-energy runaway electrons.
![Project bridges compute staff, resources at ORNL and VA health data to speed suicide risk screening for US veterans. Image Credit: Carlos Jones, ORNL](/sites/default/files/styles/list_page_thumbnail/public/2019-08/VA_REACHVET1%5B6%5D_0.jpg?h=173ee000&itok=-eA5t15j)
In collaboration with the Department of Veterans Affairs, a team at Oak Ridge National Laboratory has expanded a VA-developed predictive computing model to identify veterans at risk of suicide and sped it up to run 300 times faster, a gain that could profoundly affect the VA’s ability to reach susceptible veterans quickly.
![Computing—Building a brain](/sites/default/files/styles/list_page_thumbnail/public/2019-06/CADES2019-P00182_0.jpg?h=c6980913&itok=eyahnQde)
Researchers at Oak Ridge National Laboratory are taking inspiration from neural networks to create computers that mimic the human brain—a quickly growing field known as neuromorphic computing.
![Computing—Routing out the bugs](/sites/default/files/styles/list_page_thumbnail/public/2019-11/VA-HealthIT-2019-P04263.jpg?h=784bd909&itok=uwv091uK)
A study led by Oak Ridge National Laboratory explored the interface between the Department of Veterans Affairs’ healthcare data system and the data itself to detect the likelihood of errors and designed an auto-surveillance tool