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ORNL's Communications team works with news media seeking information about the laboratory. Media may use the resources listed below or send questions to news@ornl.gov.

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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.

ORNL assisted in investigating proteins called porins, one shown in red, which are found in the protective outer membrane of certain disease-causing bacteria and tether the membrane to the cell wall. Credit: Hyea (Sunny) Hwang/Georgia Tech and ORNL, U.S. Dept. of Energy

Scientists from Oak Ridge National Laboratory used high-performance computing to create protein models that helped reveal how the outer membrane is tethered to the cell membrane in certain bacteria.

Computing – Mining for COVID-19 connections

Scientists have tapped the immense power of the Summit supercomputer at Oak Ridge National Laboratory to comb through millions of medical journal articles to identify potential vaccines, drugs and effective measures that could suppress or stop the spread of COVID-19.

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. 

ORNL’s collaboration with Cincinati Children’s Hospital Medical Center will leverage the lab’s expertise in high-performance computing and safe, secure recordkeeping. Credit: Genevieve Martin/Oak Ridge National Laboratory, U.S. Dept. of Energy

Oak Ridge National Laboratory will partner with Cincinnati Children’s Hospital Medical Center to explore ways to deploy expertise in health data science that could more quickly identify patients’ mental health risk factors and aid in suicide prevention strategies.

Smart Neighborhood homes

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.

Project bridges compute staff, resources at ORNL and VA health data to speed suicide risk screening for US veterans. Image Credit: Carlos Jones, ORNL

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. 

Galactic wind simulation

Using the Titan supercomputer at Oak Ridge National Laboratory, a team of astrophysicists created a set of galactic wind simulations of the highest resolution ever performed. The simulations will allow researchers to gather and interpret more accurate, detailed data that elucidates how galactic winds affect the formation and evolution of galaxies.

As part of a preliminary study, ORNL scientists used critical location data collected from Twitter to map the location of certain power outages across the United States.

Gleaning valuable data from social platforms such as Twitter—particularly to map out critical location information during emergencies— has become more effective and efficient thanks to Oak Ridge National Laboratory.

Researchers used machine learning methods on the ORNL Compute and Data Environment for Science, or CADES, to map vegetation communities in the Kougarok Watershed on the Seward Peninsula of Alaska. The colors denote different types of vegetation, such as w

A team of scientists led by Oak Ridge National Laboratory used machine learning methods to generate a high-resolution map of vegetation growing in the remote reaches of the Alaskan tundra.