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Media Contacts
![Emma Betters Thumbnail](/sites/default/files/styles/list_page_thumbnail/public/2020-10/emma%20betters_sized.jpg?h=e91a75a9&itok=k1X4xVjl)
Growing up in Florida, Emma Betters was fascinated by rockets and for good reason. Any time she wanted to see a space shuttle launch from NASA’s nearby Kennedy Space Center, all she had to do was sit on her front porch.
![3D printed EMPOWER wall drawing](/sites/default/files/styles/list_page_thumbnail/public/2020-08/EMP_WALL11.jpg?h=1d9512c1&itok=3Q-UnrTY)
Oak Ridge National Laboratory researchers used additive manufacturing to build a first-of-its kind smart wall called EMPOWER.
![Cars and coronavirus](/sites/default/files/styles/list_page_thumbnail/public/2020-08/Transportation-Gauging_pandemic_impact_ORNL_0.jpg?h=4a7d1ed4&itok=Xqx4kknO)
Oak Ridge National Laboratory researchers have developed a machine learning model that could help predict the impact pandemics such as COVID-19 have on fuel demand in the United States.
![Joe Hagerman is expanding connected neighborhood research at ORNL and envisions buildings of the future as resources capable of managing the flow and exchange of energy based on economic and market signals – a concept known as transactive energy. Credit: Carlos Jones/Oak Ridge National Laboratory, U.S. Department of Energy](/sites/default/files/styles/list_page_thumbnail/public/2020-07/2020-P08672%5B2%5D_1.jpg?h=8f9cfe54&itok=CFroD1Y2)
Joe Hagerman, ORNL research lead for buildings integration and controls, understands the impact building technology innovations can have during times of crisis. Over a decade ago, he found himself in the middle of one of the most devastating natural disasters of the century, Hurricane Katrina.
![Map with focus on sub-saharan Africa](/sites/default/files/styles/list_page_thumbnail/public/2020-07/firms3-Africa-NASA_0.jpg?h=27f1d52b&itok=G8uUS5cH)
Researchers at Oak Ridge National Laboratory developed a method that uses machine learning to predict seasonal fire risk in Africa, where half of the world’s wildfire-related carbon emissions originate.
![Computational biophysicist Ada Sedova is using experiments and high-performance computing to explore the properties of biological systems and predict their form and function, including research to accelerate drug discovery for COVID-19. Photo credit: Jason Richards, Oak Ridge National Laboratory, U.S. Dept. of Energy.](/sites/default/files/styles/list_page_thumbnail/public/2020-07/2017-P06162Cropped.jpg?h=f1d4573a&itok=TrvR_opt)
Ada Sedova’s journey to Oak Ridge National Laboratory has taken her on the path from pre-med studies in college to an accelerated graduate career in mathematics and biophysics and now to the intersection of computational science and biology
![GIS – LandScan goes public](/sites/default/files/styles/list_page_thumbnail/public/2020-05/sanfran%20%281%29_2.png?h=ea18fbc4&itok=c_VbFqAC)
Oak Ridge National Laboratory’s high-resolution population distribution database, LandScan USA, became permanently available to researchers in time to aid the response to the novel coronavirus pandemic.
![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](/sites/default/files/styles/list_page_thumbnail/public/2020-02/Puerto_Rico_Resflow9.png?h=a0a1befd&itok=5n2fss_e)
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.
![Peter Wang](/sites/default/files/styles/list_page_thumbnail/public/2020-01/2019-P18026_0.jpg?h=8f9cfe54&itok=_gPTJOy-)
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.
![Shown here is a computer-aided design of the hot stamping die with visible cooling channels. Credit: Oak Ridge National Laboratory, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2019-11/Built-to-last.png?h=a86e7ddf&itok=3DoSQK7P)
Researchers demonstrated that an additively manufactured hot stamping die can withstand up to 25,000 usage cycles, proving that this technique is a viable solution for production.