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Media Contacts
![SPRUCE experiment](/sites/default/files/styles/list_page_thumbnail/public/2020-08/SPRUCE_0.png?h=9afda364&itok=zCibJUsI)
Oak Ridge National Laboratory scientists evaluating northern peatland responses to environmental change recorded extraordinary fine-root growth with increasing temperatures, indicating that this previously hidden belowground mechanism may play an important role in how carbon-rich peatlands respond to warming.
![ORNL’s Lab-on-a-crystal uses machine learning to correlate materials’ mechanical, optical and electrical responses to dynamic environments. Credit: Ilia Ivanov/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2020-08/lab_on_crystal2_0.png?h=bc215d7c&itok=5Zsjkf9e)
An all-in-one experimental platform developed at Oak Ridge National Laboratory’s Center for Nanophase Materials Sciences accelerates research on promising materials for future technologies.
![Using the ASGarD mathematical framework, scientists can model and visualize the electric fields, shown as arrows, circling around magnetic fields that are colorized to represent field magnitude of a fusion plasma. Credit: David Green/ORNL](/sites/default/files/styles/list_page_thumbnail/public/2020-08/Max1_t5e-1_EB_0.png?h=35bae166&itok=iRtx2TVM)
Combining expertise in physics, applied math and computing, Oak Ridge National Laboratory scientists are expanding the possibilities for simulating electromagnetic fields that underpin phenomena in materials design and telecommunications.
![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.
![The CrossVis application includes a parallel coordinates plot (left), a tiled image view (right) and other interactive data views. Credit: Chad Steed/Oak Ridge National Laboratory, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2020-07/CrossVisOverview_2.png?h=fd2b4cf7&itok=Mz8wRoMo)
From materials science and earth system modeling to quantum information science and cybersecurity, experts in many fields run simulations and conduct experiments to collect the abundance of data necessary for scientific progress.
![Drone shot above SPRUCE enclosure](/sites/default/files/styles/list_page_thumbnail/public/2020-07/P20_Drone_YUN00190_0.jpg?h=fe23bcc2&itok=PwOXZq1F)
Scientists at Oak Ridge National Laboratory have demonstrated a direct relationship between climate warming and carbon loss in a peatland ecosystem.
![Sergei Kalinin](/sites/default/files/styles/list_page_thumbnail/public/2020-07/2019-P00126_0.png?h=5969a3b5&itok=66cucDCt)
Five researchers at the Department of Energy’s Oak Ridge National Laboratory have been named ORNL Corporate Fellows in recognition of significant career accomplishments and continued leadership in their scientific fields.
![An organic solvent and water separate and form nanoclusters on the hydrophobic and hydrophilic sections of plant material, driving the efficient deconstruction of biomass. Credit: Michelle Lehman/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2020-07/THF_high_res.gif?h=5a472534&itok=5peedFnF)
Scientists at ORNL used neutron scattering and supercomputing to better understand how an organic solvent and water work together to break down plant biomass, creating a pathway to significantly improve the production of renewable
![Burak Ozpineci](/sites/default/files/styles/list_page_thumbnail/public/2020-07/2016-P07072_0.jpg?h=a31ffb6c&itok=dsHTBEvN)
Burak Ozpineci of the Electrical and Electronics Systems Research Division at Oak Ridge National Laboratory has won the 2020 IEEE Power Electronics Society Vehicle and Transportation Systems Achievement Award.
![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.