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Media Contacts
![ORNL collaborator Hsiu-Wen Wang led the neutron scattering experiments at the Spallation Neutron Source to probe complex electrolyte solutions that challenge nuclear waste processing at Hanford and other sites. Credit: Genevieve Martin/Oak Ridge National Laboratory, U.S. Dept. of Energy.](/sites/default/files/styles/list_page_thumbnail/public/2019-05/2019-P01240_0.jpg?h=c6980913&itok=RLLi1M-g)
Researchers at the Department of Energy’s Oak Ridge National Laboratory, Pacific Northwest National Laboratory and Washington State University teamed up to investigate the complex dynamics of low-water liquids that challenge nuclear waste processing at federal cleanup sites.
![Using artificial intelligence, Oak Ridge National Laboratory analyzed data from published medical studies to reveal the potential of direct and indirect impacts of bullying.](/sites/default/files/styles/list_page_thumbnail/public/2019-04/bullying_img.png?h=48484608&itok=zxX54Jz1)
Oak Ridge National Laboratory is using artificial intelligence to analyze data from published medical studies associated with bullying to reveal the potential of broader impacts, such as mental illness or disease.
![Desalination diagram](/sites/default/files/styles/list_page_thumbnail/public/2019-04/DesalDiagram-_0.jpg?h=d4f5ec8a&itok=-yhECJ4V)
A team of scientists led by Oak Ridge National Laboratory used carbon nanotubes to improve a desalination process that attracts and removes ionic compounds such as salt from water using charged electrodes.
![Molecular dynamics simulations of the Fs-peptide revealed the presence of at least eight distinct intermediate stages during the process of protein folding. The image depicts a fully folded helix (1), various transitional forms (2–8), and one misfolded state (9). By studying these protein folding pathways, scientists hope to identify underlying factors that affect human health.](/sites/default/files/styles/list_page_thumbnail/public/2019-03/Slide1_0.png?h=c855054e&itok=aNbgxXsc)
Using artificial neural networks designed to emulate the inner workings of the human brain, deep-learning algorithms deftly peruse and analyze large quantities of data. Applying this technique to science problems can help unearth historically elusive solutions.
![ORNL-led collaboration solves a beta-decay puzzle with advanced nuclear models](/sites/default/files/styles/list_page_thumbnail/public/2019-03/decay_coverSize_4%5B21%5D_0.jpg?h=843037ec&itok=BU6x1GD8)
OAK RIDGE, Tenn., March 11, 2019—An international collaboration including scientists at the Department of Energy’s Oak Ridge National Laboratory solved a 50-year-old puzzle that explains why beta decays of atomic nuclei
![(From left) ORNL Associate Laboratory Director for Computing and Computational Sciences Jeff Nichols; ORNL Health Data Sciences Institute Director Gina Tourassi; DOE Deputy Under Secretary for Science Thomas Cubbage; ORNL Task Lead for Biostatistics Blair Christian; and ORNL Research Scientist Ioana Danciu were invited to the White House to showcase an ORNL-developed digital tool aimed at better matching cancer patients with clinical trials.](/sites/default/files/styles/list_page_thumbnail/public/2019-03/TourassiWH%5B1%5D.png?h=26b5064d&itok=HUC2iYmE)
OAK RIDGE, Tenn., March 4, 2019—A team of researchers from the Department of Energy’s Oak Ridge National Laboratory Health Data Sciences Institute have harnessed the power of artificial intelligence to better match cancer patients with clinical trials.
![ORNL astrophysicist Raph Hix models the inner workings of supernovae on the world’s most powerful supercomputers.](/sites/default/files/styles/list_page_thumbnail/public/2019-02/hix1.jpg?h=d1cb525d&itok=qCY4BdN6)
More than 1800 years ago, Chinese astronomers puzzled over the sudden appearance of a bright “guest star” in the sky, unaware that they were witnessing the cosmic forge of a supernova, an event repeated countless times scattered across the universe.
![ORNL scientists used commuting behavior data from East Tennessee to demonstrate how machine learning models can easily accept new data, quickly re-train themselves and update predictions about commuting patterns. Credit: April Morton/Oak Ridge National La ORNL scientists used commuting behavior data from East Tennessee to demonstrate how machine learning models can easily accept new data, quickly re-train themselves and update predictions about commuting patterns. Credit: April Morton/Oak Ridge National La](/sites/default/files/styles/list_page_thumbnail/public/study_area_one_dest_2.jpg?itok=2cWFkQvW)
Oak Ridge National Laboratory geospatial scientists who study the movement of people are using advanced machine learning methods to better predict home-to-work commuting patterns.
![mirrorAsymmetry-NPDGamma_ORNL.jpg mirrorAsymmetry-NPDGamma_ORNL.jpg](/sites/default/files/styles/list_page_thumbnail/public/mirrorAsymmetry-NPDGamma_ORNL.jpg?itok=POtcSu48)
A team of scientists has for the first time measured the elusive weak interaction between protons and neutrons in the nucleus of an atom. They had chosen the simplest nucleus consisting of one neutron and one proton for the study.
![Leah Broussard leads a study of neutron decay to understand correlations between electrons and antineutrinos as well as subtle distortions in the electron energy spectrum.](/sites/default/files/styles/list_page_thumbnail/public/IMAGE%201_%202018-P08260_0.jpg?h=65b96206&itok=sitguWk-)
Leah Broussard, a physicist at the Department of Energy’s Oak Ridge National Laboratory, has so much fun exploring the neutron that she alternates between calling it her “laboratory” and “playground” for understanding the universe. “The neutron is special,” she said of the sub...