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Media Contacts
![Oak Ridge National Laboratory entrance sign](/themes/custom/ornl/images/default-thumbnail.jpg)
The unique process of accepting a new supercomputer is one of the most challenging projects a programmer may take on during a career. When the Oak Ridge Leadership Computing Facility’s (OLCF’s) Verónica Melesse Vergara came to the United States from Ecuador in 2005, she never would have dreamed of being part of such an endeavor. But just last fall, she was.
![Neutron scattering allowed direct observation of how aurein induces lateral segregation in the bacteria membranes, which creates instability in the membrane structure. This instability causes the membranes to fail, making harmful bacteria less effective.](/sites/default/files/styles/list_page_thumbnail/public/2019-03/Neutrons-FightingSuperbugs_0.jpg?h=e4b73f5a&itok=ebOQD-Mr)
As the rise of antibiotic-resistant bacteria known as superbugs threatens public health, Oak Ridge National Laboratory’s Shuo Qian and Veerendra Sharma from the Bhaba Atomic Research Centre in India are using neutron scattering to study how an antibacterial peptide interacts with and fights harmful bacteria.
![(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.
![To develop complex materials with superior properties, Vera Bocharova uses diverse methods including broadband dielectric spectroscopy. Credit: Oak Ridge National Laboratory, U.S. Dept. of Energy; photographer Jason Richards](/sites/default/files/styles/list_page_thumbnail/public/2019-02/2016-p05202.jpg?h=b6236d98&itok=w-Sd8giq)
Vera Bocharova at the Department of Energy’s Oak Ridge National Laboratory investigates the structure and dynamics of soft materials—polymer nanocomposites, polymer electrolytes and biological macromolecules—to advance materials and technologies for energy, medicine and other applications.
![Laminations such as these are compiled to form the core of modern electric vehicle motors. ORNL has developed a software toolkit to speed the development of new motor designs and to improve the accuracy of their real-world performance.](/sites/default/files/styles/list_page_thumbnail/public/2019-02/Motors_OeRSTED_0.jpg?h=af53702d&itok=mT24R4WI)
Oak Ridge National Laboratory scientists have created open source software that scales up analysis of motor designs to run on the fastest computers available, including those accessible to outside users at the Oak Ridge Leadership Computing Facility.
OAK RIDGE, Tenn., Feb. 12, 2019—A team of researchers from the Department of Energy’s Oak Ridge and Los Alamos National Laboratories has partnered with EPB, a Chattanooga utility and telecommunications company, to demonstrate the effectiveness of metro-scale quantum key distribution (QKD).
![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 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](/sites/default/files/styles/list_page_thumbnail/public/rs2019_highlight_plot_3d.png?itok=5bROV_ys)
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.
![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.
![Coexpression_hi-res_image[1].jpg Coexpression_hi-res_image[1].jpg](/sites/default/files/styles/list_page_thumbnail/public/Coexpression_hi-res_image%5B1%5D_0.jpg?itok=OnLe-krT)
While studying the genes in poplar trees that control callus formation, scientists at Oak Ridge National Laboratory have uncovered genetic networks at the root of tumor formation in several human cancers.
![Symposium attendees represented ORNL, the University of Arizona, Georgia Tech, the University of Tennessee-Knoxville, and Brigham Young University. Symposium attendees represented ORNL, the University of Arizona, Georgia Tech, the University of Tennessee-Knoxville, and Brigham Young University.](/sites/default/files/styles/list_page_thumbnail/public/news/images/2019-P00148%5B2%5D%20r1.jpg?itok=imqhuQWL)
Quantum experts from across government and academia descended on Oak Ridge National Laboratory on Wednesday, January 16 for the lab’s first-ever Quantum Networking Symposium. The symposium’s purpose, said organizer and ORNL senior scientist Nick Peters, was to gather quantum an...