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![ORNL alanine_graphic.jpg ORNL alanine_graphic.jpg](/sites/default/files/styles/list_page_thumbnail/public/ORNL%20alanine_graphic.jpg?itok=iRLfcOw-)
OAK RIDGE, Tenn., Jan. 31, 2019—A new electron microscopy technique that detects the subtle changes in the weight of proteins at the nanoscale—while keeping the sample intact—could open a new pathway for deeper, more comprehensive studies of the basic building blocks of life.
![Two neutron diffraction experiments (represented by pink and blue neutron beams) probed a salty solution to reveal its atomic structure. The only difference between the experiments was the identity of the oxygen isotope (O*) that labeled nitrate molecules Two neutron diffraction experiments (represented by pink and blue neutron beams) probed a salty solution to reveal its atomic structure. The only difference between the experiments was the identity of the oxygen isotope (O*) that labeled nitrate molecules](/sites/default/files/styles/list_page_thumbnail/public/news/images/ORNL%202018-G01254-AM-01.jpg?itok=WXkmqIs1)
Scientists at the Department of Energy’s Oak Ridge National Laboratory used neutrons, isotopes and simulations to “see” the atomic structure of a saturated solution and found evidence supporting one of two competing hypotheses about how ions come
![Radiochemical technicians David Denton and Karen Murphy use hot cell manipulators at Oak Ridge National Laboratory during the production of actinium-227. Radiochemical technicians David Denton and Karen Murphy use hot cell manipulators at Oak Ridge National Laboratory during the production of actinium-227.](/sites/default/files/styles/list_page_thumbnail/public/2016-P07827%5B1%5D.jpg?itok=yJbnFQLU)
The Department of Energy’s Oak Ridge National Laboratory is now producing actinium-227 (Ac-227) to meet projected demand for a highly effective cancer drug through a 10-year contract between the U.S. DOE Isotope Program and Bayer.
![ORNL’s Steven Young (left) and Travis Johnston used Titan to prove the design and training of deep learning networks could be greatly accelerated with a capable computing system. ORNL’s Steven Young (left) and Travis Johnston used Titan to prove the design and training of deep learning networks could be greatly accelerated with a capable computing system.](/sites/default/files/styles/list_page_thumbnail/public/news/images/RAvENNA%20release%20pic.png?itok=2bDpK5Mo)
A team of researchers from the Department of Energy’s Oak Ridge National Laboratory has married artificial intelligence and high-performance computing to achieve a peak speed of 20 petaflops in the generation and training of deep learning networks on the