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![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.
![Using as much as 50 percent lignin by weight, a new composite material created at ORNL is well suited for use in 3D printing. Using as much as 50 percent lignin by weight, a new composite material created at ORNL is well suited for use in 3D printing.](/sites/default/files/styles/list_page_thumbnail/public/2018-P09551.jpg?itok=q7Ri01Qb)
Scientists at the Department of Energy’s Oak Ridge National Laboratory have created a recipe for a renewable 3D printing feedstock that could spur a profitable new use for an intractable biorefinery byproduct: lignin.
![OAK RIDGE, Tenn., Nov. 27, 2018—The Spallation Neutron Source at the Department of Energy’s Oak Ridge National Laboratory has broken a new record by ending its first neutron production cycle in fiscal year 2019 at its design power level of 1.4 megawatts. OAK RIDGE, Tenn., Nov. 27, 2018—The Spallation Neutron Source at the Department of Energy’s Oak Ridge National Laboratory has broken a new record by ending its first neutron production cycle in fiscal year 2019 at its design power level of 1.4 megawatts.](/sites/default/files/styles/list_page_thumbnail/public/news/images/2015-P05970%5B7%5D.jpg?itok=MK35c7c-)
The Spallation Neutron Source at the Department of Energy’s Oak Ridge National Laboratory has broken a new record by ending its first neutron production cycle in fiscal year 2019 at its design power level of 1.4 megawatts.
![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