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![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.
![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.
![Picture2.png Picture2.png](/sites/default/files/styles/list_page_thumbnail/public/Picture2_1.png?itok=IV4n9XEh)
Oak Ridge National Laboratory scientists studying fuel cells as a potential alternative to internal combustion engines used sophisticated electron microscopy to investigate the benefits of replacing high-cost platinum with a lower cost, carbon-nitrogen-manganese-based catalyst.
![ORNL’s Frank Combs and Michael Starr of the U.S. Armed Forces (driver) work in ORNL’s Vehicle Security Laboratory to evaluate a prototype device that can detect network intrusions in all modern vehicles. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy ORNL’s Frank Combs and Michael Starr of the U.S. Armed Forces (driver) work in ORNL’s Vehicle Security Laboratory to evaluate a prototype device that can detect network intrusions in all modern vehicles. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/news/images/01_Cybersecurity_guarding_autonomous_vehicles.jpg?itok=qaErb8Ia)
A new Oak Ridge National Laboratory-developed method promises to protect connected and autonomous vehicles from possible network intrusion. Researchers built a prototype plug-in device designed to alert drivers of vehicle cyberattacks. The prototype is coded to learn regular timing...
![ORNL Image](/sites/default/files/styles/list_page_thumbnail/public/2017-S00094_2.jpg?itok=ZGWBnMOv)
Researchers used neutrons to probe a running engine at ORNL’s Spallation Neutron Source
![The Transforming Additive Manufacturing through Exascale Simulation project (ExaAM) is building a new multi-physics modeling and simulation platform for 3D printing of metals The Transforming Additive Manufacturing through Exascale Simulation project (ExaAM) is building a new multi-physics modeling and simulation platform for 3D printing of metals](/sites/default/files/styles/list_page_thumbnail/public/ECP%20release%20graphic%202_0.jpg?itok=JzmmCpGX)
Oak Ridge National Laboratory experts are playing leading roles in the recently established Department of Energy’s (DOE’s) Exascale Computing Project (ECP), a multi-lab initiative responsible for developing the strategy, aligning the resources, and conducting the R&D necessary to achieve the nation’s imperative of delivering exascale computing by 2021.