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Media Contacts
![Paul Brackman loads 3D-printed metal samples into a tower for examination using an X-ray CT scan in DOE’s Manufacturing Demonstration Facility at ORNL. Credit: Brittany Cramer/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2022-10/X-ray%20CT%20scan.png?h=8caed45b&itok=S3NHrWlr)
A new deep-learning framework developed at ORNL is speeding up the process of inspecting additively manufactured metal parts using X-ray computed tomography, or CT, while increasing the accuracy of the results. The reduced costs for time, labor, maintenance and energy are expected to accelerate expansion of additive manufacturing, or 3D printing.
![A simulation of the planet from the DOE Energy Exascale Earth System Model, one of the large-scale models incorporated in the Earth System Grid Federation led by DOE’s Oak Ridge, Argonne and Lawrence Livermore national laboratories. Credit: LLNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2022-10/E3SM%20nAtlHurricanesTake2.0557_trsp.png?h=4fe6ae66&itok=WSM8rX_c)
The Earth System Grid Federation, a multi-agency initiative that gathers and distributes data for top-tier projections of the Earth’s climate, is preparing a series of upgrades.
![A new online tool developed by ORNL researchers, VERIFI, provides an easy to use dashboard for plant managers to track carbon emissions produced by industrial processes. The tool also monitors energy usage and produces trend reports. Credit: ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2022-10/verifi_0.png?h=d860bbb5&itok=VxnU8Hme)
Researchers at ORNL have developed an online tool that offers industrial plants an easier way to track and download information about their energy footprint and carbon emissions.
![Oak Ridge National Laboratory’s software suite AutoBEM is being used in the architecture, city planning, real estate and home efficiency industries. Users take advantage of the suite’s energy modeling of almost all U.S. buildings. Credit: ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2022-09/autobem_0_0.jpg?h=571559ce&itok=-YDymByQ)
Two years after ORNL provided a model of nearly every building in America, commercial partners are using the tool for tasks ranging from designing energy-efficient buildings and cities to linking energy efficiency to real estate value and risk.
![Researchers used quantum Monte Carlo calculations to accurately render the structure and electronic properties of germanium selenide, a semiconducting nanomaterial. Credit: Paul Kent/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2022-09/ECP-storytip_0.png?h=e58db2e8&itok=ZzbB2Z-f)
A multi-lab research team led by ORNL's Paul Kent is developing a computer application called QMCPACK to enable precise and reliable predictions of the fundamental properties of materials critical in energy research.
![Technology Innovation Program](/sites/default/files/styles/list_page_thumbnail/public/2022-08/TIPbg_0.jpg?h=a50b7bdc&itok=_3vRlbkP)
Five technologies invented by scientists at the Department of Energy’s Oak Ridge National Laboratory have been selected for targeted investment through ORNL’s Technology Innovation Program.
![Sophie Voisin, an ORNL software engineer, was part of a team that won a 2014 R&D 100 Award for work on Intelligent Software for a Personalized Modeling of Expert Opinions, Decisions and Errors in Visual Examination Tasks. Credit: Jason Richards/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2022-08/algo-crop2.jpg?h=384d27f0&itok=qfe3b2Fx)
Cameras see the world differently than humans. Resolution, equipment, lighting, distance and atmospheric conditions can impact how a person interprets objects on a photo.
![Data from different sources are joined on platforms created by ORNL researchers to offer better information for decision makers. Credit: ORNL/Nathan Armistead](/sites/default/files/styles/list_page_thumbnail/public/2022-07/COVID%20dashboards%20story%20graphic_0.jpg?h=d1cb525d&itok=ubNOO2W4)
When the COVID-19 pandemic stunned the world in 2020, researchers at ORNL wondered how they could extend their support and help
![ORNL polymer scientists Tomonori Saito, left, and Sungjin Kim upcycled waste plastic to create a stronger, tougher, solvent-resistant material for new additive manufacturing applications. Credit: Genevieve Martin/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2022-06/2022-P04745_2.jpg?h=c6980913&itok=9DI9K-vJ)
ORNL researchers have developed an upcycling approach that adds value to discarded plastics for reuse in additive manufacturing, or 3D printing.
![Oak Ridge National Laboratory researchers developed an invertible neural network, a type of artificial intelligence that mimics the human brain, to improve accuracy in climate-change models and predictions. Credit: Getty Images](/sites/default/files/styles/list_page_thumbnail/public/2022-05/CCSD%20Neuro-climate.png?h=845c699a&itok=AJbSKZF8)
Oak Ridge National Laboratory researchers developed an invertible neural network, a type of artificial intelligence that mimics the human brain, to improve accuracy in climate-change models and predictions.