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Media Contacts
![Watermarks, considered the most efficient mechanisms for tracking how complete streaming data processing is, allow new tasks to be processed immediately after prior tasks are completed. Image Credit: Nathan Armistead, ORNL](/sites/default/files/styles/list_page_thumbnail/public/2021-11/Watermarks%5B1%5D.jpg?h=f7cc716d&itok=Er5k0WwK)
A team of collaborators from ORNL, Google Inc., Snowflake Inc. and Ververica GmbH has tested a computing concept that could help speed up real-time processing of data that stream on mobile and other electronic devices.
![A new tool that simulates the energy profile of every building in America will give homeowners, utilities and companies a quick way to determine energy use and cost-effective retrofits that can reduce energy and carbon emissions.](/sites/default/files/styles/list_page_thumbnail/public/2021-08/VirtualEPB_map_models_0.jpg?h=0c7f5a21&itok=rRhlQQ4F)
A new tool that simulates the energy profile of every building in America will give homeowners, utilities and companies a quick way to determine energy use and cost-effective retrofits that can reduce energy and carbon emissions.
![An algorithm developed and field-tested by ORNL researchers uses machine learning to maintain homeowners’ preferred temperatures year-round while minimizing energy costs. Credit: ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2021-07/2019-P07408_2.jpg?h=8f9cfe54&itok=jBvKdqIv)
Oak Ridge National Laboratory researchers designed and field-tested an algorithm that could help homeowners maintain comfortable temperatures year-round while minimizing utility costs.
![Innovation Crossroads Cohort 5 includes left to right: Caleb Alexander, DayLyte Batteries; Sam Evans, Unbound Water Technologies; Tommy Gibbons, Hempitecture; Shuchi “SK” Khurana, Addiguru; Forrest Shriver, Sentinel Devices; and Philip Stuckey, FC Renew.](/sites/default/files/styles/list_page_thumbnail/public/2021-06/Cohort5_comp.jpg?h=bfc3df63&itok=GvY2BEKg)
Six science and technology innovators from across the United States will join the fifth cohort of Oak Ridge National Laboratory’s Innovation Crossroads program in June.
![ORNL researchers developed an innovative insulation system that uses sensors and controls to exchange heat or coolness between a building and its thermal energy storage system, which maximizes energy savings. Credit: Andrew Sproles and Michelle Lehman/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2021-06/wall_drop_0.jpg?h=31aa1c7b&itok=-ORCW5_u)
Researchers at Oak Ridge National Laboratory have developed a novel envelope system that diverts heat or coolness away from a building and stores it for future use.
![ORNL’s non-disruptive air leak detector captures air escaping from exterior walls and uses refractive imaging to calculate the leakage flow rate. Credit: ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2021-05/EnZUYVxI_0.jpeg?h=dfc3be9e&itok=IohEfqiW)
A team of researchers at Oak Ridge National Laboratory has developed a method to detect and measure air leaking from a building’s walls and roof that is quicker, cheaper and less disruptive to occupants.
![ORNL researchers used fiber reinforcements made of steel, glass and carbon to develop a concrete mix that demonstrated high early strength within six hours of production, which is needed for the precast concrete industry. Credit: ORNL/U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2021-03/fibers01_0.jpg?h=4885e843&itok=k7L8OLxP)
A team of researchers at Oak Ridge National Laboratory and the University of Tennessee have developed a concrete mix that demonstrated high early strength within six hours of mixing, potentially doubling the production capacity for the precast industry.
![Xin Sun](/sites/default/files/styles/list_page_thumbnail/public/2021-03/2018-P07541.jpg?h=49ab6177&itok=d9DdBp0M)
Xin Sun has been selected as the associate laboratory director for the Energy Science and Technology Directorate, or ESTD, at the Department of Energy’s Oak Ridge National Laboratory.
![An X-ray CT image of a 3D-printed metal turbine blade was reconstructed using ORNL’s neural network and advanced algorithms. Credit: Amir Ziabari/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2021-01/Manufacturing%20-%20Defect%20detection%202_0.jpg?h=259e5a75&itok=CwpLQv6U)
Algorithms developed at Oak Ridge National Laboratory can greatly enhance X-ray computed tomography images of 3D-printed metal parts, resulting in more accurate, faster scans.