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![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.
![ORNL researchers are developing a method to print low-cost, high-fidelity, customizable sensors for monitoring power grid equipment. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2021-02/SAW%20sensors%202021-P01084_0.jpg?h=8f9cfe54&itok=H3Fe6A_G)
A method developed at Oak Ridge National Laboratory to print high-fidelity, passive sensors for energy applications can reduce the cost of monitoring critical power grid assets.
![Buildings—Reaching the boiling point](/sites/default/files/styles/list_page_thumbnail/public/2019-10/Open_cell_metal_foam_ORNL.jpg?h=6e4c3ffa&itok=EvkucSnf)
Researchers at Oak Ridge National Laboratory demonstrated that metal foam enhances the evaporation process in thermal conversion systems and enables the development of compact HVAC&R units.