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Media Contacts
An Oak Ridge National Laboratory team developed a novel technique using sensors to monitor seismic and acoustic activity and machine learning to differentiate operational activities at facilities from “noise” in the recorded data.
University of Pennsylvania researchers called on computational systems biology expertise at Oak Ridge National Laboratory to analyze large datasets of single-cell RNA sequencing from skin samples afflicted with atopic dermatitis.
Scientists have developed a novel approach to computationally infer previously undetected behaviors within complex biological environments by analyzing live, time-lapsed images that show the positioning of embryonic cells in C. elegans, or roundworms. Their published methods could be used to reveal hidden biological activity.
Oak Ridge National Laboratory researchers have created a technology that more realistically emulates user activities to improve cyber testbeds and ultimately prevent cyberattacks.
Staff at Oak Ridge National Laboratory organized transport for a powerful component that is critical to the world’s largest experiment, the international ITER project.
Oak Ridge National Laboratory researchers developed and demonstrated algorithm-based controls for a hybrid electric bus that yielded up to 30% energy savings compared with existing controls.
An Oak Ridge National Laboratory researcher has invented a version of an isotope-separating device that can withstand extreme environments, including radiation and chemical solvents.
Equipment and expertise from Oak Ridge National Laboratory will allow scientists studying fusion energy and technologies to acquire crucial data during landmark fusion experiments in Europe.
A better way of welding targets for Oak Ridge National Laboratory’s plutonium-238 production has sped up the process and improved consistency and efficiency. This advancement will ultimately benefit the lab’s goal to make enough Pu-238 – the isotope that powers NASA’s deep space missions – to yield 1.5 kilograms of plutonium oxide annually by 2026.
Oak Ridge National Laboratory researchers have developed a machine learning model that could help predict the impact pandemics such as COVID-19 have on fuel demand in the United States.