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Alex Roschli in front of BAAM

Alex Roschli is no stranger to finding himself in unique situations. After all, the early career researcher in ORNL’s Manufacturing Systems Research group bears a last name that only 29 other people share in the United States, and he’s certain he’s the only Roschli (a moniker that hails from Switzerland) with the first name Alex.

The concrete parts are installed in a residential and commercial tower (above center and below) on the site of the Domino Sugar Factory along the waterfront in Brooklyn. Windows in the tower resemble sugar crystals. Image credit: Gate Precast

A residential and commercial tower under development in Brooklyn that is changing the New York City skyline has its roots in research at the Department of Energy’s Oak Ridge National Laboratory.

Transportation Energy Data Book Edition 37

Oak Ridge National Laboratory’s latest Transportation Energy Data Book: Edition 37 reports that the number of vehicles nationwide is growing faster than the population, with sales more than 17 million since 2015, and the average household vehicle travels more than 11,000 miles per year.

As part of a preliminary study, ORNL scientists used critical location data collected from Twitter to map the location of certain power outages across the United States.

Gleaning valuable data from social platforms such as Twitter—particularly to map out critical location information during emergencies— has become more effective and efficient thanks to Oak Ridge National Laboratory.

Laminations such as these are compiled to form the core of modern electric vehicle motors. ORNL has developed a software toolkit to speed the development of new motor designs and to improve the accuracy of their real-world performance.

Oak Ridge National Laboratory scientists have created open source software that scales up analysis of motor designs to run on the fastest computers available, including those accessible to outside users at the Oak Ridge Leadership Computing Facility.

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

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.

Symposium attendees represented ORNL, the University of Arizona, Georgia Tech, the University of Tennessee-Knoxville, and Brigham Young University.

Quantum experts from across government and academia descended on Oak Ridge National Laboratory on Wednesday, January 16 for the lab’s first-ever Quantum Networking Symposium. The symposium’s purpose, said organizer and ORNL senior scientist Nick Peters, was to gather quantum an...

Nuclear—Deep space travel

By automating the production of neptunium oxide-aluminum pellets, Oak Ridge National Laboratory scientists have eliminated a key bottleneck when producing plutonium-238 used by NASA to fuel deep space exploration.

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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.