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This newly manufactured fixed guide vane of a hydropower turbine system was printed at the DOE Manufacturing Demonstration Facility at ORNL. Credit: Genevieve Martin/ORNL, U.S Dept. of Energy

A new report published by ORNL assessed how advanced manufacturing and materials, such as 3D printing and novel component coatings, could offer solutions to modernize the existing fleet and design new approaches to hydropower.

Researchers found that moderate levels of ash — sometimes found as spheres in biomass — do not significantly affect the mechanical properties of biocomposites made up of corn stover, switchgrass and PLA thermoplastic. Credit: Andy Sproles/ORNL, U.S. Dept. of Energy

The presence of minerals called ash in plants makes little difference to the fitness of new naturally derived compound materials designed for additive manufacturing, an Oak Ridge National Laboratory-led team found.

A new process developed by Oak Ridge National Laboratory leverages deep learning techniques to study cell movements in a simulated environment, guided by simple physics rules similar to video-game play. Credit: MSKCC and UTK

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. 

Data collection instruments at the North Pole

Researchers at Oak Ridge National Laboratory were part of an international team that collected a treasure trove of data measuring precipitation, air particles, cloud patterns and the exchange of energy between the atmosphere and the sea ice.

Quantum—Widening the net

Scientists at Oak Ridge National Laboratory studying quantum communications have discovered a more practical way to share secret messages among three parties, which could ultimately lead to better cybersecurity for the electric grid 

Computing—Routing out the bugs

A study led by Oak Ridge National Laboratory explored the interface between the Department of Veterans Affairs’ healthcare data system and the data itself to detect the likelihood of errors and designed an auto-surveillance tool