CYBERSECURITY – Piranha nets honor …
Piranha, an award-winning intelligent agent-based technology to analyze text data with unprecedented speed and accuracy, will be showcased at the Smithsonian’s Innovation Festival Sept. 26-27. The Oak Ridge National Laboratory technology, which received an R&D 100 Award in 2007, quickly identifies connections in documents that might be difficult or impossible for human analysts to identify. Thirteen companies, universities, government agencies and independent inventors selected by a panel will participate in the festival, which will explore how today’s inventors are changing the world. The event, a collaboration with the U.S. Patent and Trademark Office, also gives visitors a chance to learn about the patent and intellectual property systems and how they support invention and innovation. [Contact: Ron Walli, (865) 576-0226; [email protected]]
SUPERCOMPUTING – Turbocharging materials research …
Lightweight powertrain materials could play a hefty role in helping automakers meet stricter Corporate Average Fuel Economy standards, and Oak Ridge National Laboratory’s supercomputer could accelerate their deployment. Working with industry, ORNL researchers are developing materials that are lighter, affordable and able to withstand the higher temperatures and pressures of high-efficiency turbocharged engines. These engines are increasingly popular because they provide the benefit of improved fuel economy without sacrificing performance. Using Titan, the nation’s fastest computer for open science research, researchers are taking a materials genome approach to develop new cast aluminum alloys that have improved properties at much higher temperatures. “Our goal is to take high-temperature cast aluminum where it has never been,” said ORNL researcher Amit Shyam. [Contact: Ron Walli, (865) 576-0226; [email protected]]
ENERGY – Switchgrass to hydrogen …
Biorefineries could benefit from a new process developed at Oak Ridge National Laboratory that produces hydrogen from plant sources such as switchgrass. The method converts biomass waste streams into hydrogen through heating and processing in microbe-based electrochemical cells. This approach reduces the use of natural gas during biofuel production, which could help biorefineries lower their greenhouse gas emissions. “The production of renewable hydrogen from biomass is a long-sought technology for moving away from fossil fuels and toward a low-carbon economy,” said ORNL’s Abhijeet Borole. The team’s prototype set-up, which yields more than four liters of hydrogen per day, is detailed in Bioresource Technology. [Contact: Morgan McCorkle, (865) 574-7308; [email protected]]
CHEMISTY – Mining nature for pharmaceuticals …
Oak Ridge National Laboratory researchers have invented an automated droplet-based sampling probe system that scientists at the University of North Carolina at Greensboro are using for quick identification of bioactive compounds in fungi. As more medicines are identified from natural sources, screening processes become vital to the rapid discovery of new drug leads. ORNL researchers Vilmos Kertesz and Gary Van Berkel helped their university collaborators seamlessly integrate ORNL’s novel sampling technology to map unique patterns of secondary fungal metabolites in situ for addition to a library of more than 300 biological compounds. ORNL’s sampling probe system takes months off of UNCG’s traditional protocol. “The robustness and simplicity of the droplet-based sampling probe system makes it a powerful and effective tool for natural products research,” Kertesz said. – written by Ashanti B. Washington [Contact: Ron Walli, (865) 576-0226; [email protected]]
MATERIALS – Machine learning and microscopy …
A new technique developed by microscopy and computing experts at Oak Ridge National Laboratory could accelerate advances in materials science and engineering. The team’s approach combines high-performance computing and machine learning algorithms to analyze atomic-scale images and videos from electron and scanning probe microscopes. The near-real time analysis will help researchers extract more chemical and physical information from high-resolution images than previously possible. The ORNL approach focuses on automatically identifying characteristics in “atomic neighborhoods” because local patterns can define a material’s overall properties. This automated data collection lays the framework for building image genomes and libraries to support materials research and design. The team’s study is published in Nature Communications. [Contact: Morgan McCorkle, (865) 574-7308; [email protected]]
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