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Five Argonne technologies named finalists in the 2018 R&D 100 Awards

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Five Argonne National Laboratory entries to the R&D 100 Awards, long considered the “Oscars” of scientific innovation, have been named finalists.

The elite competition, sponsored by R&D Magazine, recognizes the 100 most innovative technologies of the previous year. Winning projects have included sophisticated testing equipment; innovative new materials; disruptive chemistry breakthroughs; new biomedical products; breakthrough consumer products and new technologies spanning industry, academia and government.

A total of 130 R&D 100 Awards have gone to Argonne scientists since the competition began in 1964.

This year’s entries include:

Kirill Prozument (CSE) of the RAINet team. Not pictured from the RAINet team is Daniel Zaleski.

Automated Assignment of Rotational Spectra Using Artificial Neural Networks (RAINet) by Kirill Prozument (CSE) and Daniel Zaleski

RAINet is an artificial neural network that automatically identifies the physical parameters of molecules in the gas phase by their rotational spectra. Compared with mass spectrometry, rotational spectroscopy conveys richer information on chemical species. RAINet enables rotational spectroscopy by streamlining conversion of spectral information to chemical composition.

 

 

 

(From left) Yuepeng Zhang (AMD) and Kaizhong Gao (AMD) of the HyMag Magnets team.

HyMag Magnets by Kaizhong Gao (AMD) and Yuepeng Zhang (AMD)

This submittal proposes a revolutionary technology (HyMag) that significantly increases the usable magnetic flux density of a permanent magnet by 10–30 percent, leading to a dramatic improvement in the energy efficiency of electric motors and wind turbine generators. HyMag are less expensive and more environmentally friendly, consuming 60–90 percent fewer heavy-rare-earth materials.

 

 

 

(From left) Kevin Harms (LCF), Shane Snyder (MCS), Philip Carns (MCS), Robert Ross (MCS) and Robert Latham (MCS) of the Darshan team.

Darshan Software by Philip Carns (MCS), Kevin Harms (LCF), Robert Latham (MCS), Shane Snyder (MCS) and Robert Ross (MCS)

Darshan is a software product used to understand and improve the performance of the world’s largest data-intensive computing applications in fields such as physics, cosmology, chemistry, biology, aerospace and earth science. It has become the de facto standard for optimizing scientific data access in government, academic and industry computing centers around the world.

 

 

 

(From left) Scott Schlueter (DIS), Tom Wall (DIS) and Carmella Burdi (DIS) of the GRID-M team. Not pictured from the GRID-M team is Kyle Pfeiffer (DIS).

Grassroots Infrastructure Dependency Model (GRID-M) by Kyle Pfeiffer, Tom Wall, Carmella Burdi and Scott Schlueter (DIS)

This entry is for a model that provides public safety officials with the near-real-time status of critical supply chains following major disasters. GRID-M is offered at no charge to the Federal Emergency Management Agency (FEMA), which sponsored its development, and it will be free to all federal sponsors. By scaling the complex supply chain processes to a manageable paradigm, GRID-M reduces the otherwise daunting computational load associated with providing a wealth of disaster-related information in real time and analyzing recovery and restoration of services. Users can customize the tool to consider the supply chains of greatest significance within their jurisdictions.

 

Justin Wozniak (DSL) of the Swift/T team. Not pictured from the Swift/T team are Jonathan Ozik (DIS), Nicholson Collier (DIS), Ian Foster (DSL) and Michael Wilde.

Swift/T: Dataflow Programming for Scientific Supercomputing Workflows by Justin Wozniak (DSL), Jonathan Ozik (DIS), Nicholson Collier (DIS), Michael Wilde and Ian Foster (DSL) in addition to two outside collaborators

Swift/T is a software system that scientists use to run calculations on very large supercomputers. It has been successfully used by cancer scientists and combustion engine designers, among others. The technology allows researchers to distribute the computational work of scientific studies and make good use of parallel computing systems.

The R&D 100 Awards span five categories: Analytical/Test, IT/Electrical, Mechanical Devices/Materials, Process/Prototyping and Software/Services. For the third year, the R&D 100 Awards Committee will also honor excellence with four Special Recognition Awards: Market Disruptor Services, Market Disruptor Products, Corporate Social Responsibility and Green Tech.

The competition’s 180 finalists were selected by an independent panel of more than 50 judges representing R&D leaders in a variety of fields. Winners will be announced Nov. 16 at the 2018 R&D 100 Awards and Technology Conference in Orlando.

 


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