Berkeley Lab Innovations Recognized With 3 R&D 100 Awards

NWB:N supports storage and use of data from complex neurophysiology experiments

NWB:N supports storage and use of data from complex neurophysiology experiments and enables collaboration and sharing, reuse, and reproduction of data and analysis across teams and projects. Image shows MRI scans of a person with multiple sclerosis. (Credit: Ilena George and Daniel Reich, National Institute of Neurological Disorders and Stroke, National Institutes of Health

Cutting-edge technologies from Lawrence Berkeley National Laboratory (Berkeley Lab) to detect radiation, make buildings more energy efficient, and accelerate neuroscience research were honored with R&D 100 Awards by R&D World magazine.

Also recognized was Spack : A Package Manager for HPC Systems, a project led by Lawrence Livermore National Laboratory and which includes the National Energy Research Scientific Computing Center (NERSC) . NERSC is a supercomputing facility operated by Berkeley Lab for the Department of Energy’s Office of Science.

Since 1963, the annual R&D 100 Awards have recognized 100 technologies of the past year deemed most innovative and disruptive by an independent panel of judges. The full list of winners, announced by parent company WTWH Media, LLC, is available here.

Berkeley Lab’s award-winning technologies are described below.

Neurodata Without Borders: Neurophysiology (NWB:N)

The Neurodata Without Borders: Neurophysiology (NWB:N) project is a data standard for neurophysiology research that provides neuroscientists with a software ecosystem that enables them to share, archive, use, and build tools for analyzing data, ensuring the success of brain research worldwide and accelerating the pace of scientific discovery. It is led by Berkeley Lab in collaboration with the Allen Institute for Brain Science and multiple neuroscience labs.

"NWB:N fills a critical gap in the neuroscience research community by providing not only a data standard but a rich software ecosystem surrounding the standard," said Oliver Rübel, a staff scientist in Berkeley Lab’s Computational Research Division and an NWB:N principal investigator.

Unlike other data formats, NWB is open-source, free to use, supports the full scope of neurophysiology experiments, and is optimized for storing and analyzing the increasingly large datasets being generated today.

For a more detailed description of NWB:N and a complete list of researchers, click here for an article by Berkeley Lab Computing Sciences.

Commercial Building Energy Saver (CBES)

In the United States, smalland medium-sized commercial buildings consume 47% of the primary energy in the building sector. However, building owners and their contractors lack easy, low-cost access to tools to identify cost-effective energy-efficient retrofits. The Commercial Building Energy Saver (CBES) software toolkit enables equitable access to building deep retrofit and zero-net energy strategies for these buildings.

CBES identifies and evaluates a wide range of retrofit measures in terms of energy savings, energy cost savings, and payback, considering incentives and rebates. CBES enables users to evaluate and quantify the potential benefits of renewable technologies (such as photovoltaics and energy storage), advanced HVAC systems, and demand response measures. CBES supports rapid decarbonization of smalland medium-sized buildings by enabling an uncomplicated, affordable dataand model-driven retrofit decision-making process.

"We wanted to provide a tool for smalland medium-sized businesses because it’s an overlooked sector that, collectively, has a large carbon footprint," said Tianzhen Hong, one of the lead developers. "CBES is powerful yet easy to use, and we believe it can help buildings reach their net-zero energy goals.”

The development team also includes Berkeley Lab researchers Mary Ann Piette, Kaiyu Sun, Cynthia Regnier, Xuan Luo, Sang Hoon Lee, Yixing Chen, Rongpeng Zhang, Sarah C. Taylor-Lange, and Philip Price of the Energy Technologies Area.

The above two technologies won in the software/services category. The third won in the analytical/test category.

Portable Radiation Imaging, Spectroscopy and Mapping (PRISM)

The Portable Radiation Imaging, Spectroscopic and Mapping (PRISM) system is a new type of advanced radiation detection device for search, location, identification, and characterization of radioactive materials. The system can be used to counter nuclear threats as well as to mitigate human exposure to radioactivity, such as accidents at nuclear power plants or nuclear terrorism incidents.

Unlike other portable radiation imaging systems, which require static operations and provide only 2D images, this device provides 3D maps of radioactive nuclear materials co-registered to physical objects. And because the PRISM device can be freely carried through the environment by either a human or robotic operator, dynamic operation with feedback during the data acquisition is possible. The system uses more than 100 detectors made of cadmium zinc telluride.

PRISM alerts the operator of the presence, type, amount, location and distribution of gamma-ray emitting nuclear material. The size and weight of the device permits efficient deployment to U.S. military, international inspectors, and law enforcement personnel conducting search and interdiction operations.

Researchers include Lucian Mihailescu, Kai Vetter, Paul Barton, Marcos Turqueti, Daniel Hellfeld, Alex Moran, Victor Negut, and Donald Gunter of Berkeley Lab’s Nuclear Science and Engineering Divisions, as well as Hank Zhu of the Defense Threat Reduction Agency, which funded the project.


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