Lighthouse Directional Radiation Detectors
EDGE (Empowering the Development of Genomics Expertise) Bioinformatics
This award is designed to highlight any innovation that was employed to battle the worldwide COVID-19 pandemic. This is not limited to medical or pharmaceutical entries—newly developed products and services as diverse as software, safety equipment, or AI that had an impact will be considered.
EpiCast: Simulating Disease Epidemics with Extreme Detail - GOLD
The agent-based simulation uses synthetic, representative populations to simulate infectious disease transmission in the U.S. in tremendous detail. The simulation models human behavior combined with community-specific information to provide a fine-grained projection of the effect of potential mitigation strategies for decision makers. During the COVID-19 pandemic, the CDC and the New Mexico Department of Health used EpiCast simulations to examine what-if scenarios of the combined impact of different intervention strategies.
Sara Del Valle led the Los Alamos team of Timothy Germann, Geoffrey Fairchild, Carrie Manore, Manhong Z. Smith, Lori Dauelsberg, Terece Turton, Morgan Gorris, Chrysm Ross, James Ahrens, Daniel Hemphill, and Kaitlyn M. Martinez.
From an engineering and societal perspective, efficiency and environmental factors play an increasingly important role in the world today. R&D World wants to recognize those innovations that help make our environment greener and our goal towards energy reduction closer.
Oleo-Furan Surfactants Made from Renewable Biomass - BRONZE
Oleo-furan surfactants (OFS) is a new class of non-toxic, non-irritating cleaning agents (surfactants) for laundry detergent. It is the only surfactant that performs effectively in cold water and in hard water, without additional chemicals that other detergents must use to bind the minerals in hard water. OFS can be produced readily from sustainable, bioderived molecules that don’t tax the environment or compete with the food supply chain.
Andrew Sutton of Los Alamos National Laboratory led the Los Alamos team of Cameron Moore and Xiao (Claire) Yang. Christoph Krumm of Sironix Renewables led collaborators from Sironix.
Engineered Quantum Dots for Luminescent Solar Concentrators
A recipient of the Green Technology Special Recognition Award was the Los Alamos innovation called Turning Windows and Building Facades into Energy-Producing Solar Panels: Engineered Quantum Dots for Luminescent Solar Concentrators.
These revolutionary semitransparent windows contain highly emissive semiconductor nanocrystals (quantum dots) that collect sunlight for photovoltaics and provide a desired degree of shading. The material can turn windows and building facades into electrical generators of nonpolluting power. The nontoxic dots absorb the sunlight, re-emit it at a longer wavelength and waveguide it towards edge-installed photovoltaic cells to produce electricity. This technology can transform once-passive building facades into power-generation units, which can be particularly useful in densely populated areas.
Los Alamos submitted the joint entry with co-developer University of Milano-Bicocca. Victor I. Klimov of Physical Chemistry and Applied Spectroscopy led the team of Kirill Velizhanin of Physics and Chemistry of Materials, Hunter McDaniel (former Los Alamos postdoctoral researcher, currently with UbiQD LLC), Sergio Brovelli, and Francesco Meinardi (University of Milano-Bicocca).
This award is designed to highlight any service from any category as one that forever changed the R&D industry or a particular vertical within the industry. No matter what the specific service is, the focus should be on industry impact.
Terra Spotlight: A New Paradigm in Rapid Change Detection Using Satellite Images - SILVER
The software accomplishes what once seemed impossible: automatic identification of changes in satellite-based imagery collected from multiple independent imaging systems. The rigorous mathematical framework implicitly aligns the disparate sensing systems for multi-satellite, multi-physics data fusion, and rapid discovery of important changes on the Earth’s surface. Terra Spotlight uses more data collected from existing satellite imaging sensors without requiring investment in additional expensive satellite platforms.
Amanda Ziemann led the Los Alamos team of James Theiler and Christopher Ren
SmartTensors AI Platform - BRONZE
Crucial signals can be overlooked in big data. SmartTensors AI Platform uses unsupervised machine learning to transform and compress hundreds of trillions of data bytes into manageable pieces of information. Identifying hidden patterns in the data facilitates the discovery of new phenomena and new mechanisms, which enables informed decisions. Applications include analyses in medicine, disease spread and prediction, energy extraction, material science, carbon sequestration, climate change, economy, infrastructure stability, anomaly detection, text mining, and national security.
Boian Alexandrov and Velimir “Monty” Vesselinov led the Los Alamos team of Bulbul Ahmmed, James Ahrens, Manish Bhattarai, Gopinath Chennupati, Derek DeSantis, Hristo Djidjev, Maksim Erin, Namita Karat, Daniel Livingston, Maruti Mudunuru, Ben Nebgen, Dan O’Malley, John Patchett, Elijah Pelofske, Lakshman Prasad, Jesus Pulido, Kim Rasmussen, Adam Rupe, Erik Skau, Justin Sybrandt, Carl James Talsma, Duc Truong, Ravi Vangara, and Neda Vesselinova
Cluster Integrity, Exception Resolution, and Reclustering Algorithm - GOLD
CIERRA is the first and only software that routinely identifies the most extraordinary and unpredictable type of lightning–megaflashes–providing unprecedented quality data for further research. At the forefront of extreme lightning research, CIERRA improves environmental hazard awareness by issuing rapid notifications when a storm starts generating megaflashes, enhancing public safety, weather, and wildfire predictions.
Michael Peterson (LANL) and University of Maryland
Smart Microbial Cell Technology - SILVER
Smart Microbial Cell Technology is an ultra‐high‐throughput biocatalyst screening platform that alleviates the bioengineering testing bottleneck, finds efficient and useful biocatalysts, and delivers optimized custom biocatalysts, accelerating biocatalyst discovery and essential industrial applications like pharmaceuticals and renewable energy. Smart Microbial Cell Technology is a significant breakthrough in biocatalyst discovery, engineering, and evolution, with benefits that will ripple across society.
LANL team: Taraka Dale, Ramesh Jha, and Charlie Strauss
This award is designed to highlight any product from any category as one that has changed the game in any industry. No matter what the specific product is, the focus should be on industry impact. Was your product a game changer in the last year?
Earth’s-field Resonance Detection and Evaluation (ERDE) Devices - SILVER
ERDE devices are portable nuclear magnetic resonance (NMR) spectrometers that use the Earth’s magnetic field for rapid, accurate, and safe identification of chemicals without requiring superconducting magnets and liquid cryogens. Smaller than a microwave oven, ERDE devices have spectral resolutions equivalent to or higher than achieved with conventional superconducting NMR spectroscopy at a much lower cost and can simultaneously collect signature data for all NMR-active nuclei in a single spectrum. These portable NMR spectrometers leverage heteronuclear J-couplings for applications in environmental sensing, through-pipe sensing, chemical analysis, toxic chemical detection, and compound structure identification.
Derrick Kaseman and Bob Williams led the Los Alamos team of Michelle Espy, Jacob Yoder, Per Magnelind, Algis Urbaitis, Michael Janicke, and Scarlett Widgeon Paisner
Atomic Armor - GOLD
The diamond-hard, flexible 2D coating shields sensitive materials and devices from harsh environments while extending a device’s lifetime and maximizing its functionality. Atomic Armor can be coated on solid surfaces of any shape or material. The Materials by Design approach for the one-atom-thick tunable coating enables it to be customized for many applications, including selective permeability.
Nathan Moody and Hisato Yamaguchi led the team of Fangze Liu, Enrique Batista, Gaoxue Wang, Ping Yang, Vitaly Pavlenko, Philip Fernandes, and Jeffrey DeFazio (Photonis Scientific, Inc)
GUFI: Grand Unified File Index
The Grand Unified File Index is the fastest software for searching metadata at the scale used by supercomputer and enterprise datacenters. This open-source software allows simultaneous secure queries of ultrascale metadata by multiple users and system administrators. Users can search billions of files in the file system trees and receive query results in seconds without sacrificing the performance of the file system itself or impacting security.
Gary Grider led the team of David Bonnie, Jeff Inman, Dominic Manno, and Wendy Poole
Lighthouse Directional Radiation Detectors
The detectors precisely determine the location, amount, and movement of a radioactive source in the presence of multiple sources. Gamma, fast-neutron, and thermal-neutron detectors are small, lightweight, portable, high resolution, and fast. Applications include environmental and geological surveys, emergency response, materials accountability and control, and situational awareness.
Los Alamos submitted the joint entry with Questa Instruments LLC, Phoenix International Holdings Inc., Sexton Corp. L. Jonathan Dowell and Dale Talbott led the team of Rick Rasmussen, Rick Rothrock, Sam Salazar, Theresa Cutler, Mark Wald-Hopkins, Kris Hyatt, Don Hyatt, Larry Bronisz, James Thompson, Chris Chen, David Fontaine, Adam Kingsley, Thomas Barks, Damien Milazzo, James Hemsing, Gary Sundby, and David Allen. The team included collaborators from the U.S. Army; Quaesta Instruments, LLC; Phoenix International Holdings, Inc.; and Sexton Corporation
This award honors organizational efforts to be a greater corporate member of society, from a local to global level. Good works criteria may include, but aren't limited to, efforts to curb carbon footprint reduction, efforts in third-world countries, better prosthetics for wounded soldiers, LEED green building certification, local fundraising efforts, scholarship programs, and involvement and/or contributions to the STEM community.
CICE Consortium - GOLD
Sea ice is critical in moderating the global climate and polar ecosystems. Los Alamos leads the CICE Consortium, an international group of stakeholders and code developers that advances sea ice modeling in the public domain, providing state-of-the-art models for both near-term predictions of sea ice and weather and longer term climate projections. CICE and its infrastructure are the global standard for sea ice modeling across scales for scientific research, weather and ice forecasting, maritime operations planning, and global climate projections.
Los Alamos led the joint entry with the Danish Meteorological Institute, Environment and Climate Change Canada, Institute of Oceanology – Polish Academy of Sciences, National Center for Atmospheric Research, National Oceanic and Atmospheric Administration, Naval Postgraduate School, Naval Research Laboratory Stennis Space Center, University of Washington, and University of Reading. The Los Alamos research team of Elizabeth Hunke, John Dukowicz, Bill Lipscomb, Adrian Turner, Andrew Roberts, Matthew Turner, Nicole Jeffery, Philip Jones, and Scott Elliott developed the core sea ice model and software.
QUIC-Fire - GOLD
QUIC-Fire is the first laptop-capable, real-time wildland fire prediction software to explicitly model a fire’s two-way interaction with the atmosphere and 3D heterogeneous vegetation, transforming the ability to assess risk, optimize fuel treatments, and plan prescribed burns. With QUIC-Fire, practitioners can quickly model how a fire will spread in situations previously impossible without a supercomputer by capturing critical influences of 3D vegetation structure, interactions between multiple fires, variable winds, and complex topography at meter-scale resolutions.
Multi-institution team of LANL (Sara Brambilla, Michael Brown, Alexandra Jonko, Alexander Josephson, Rod Linn, Richard Middleton, David Robinson) and U.S. Department of Agriculture Forest Service and Tall Timbers Research Station
RETRO Rx - GOLD
Rapid, easy tools for responding to outbreaks and re-emergence events use web-based information to assess infectious disease outbreaks and then provide visual analytics and actionable information to mitigate them and protect the population. The analytic tools require minimal effort and expertise and can be used for research, decision-making, analysis, forecasting, and training and education.
Alina Deshpande led the team of Geoffrey Fairchild, Derek Aberle, William Rosenberger, Ashlynn Daughton, Nidhi Parikh, Antonietta Lillo, Nileena Velappan, Attelia Hollander, Emily Alipio Lyon, Forrest Altherr, Maneesha Chitanvis, Lauren Castro, Reid Priedhorsky, Grace Vuyisich, Eric Generous, Kristen Margevicius, Kirsten McCabe, and collaborators from University of New Mexico, University of Virginia, University of California – Santa Barbara, and Specifica Inc.
SimCCS2.0 - SILVER
The open-source software optimizes the design of carbon dioxide (CO2) capture, transport, and storage infrastructure while reducing industry’s carbon footprint and enhancing carbon tax credits and oil production. The fully integrated, end-to-end software package accounts for geographic and social constraints to geolocate pipelines in the real world. Industry, government, and stakeholders could use the software to design cost-effective pipeline networks linking CO2 sources (such as power plants) with sites where CO2 can be stored in deep saline aquifers or reused to increase oil and gas production.
Los Alamos led the joint entry with Indiana University and Montana State University. Richard Middleton directed the team of Bailian Chen, Dylan Harp, Brendan Hoover, Rajesh Pawar, Philip Stauffer, and Hari Viswanathan plus collaborators from Indiana University and Montana State University.
Universal Bacterial Sensor - GOLD
The human immune system inspired the development of the Universal Bacterial Sensor—a unique technology that mimics biological recognition of bacterial pathogens. Like the immune system, the sensor recognizes all bacterial infections as early as before the onset of symptoms. The method uses only a small volume of sample and requires no prior knowledge of what the bacteria might be. It is inexpensive, field-ready, can be performed by a nonexpert, and provides reliable answers within 30 minutes.
Harshini Mukundan led the team of Basil Swanson, Aaron Anderson, Jessica Kubicek-Sutherland, Ramamurthy Sakamuri, and Loreen Stromberg