The project brought together the combined resources of the Department of Energy and the National Cancer Institute to accelerate solutions to cancer-specific science challenges, including drug discovery, protein behavior in cell membranes, and electronic health record analysis. CANDLE applies machine learning and deep learning techniques to large-scale cancer datasets in a distributed computing environment for the discovery of new cancer therapies and treatments. The software suite provides cancer researchers with key functions and capabilities to optimize and apply these models on supercomputers.
Rick Stevens (Argonne National Laboratory) directed the joint entry with Lawrence Livermore National Laboratory, Oak Ridge National Laboratory, Los Alamos National Laboratory, and the Frederick National Laboratory for Cancer Research. Tanmoy Bhattacharya led the Los Alamos team that included Jamal Mohd- Yusof, Cristina Garcia Cardona, and Sayera Dhaubhadel.
The portable instrument uses high-resolution absorption spectroscopy to determine the isotopes in a solid sample quickly and accurately. This avoids the sample preparation, chemical waste, and isotopic interference of other methods. Fast analysis at the point of generation aids nuclear energy production, global security, and nuclear medicine.
Alonso Castro led the Los Alamos team of Joshua Bartlett and David Petrushenko.
The platform develops optimized biosurveillance tools for entire classes of viral pathogens, outbreak strains and variants. The current methods of pathogenic viral detection can’t keep pace with the high mutation rate of RNA viruses. The FEVER technology of designing diagnostic probes is bolstered against viral mutation. FEVER provides the foundational biosurveillance capability to support global pandemic preparedness and mitigate future outbreaks.
Jessica Kubicek-Sutherland led the Los Alamos team of Brian Foley, Samantha Courtney, Jason Gans, Zachary Stromberg, and James Theiler. The late Karina Yusim initially directed the researchers.
The integrated system seamlessly coordinates residential air conditioners to enhance electric-grid reliability. GRID-BAL uses the flexibility of large aggregations of residential air conditioner systems, modestly adjusting their on-off timing without affecting customer comfort. The control method has been tested through simulation, laboratory experimentation and field testing to demonstrate that it can transform the appliance responsible for the largest fraction of household electricity use into an asset for providing grid resiliency and offsetting renewable generation variability.
Drew Geller led the Los Alamos efforts, including contributions from Scott Backhaus, while Professor Johanna Mathieu at the University of Michigan led the overall project. Additional collaborators included the University of California - Berkeley and Pecan Street Inc.
The new capability in energy resolution and efficiency for material analysis in scanning electron microscopes allows researchers to measure material signatures at the nanoscale. Such analytical capabilities for chemical and elemental composition mapping are especially important for samples that vary in composition on very small length scales, and where macroscopic material properties depend on microscopic features. Nanoscale mapping could benefit the semiconductor fabrication industry, forensics, materials science, environmental science, biological science, and geological science fields.
Mark Croce led the Los Alamos team of Enrique Batista, Eric Bowes, Matthew Carpenter, Christopher Fontes, Joseph Kasper, Katrina Koehler, Daniel McNeel, Michael Rabin, Katherine Schreiber, Benjamin Stein, Emily Teti, Gregory Wagner, Jacob Ward, Lei Xu, and Ping Yang; partner organizations included the National Institute of Standards and the University of Colorado - Boulder.
The novel instrument delivers trace gas detection capabilities in a small, lightweight package for space. It analyzes the spectral fingerprint of each toxic gas, processes raw data, and allows attribution of harmful gas emission sources on Earth. NACHOS supports space-based, airborne, and ground-based mission deployment, including trace gas detection from CubeSats, deepspace planetary missions, remote monitoring ground stations and airborne monitoring from drones. Two NACHOS CubeSats have flown in space.
Steven Love led the Los Alamos team of Kerry Boyd, Michael Caffrey, Malakai Coblentz, Magdalena Dale, Nicholas Dallmann, Manvendra Dubey, Bernard Foy, Tracy Gambill, Arthur Guthrie, Markus Hehlen, Ryan Hemphill, Gregory Lee, Kristina McKeown, Hannah Mohr, Donathan Ortega, Logan Ott, Glen Peterson, Kirk Post, Michael Proicou, Claira Safi, Daniel Seitz, Paul Stein, James Theiler, Christian Ward, and James Wren.
Data analysis process is complex, time consuming and resource intensive. The KV-CSD revolutionary information storage hardware efficiently records, sorts and indexes supercomputer simulation output to streamline big-data analysis. The technology combines an efficient hardware platform and ordered key-value storage interface to provide an optimized data layout for retrieving data on query and using computational resources on the storage device. This advance drastically reduces unnecessary data movement and slashes the time to scientific insight.
Los Alamos led the joint entry with SK hynix. Dominic Manno directed the Los Alamos team of Jason Lee, Qing Zheng, David Bonnie, Gary Grider, and Bradley Settlemyer.
Modern society is critically dependent on the electric power grid. The optimization software package models restoration and reconfiguration of electric power distribution feeders featuring networked microgrids. The technology uses real-world data from utilities and has been tested with power hardware-in-the-loop, allowing resilience scenarios to be validated without risk to the real system. Utilities can use PowerModelsONM to plan for networked microgrids to support increased resilience and rapid recovery after electric grid outages.
Los Alamos led the joint entry with the National Renewable Energy Laboratory, Sandia National Laboratories, and the National Rural Electric Cooperative Association. Russell Bent directed the Los Alamos team of David Fobes, Arthur Barnes, Jose Tabarez, Harsha Nagarajan, Hassan Hijazi, Smitha Gopinath, Kshitij Girigoudar, Haoxiang Yang, Thabiso Mabote, Matthew Job, and Zhen Fan.
The technology builds hardened machine tooling for forming, drawing and stamping materials. Metal powder additive manufacturing reduces the total number of steps to create tooling, saves time, minimizes wasted energy and material and improves recyclability of material. Material addition, densification, and hardening take place in a single process. Tools with complex geometric designs, interior features and material characteristics can be tailored for weight, thermal properties, strength, and wear resistance.
Ryan Mier led the team of Kevin Le, Colt Montgomery, Robin Montoya, and Michael Brand.
The technology combines molecular engineering of earthabundant materials with a thin film coating method that can be adapted to mass production and scaled for size. Processing costs less and uses much less energy compared with current approaches. The near-single crystal layer films create many fewer crystal-grain boundaries and defects than other semiconductor fabrication methods. Benefits include more efficient solar cells, brighter and fully color-tunable lightemitting diodes (LEDs), and more sensitive x-ray detectors.
Wanyi Nie led the team of Sergei Tretiak, Hsinhan Tsai, and Shreetu Shrestha.