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.
In addition to the R&D 100 Award, SimCCS2.0 won a Silver Medal in the Corporate Social Responsibility Special Recognition Category. This award honors organizational efforts to be a greater corporate member of society, from a local to global level.
The miniature platform technology performs sequential operations involved in complex laboratory processes. SPLASH uses novel and powerful magnetically actuated valves and pumps to create complex microfluidic circuits with minimal peripheral hardware, tubing, and power requirements. The small size and simplicity of operation enable automated sample preparation and processing for point-of-need applications.
Pulak Nath led the team of Dylan Purcell, Jackson McFall, Aneesh Pawar, Tony Huang, Kiersten Haffey, and Hasibul Islam.
The MC-15 instrument is the smallest, lightest, and fastest portable neutron multiplicity detector, recording neutrons with a 100-nanosecond time resolution. The MC-15 requires little training to operate, provides onboard or remote operation, and processes data in real time. Two units can be used in tandem to double the detection efficiency. The invention enables nuclear emergency response teams to quickly identify and assess nuclear-based threats, and it has applications for research in nuclear data and radiation transport validation.
Los Alamos led the joint entry with Lawrence Livermore National Laboratory and Sandia National Laboratories. The Los Alamos team consisted of Mark Nelson, Eric Sorensen, Brian Rooney, Richard Rothrock, Kiril Ianakiev, Metodi Iliev, Samual Salazar, Christopher Romero, David Jones, Jesson Hutchinson, and Matthew Newell and included collaborators from Lawrence Livermore National Laboratory and Sandia National Laboratories.
As supercomputers move toward exascale—a quintillion calculations per second—they incorporate a variety of hardware and processing systems. All of the elements in these systems must communicate harmoniously to operate efficiently. UCX is an open-source software for high performance computers that allows diverse hardware systems and architectures to communicate by creating common interface definitions.
Los Alamos led the joint entry with Advanced Micro Devices, Argonne National Laboratory, Arm Ltd, Mellanox Technologies, NVIDIA, Stony Brook University, Oak Ridge National Laboratory, and Rice University. Stephen Poole directed the team of Jeffery Kuehn and Howard Pritchard and collaborators from Advanced Micro Devices, ANL, Arm Ltd, Mellanox Technologies, NVIDIA, Stony Brook University, ORNL, and Rice University.
The FEARCE software models engine motion, the motion of parts and their influence on the gases, multiphase injection of sprays and fuel droplets, the turbulent mixing of fuel and air, and subsequent chemical reactions in combustion engines. This modeling helps enable the design of engines for higher fuel efficiency and lower harmful emission. FEARCE models an engine’s operating properties and ranges that can’t be addressed readily with experiments. The software also enables designers to develop and optimize engines to run on alternative fuels, such as biofuels, which may require different operating conditions than those required for conventional fuels.
David Carrington led the team with Jiajia Waters.
The platform is an affordable, robust, autonomous system for the detection of natural gas leaks quickly and at low cost. Gas sensor data and atmospheric wind measurements from two compact instruments are fed into an artificial neural network that can detect, locate, and quantify a leak. The lightweight instrument can be flown on a drone or attached to a vehicle to pinpoint, attribute, and distinguish natural gas leaks from biogenic methane sources.
Manvendra Dubey led the team of Bryan Travis, Keely Costigan, Jeremy Sauer, and collaborators from Aeris Technologies and Rice University.
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).
In addition to the R&D 100 Award, Atomic Armor won a Gold Medal in the Market Disruptor-Products Special Recognition Category. This award is designed to highlight any product that has changed the game in any industry.
The DeltaFS open-source distributed file system for massively parallel applications creates, updates, and manages extreme numbers of files, alleviating the metadata bottleneck and accelerating highly selective queries. DeltaFS creates billions of files per second and does not require any additional compute resources or post-processing to create its data index. The performance and scalability capabilities that DeltaFS introduces are critical for storing and accessing data in the era of exascale computing.
Los Alamos led the joint entry with Carnegie Mellon University. Bradley Settlemyer directed the team of Gary Grider and collaborators from Carnegie Mellon University.
Electric power transmission networks are critical for modern societies, but these networks are vulnerable to threats from extreme events. The Severe Contingency Solver open-source software analyzes severely damaged electric power networks that have hundreds to thousands of damaged components. The software removes the need for human intervention when assessing how damage from extreme events will restrict power delivery from utility grids.
Carleton Coffrin led the team of James Arnold, Scott Backhaus, Russell Bent, David Fobes, Kaarthik Sundar, and Byron Tasseff.