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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 757 records · Page 42

All sources NASA NTRS DOE OSTI

DOE OSTI2017

Control of Architecture in Rhombic Dodecahedral Pt–Ni Nanoframe Electrocatalysts

Platinum-based alloys are known to demonstrate advanced properties in electrochemical reactions that are relevant for proton exchange membrane fuel cells and electrolyzers. Further development of Pt alloy electrocatalysts relies on the design of architectures with highly active surfaces and optimized utilization of the expensive element, Pt. For this study, we show that the three-dimensional Pt anisotropy of Pt-Ni rhombic dodecahedra can be tuned by controlling the ratio between Pt and Ni precursors such that either a completely hollow nanoframe or a new architecture, the excavated nanoframe, can be obtained. The excavated nanoframe showed ~10 times higher specific and ~6 times higher mass activity for the oxygen reduction reaction than Pt/C, and twice the mass activity of the hollow nanoframe. The high activity is attributed to enhanced Ni content in the near-surface region and the extended two-dimensional sheet structure within the nanoframe that minimizes the number of buried Pt sites.

36 MATERIALS SCIENCE↗

NASA NTRS1992

Architectures for mission control at the Jet Propulsion Laboratory

JPL is currently converting to an innovative control center data system which is a distributed, open architecture for telemetry delivery and which is enabling advancement towards improved automation and operability, as well as new technology, in mission operations at JPL. The scope of mission control within mission operations is examined. The concepts of a mission control center and how operability can affect the design of a control center data system are discussed. Examples of JPL's mission control architecture, data system development, and prototype efforts at the JPL Operations Engineering Laboratory are provided. Strategies for the future of mission control architectures are outlined.

Davidson, Reger A.↗

NASA NTRS2002

Comparison of the EO-1 Advanced Land Imager Performance With the Landsat Data Continuity Mission Specification

The performance requirements for the Advanced Land Imager were developed under NASA's New Millennium Program and were intended to facilitate the validation of new sensor technologies and architectures for potential application in future remote sensing missions. The Advanced Land Imager (ALI) was designed and flown well before the Landsat Data Continuity Mission (LDCM) specifications were developed. Nevertheless, the science focus of the ALI technology validation was Landsat data continuity. Therefore, although exact compliance by ALI is not expected, the performance should demonstrate a path to a compliant sensor system. The performance of the ALI, as determined from preflight and flight data, is compared to the LDCM specification. Twenty-one noncompliances have been identified: four data collection, four spectral, six spatial, and seven radiometric (Table I). All but six of these are considered minor. The six major noncompliances are the result of stray light, leaky detectors, and contamination. Appendix A replicates the LDCM specification and contains ALI compliance notes where appropriate. Details of the ALI stray light, contamination, and leaky detectors are provided in Appendix B, C, and D respectively. Additional information pertaining to the calculation of the ALI edge response and coherent noise is presented in Appendix E and F. A list of ALI related publications is provided in Appendix G.

Mendenhall, J. A.↗

DOE OSTI2017

Photocatalytic fuel production

The conversion of carbon dioxide and water to fuel in artificial systems requires efficient coupling of light absorbers and catalysts, and assembly of the components into hierarchical structures to close the photocatalytic cycle. Recent breakthroughs in the embodiment of molecular photoactive components in ultrathin oxide layers, and the introduction of new materials approaches for interfacial charge transfer have led to substantially improved coupling of chromophores and catalysts. Finally, these advances are accelerating the exploration of novel architectures for reducing CO 2 by H 2 O in scalable, single integrated photosystems to reach the high power efficiencies recently demonstrated with photovoltaic-assisted approaches.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2018

Building Extraction at Scale Using Convolutional Neural Network: Mapping of the United States

Establishing up-to-date large scale building maps is essential to understand the urban dynamics, such as estimating population, urban planning, and many other applications. Although many computer vision tasks have been successfully carried out with deep convolutional neural networks, there is a growing need to understand their large scale impact on building mapping with remote sensing imagery. In this paper, taking advantage of the scalability of convolutional neural networks (CNNs) and using only few areas with the abundance of building footprints, for the first time we conduct a comparative analysis of four state-of-the-art CNNs for extracting building footprints across the entire continental United States. The four CNN architectures namely: Branch-out CNN, fully convolutional network (FCN), conditional random field as recurrent neural network (CRFasRNN), and SegNet, support semantic pixelwise labeling and focus on capturing textural information at multiscale. We use 1-meter resolution aerial images from National Agriculture Imagery Program as the test-bed, and compare the extraction results across the four methods. In addition, we propose to combine signed-distance labels with SegNet, the preferred CNN architecture identified by our extensive evaluations, to advance building extraction results to instance level. We further demonstrate the usefulness of fusing additional near IR information into the building extraction framework. Large scale experimental evaluations are conducted and reported using metrics that include: Precision, recall rate, intersection over union, and the number of buildings extracted. With the improved CNN model and no requirement of further postprocessing, we have generated building maps for the United States with an average processing time less than one minute for an area of size ∼ 56 km 2 . Finally, the quality of extracted buildings and processing time demonstrated that the proposed CNN based framework fits the need of building extraction at scale.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2019

Energy storage: The future enabled by nanomaterials

Lithium-ion batteries, which power portable electronics, electric vehicles, and stationary storage, have been recognized with the 2019 Nobel Prize in chemistry. The development of nanomaterials and their related processing into electrodes and devices can improve the performance and/or development of the existing energy storage systems. We provide a perspective on recent progress in the application of nanomaterials in energy storage devices, such as supercapacitors and batteries. The versatility of nanomaterials can lead to power sources for portable, flexible, foldable, and distributable electronics; electric transportation; and grid-scale storage, as well as integration in living environments and biomedical systems. To overcome limitations of nanomaterials related to high reactivity and chemical instability caused by their high surface area, nanoparticles with different functionalities should be combined in smart architectures on nano- and microscales. The integration of nanomaterials into functional architectures and devices requires the development of advanced manufacturing approaches. We discuss successful strategies and outline a roadmap for the exploitation of nanomaterials for enabling future energy storage applications, such as powering distributed sensor networks and flexible and wearable electronics.

catalysis (heterogeneous)↗

DOE OSTI2026

A roadmap toward scaling, reasoning and self-evolving foundation models for nuclear and particle physics

Foundation models have revolutionized artificial intelligence, with Large Language Models demonstrating unprecedented capabilities in multimodal understanding, reasoning and tool use. Nuclear and particle physics stands at a critical juncture where similar transformative potential awaits realization. The field generates exabytes of experimental data, exascale simulations, and decades of theoretical insights — yet these remain largely disconnected from modern Artifical Intelligence (AI) capabilities, with most physics AI applications confined to narrow, task-specific models that suffer from domain shifting when applied to real experimental data. We present a roadmap for FM4NPP (Foundation Model for Nuclear and Particle Physics), systematically scaling from current proof-of-concept models to trillion-parameter architectures capable of autonomous discovery. Our approach advances three critical frontiers: unified data infrastructure integrating detector data, scientific knowledge and computational tools across global facilities; multi-facility foundation models enabling cross-experiment knowledge transfer and accelerated discovery; and agentic AI capabilities for reasoning and autonomous tool use. The resulting self-evolving FM4NPP will transform physics research by converting time-intensive data analysis, theory derivation and computational bottlenecks into rapid AI–human collaborative discovery. This paradigm shift promises to fundamentally accelerate scientific progress in nuclear and particle physics, enabling researchers to focus on high-level insights while AI handles routine analysis and explores vast parameter spaces beyond human capacity.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2024

Pulse compressor architecture to enable next-generation high-energy petawatt-class lasers

The maximum energy obtainable within a single aperture of a high-energy petawatt-class (HEPW) laser is typically limited by the pulse compressor. This work evaluates the potential impact of two new pulse compression grating technologies (HELD gratings and TM polarization) on HEPW laser systems. A compressor architecture is proposed that implements these grating advancements in order to support ∼6× higher pulse energies than currently demonstrated. This increase in energy and intensity could have substantial benefits to high-flux secondary sources and enable new applications.

47 OTHER INSTRUMENTATION↗

DOE OSTI2010

Microfluidics without channels: highly-flexible synthesis on a digital-microfluidic chip for production of diverse PET tracers

Positron emission tomography (PET) imaging is used for fundamental studies of living biological organisms and microbial ecosystems in applications ranging from biofuel production to environmental remediation to the study, diagnosis, and treatment monitoring of human disease. Routine access to PET imaging, to monitor biochemical reactions in living organisms in real time, could accelerate a broad range of research programs of interest to DOE. Using PET requires access to short-lived radioactive-labeled compounds that specifically probe the desired living processes. The overall aims of this project were to develop a miniature liquid-handling technology platform (called “microfluidics”) that increases the availability of diverse PET probes by reducing the cost and complexity of their production. Based on preliminary experiments showing that microfluidic chips can synthesis such compounds, we aimed to advance this technology to improve its robustness, increase its flexibility for a broad range of probes, and increase its user-friendliness. Through the research activities of this project, numerous advances were made; Tools were developed to enable the visualization of radioactive materials within microfluidic chips; Fundamental advances were made in the microfluidic chip architecture and fabrication process to increase its robustness and reliability; The microfluidic chip technology was shown to produce useful quantities of an example PET probes, and methods to further increase the output were successfully pursued; A “universal” chip was developed that could produce multiple types of PET probes, enabling the possibility of “on demand” synthesis of different probes; and Operation of the chip was automated to ensure minimal radiation exposure to the operator Based on the demonstrations of promising technical feasibility and performance, the microfluidic chip technology is currently being commercialized. It is anticipated that costs of microfluidic chips can be dramatically reduced in the future by leveraging economies of scale in the microelectronics industry, leading to low cost production of PET probes.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

DOE OSTI2018

Abstract - Cooperative Research and Development Agreement between Penn State University and National Energy Technology Laboratory

This project will use bipolar membranes to produce efficient vapor-phase electrolysis cells for splitting CO 2 to CO and oxygen. CO is a valuable chemical feedstock that can be combined catalytically with hydrogen in the Fischer-Tropsch process to make liquid fuels. CO is arguably the best target for CO 2 reduction since, as a gaseous product, it is easily collected and is relatively immune to membrane crossover losses. The keys to success in this project are to design and synthesize hydrophilic, low resistance bipolar membranes and to create optimized electrode/catalyst/ electrolyte architectures based on these new membranes and advanced catalysts in order to achieve high current density at low overpotentials for CO 2 conversion. High current density is key to achieving industrially-relevant throughput for the process and low overpotentials maintain high overall efficiency for the process.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Cooperative Research and Development Agreement between National Energy Technology Laboratory and The Pennsylvania State University (Final Report)

This project will use bipolar membranes to produce efficient vapor-phase electrolysis cells for splitting CO 2 to CO and oxygen. CO is a valuable chemical feedstock that can be combined catalytically with hydrogen in the Fischer-Tropsch process to make liquid fuels. CO is arguably the best target for CO 2 reduction since, as a gaseous product, it is easily collected and is relatively immune to membrane crossover losses. The keys to success in this project are to design and synthesize hydrophilic, low resistance bipolar membranes and to create optimized electrode/catalyst/electrolyte architectures based on these new membranes and advanced catalysts in order to achieve high current density at low overpotentials for CO 2 conversion. High current density is key to achieving industrially relevant throughput for the process and low overpotentials maintain high overall efficiency for the process.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2026

Scientific Discovery with Physics-Informed System Identification (Abbreviated Report)

My fellowship research focused on making physics-based simulations faster and more useful through machine learning. Many problems in science and engineering are governed by partial differential equations, but high-fidelity simulations are often too expensive to run repeatedly. I worked on improving Latent Space Dynamics Identification (LaSDI), a reduced-order modeling framework that compresses large simulation data sets into a smaller representation and then learns how that representation evolves over time. The motivation was to develop reduced models that remain accurate for more challenging systems, especially when predictions must remain reliable over long time intervals or when the underlying dynamics are more complicated than standard methods can easily handle. I also contributed to related work on Quandary, a high-performance software effort for simulation and control of open quantum systems, before focusing primarily on Latent Space Dynamics Identification methods. The main outcomes of the fellowship were two new algorithms (both of which were published), Rollout-LaSDI and Higher-Order LaSDI, together with supporting work on multi-stage Latent Space Dynamics Identification. Rollout-LaSDI improved long-term prediction by training the model to stay accurate over extended time horizons, and Higher-Order LaSDI broadened the method so it could model systems with higher-order time dynamics. My contributions to multistage Latent Space Dynamics Identification also helped show that its later training stages could be simplified without losing effectiveness, and that this behavior held across different model architectures and training strategies. Taken together, these advances improved the accuracy, flexibility, and practical value of reduced-order modeling tools for computational science.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1983

The Information Adaptive System - A demonstration of real-time onboard image processing

The Information Adaptive System (IAS) program has the objective to develop and demonstrate, at the brassboard level, an architecture which can be used to perform advanced signal procesing functions on board the spacecraft. Particular attention is given to the processing of high-speed multispectral imaging data in real-time, and the development of advanced technology which could be employed for future space applications. An IAS functional description is provided, and questions of radiometric correction are examined. Problems of data packetization are considered along with data selection, a distortion coefficient processor, an adaptive system controller, an image processing demonstration system, a sensor simulator and output data buffer, a test support and demonstration controller, and IAS demonstration operating modes.

Thomas, G. L.↗

NASA NTRS1990

Payload accommodations: Avionics payload support architecture

Technology issues/trade studies; candidate programs; key contacts/facilities: milestones; accomplishments; and major objectives of the payload accommodation are outlined. Topics covered include: avionics payload support architecture; satellite serving; P/L deploy systems and advanced manipulators; advanced telemetry systems; and on-board abort planning. This presentation is represented by viewgraphs only.

Source record↗

NASA NTRS1990

Advanced embedded processing: Present and future

Integrated airframe/propulsion control system architecture is discussed. The main objectives of the program are: design and validation methodology for system architecture; system design; system specification; and small-scale system testing.

Cohen, Gerald C.↗

NASA NTRS1992

Storage needs in future supercomputer environments

The Lawrence Livermore National Laboratory (LLNL) is a Department of Energy contractor, managed by the University of California since 1952. Major projects at the Laboratory include the Strategic Defense Initiative, nuclear weapon design, magnetic and laser fusion, laser isotope separation, and weather modeling. The Laboratory employs about 8,000 people. There are two major computer centers: The Livermore Computer Center and the National Energy Research Supercomputer Center. As we increase the computing capacity of LLNL systems and develop new applications, the need for archival capacity will increase. Rather than quantify that increase, I will discuss the hardware and software architectures that we will need to support advanced applications.

Coleman, Sam↗

NASA NTRS1991

Storage needs in future supercomputer environments

As the computing capacity of the Lawrence Livermore National Laboratory (LLNL) systems is increased and new applications are developed, the need for archival capacity will increase. The hardware and software architectures that will be needed to support advanced applications are discussed. Viewgraphs are included.

Coleman, Sam↗

NASA NTRS1995

Ka-band MMIC subarray technology program (Ka-Mist)

The broad objective of this program was to demonstrate a proof of concept insertion of Monolithic Microwave Integrated Circuit (MMIC) device technology into an innovative (tile architecture) active phased array antenna application supporting advanced EHF communication systems. Ka-band MMIC arrays have long been considered as having high potential for increasing the capability of space, aircraft, and land mobile communication systems in terms of scan performance, data rate, link margin, and flexibility while offering a significant reduction in size, weight, and power consumption. Insertion of MMIC technology into antenna systems, particularly at millimeter wave frequencies using low power and low noise amplifiers in close proximity to the radiating elements, offers a significant improvement in the array transmit efficiency, receive system noise figure, and overall array reliability. Application of active array technology also leads to the use of advanced beamforming techniques that can improve beam agility, diversity, and adaptivity to complex signal environments.

Pottenger, Warren↗