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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 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
NASA NTRS2002

Innovations in Mission Architectures for Human and Robotic Exploration Beyond Low Earth Orbit

Through the application of advanced technologies, mission concepts, and new ideas in combining capabilities, architectures for missions beyond Earth orbit have been dramatically simplified. These concepts enable a stepping stone approach to discovery driven, technology enabled exploration. Numbers and masses of vehicles required are greatly reduced, yet enable the pursuit of a broader range of objectives. The scope of missions addressed range from the assembly and maintenance of arrays of telescopes for emplacement at the Earth-Sun L2, to Human missions to asteroids, the moon and Mars. Vehicle designs are developed for proof of concept, to validate mission approaches and understand the value of new technologies. The stepping stone approach employs an incremental buildup of capabilities; allowing for decision points on exploration objectives. It enables testing of technologies to achieve greater reliability and understanding of costs for the next steps in exploration.

Cooke, Douglas R.↗
DOE OSTI2018

Role of Interfaces at Nano-Architectured Photocatalysts for Hydrogen Production from Water Splitting

Hydrogen has been nominated as an ideal energy carrier to replace the heavily engaged fossil fuels. Photocatalytic hydrogen production from the splitting of water is the most energy effective and environmentally preservative strategy. This chapter summarizes the basic principles of the photocatalytic hydrogen evolution reaction (HER) from the splitting of water with focus on the role of interfaces in nanostructured photocatalysts. We review the historical development of photocatalytic water splitting systems consisting of various types of heterojunctions that benefit the photogenerated charge carrier separation during photocatalytic processes. These “interfaces” are generally found in metal–semiconductor and semiconductor–semiconductor composite catalysts built upon nano-architectures made possible with recent advances in nanomaterial synthesis. The mechanisms are also discussed for the enhanced photocatalytic HER yield over the various interfaces in the composite photocatalysts.

Peng, Rui↗
DOE OSTI2026

Through‐Plane Conductive Hydrophobic Electrodes for CO 2 Electrolysis to Ethylene

Copper catalyst gas diffusion electrodes (GDEs) have demonstrated unique electrochemical selectivity converting CO 2 to C 2 -hydrocarbons such as ethylene and ethanol but have been challenged by their hydrophobic chemical stability and internal electrical resistance leading to low energy efficiency. Carbon-supported GDEs have low electrical resistance but lack sufficient stability at industrially relevant current densities. While polymer-supported GDEs have improved hydrophobicity, they also display high in-plane electrical resistance, particularly at industrial scales. Here, in this work, we demonstrate a composite gas diffusion layer that combines hydrophobic porous polymers with an electrically conductive backbone addressing these core gas diffusion electrode (GDE) scaling challenges. We investigate the material properties of standalone porous perfluoropolyether (PFPE) polymers, including porosity and surface morphology, under varying processing conditions and then incorporate these polymers into a porous copper foam. This composite enhances the mechanical rigidity necessary for cell assembly and provides a through-plane electrical conduction path to reduce electrical resistive losses. This enhanced PFPE composite GDE displays efficient CO 2 reduction, achieving 15% ethylene energy efficiency at 100 cm 2 . These findings contribute to the development of advanced catalyst materials and electrode architectures and promote scalable strategies for electrochemical conversion of CO 2 into high-value carbon products.

Chemistry↗
DOE OSTI2018

Long-distance propagation of short-wavelength spin waves

Recent years have witnessed a rapidly growing interest in exploring the use of spin waves for information transmission and computation toward establishing a spin-wave-based technology that is not only significantly more energy efficient than the CMOS technology, but may also cause a major departure from the von-Neumann architecture by enabling memory-in-logic and logic-in-memory architectures. A major bottleneck of advancing this technology is the excitation of spin waves with short wavelengths, which is a must because the wavelength dictates device scalability. Here, we report the discovery of an approach for the excitation of nm-wavelength spin waves. The demonstration uses ferromagnetic nanowires grown on a 20-nm-thick Y 3 Fe 5 O 12 film strip. The propagation of spin waves with a wavelength down to 50 nm over a distance of 60,000 nm is measured. The measurements yield a spin-wave group velocity as high as 2600 m s –1 , which is faster than both domain wall and skyrmion motions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2012

Conformal Ni-silicide formation over three-dimensional device structures

This letter reports on conformal formation of ultrathin Ni-silicide films over a three-dimension structure relevant to the most advanced tri-gate transistor architecture. This is achieved by combining ionization of the sputtered Ni atoms with application of an appropriate bias to the Si substrate during the sputter-deposition of Ni films. In comparison, use of ordinary DC sputtering for Ni deposition results in thinner or less uniform silicide films on the vertical sidewalls than on the top surface of the three-dimensional structure. The roughened Si sidewall surface is ascribed to be responsible for a deteriorated thermal stability of the resultant silicide films.

36 MATERIALS SCIENCE↗
DOE OSTI2023

TAMM: Tensor algebra for many-body methods

Tensor algebra operations such as contractions in computational chemistry consume a significant fraction of the computing time on large-scale computing platforms. The widespread use of tensor contractions between large multi-dimensional tensors in describing electronic structure theory has motivated the development of multiple tensor algebra frameworks targeting heterogeneous computing platforms. In this paper, we present Tensor Algebra for Many-body Methods (TAMM), a framework for productive and performance-portable development of scalable computational chemistry methods. TAMM decouples the specification of the computation from the execution of these operations on available high-performance computing systems. With this design choice, the scientific application developers (domain scientists) can focus on the algorithmic requirements using the tensor algebra interface provided by TAMM, whereas high-performance computing developers can direct their attention to various optimizations on the underlying constructs, such as efficient data distribution, optimized scheduling algorithms, and efficient use of intra-node resources (e.g., graphics processing units). The modular structure of TAMM allows it to support different hardware architectures and incorporate new algorithmic advances. We describe the TAMM framework and our approach to the sustainable development of scalable ground- and excited-state electronic structure methods. We present case studies highlighting the ease of use, including the performance and productivity gains compared to other frameworks.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

High-throughput characterization, correlation, and mapping of leaf photosynthetic and functional traits in the soybean ( Glycine max ) nested association mapping population

We report photosynthesis is a key target to improve crop production in many species including soybean [Glycine max (L.) Merr.]. A challenge is that phenotyping photosynthetic traits by traditional approaches is slow and destructive. There is proof-of-concept for leaf hyperspectral reflectance as a rapid method to model photosynthetic traits. However, the crucial step of demonstrating that hyperspectral approaches can be used to advance understanding of the genetic architecture of photosynthetic traits is untested. To address this challenge, we used full-range (500–2,400 nm) leaf reflectance spectroscopy to build partial least squares regression models to estimate leaf traits, including the rate-limiting processes of photosynthesis, maximum Rubisco carboxylation rate, and maximum electron transport. In total, 11 models were produced from a diverse population of soybean sampled over multiple field seasons to estimate photosynthetic parameters, chlorophyll content, leaf carbon and leaf nitrogen percentage, and specific leaf area (with R 2 from 0.56 to 0.96 and root mean square error approximately <10% of the range of calibration data). We explore the utility of these models by applying them to the soybean nested association mapping population, which showed variability in photosynthetic and leaf traits. Genetic mapping provided insights into the underlying genetic architecture of photosynthetic traits and potential improvement in soybean. Notably, the maximum Rubisco carboxylation rate mapped to a region of chromosome 19 containing genes encoding multiple small subunits of Rubisco. We also mapped the maximum electron transport rate to a region of chromosome 10 containing a fructose 1,6-bisphosphatase gene, encoding an important enzyme in the regeneration of ribulose 1,5-bisphosphate and the sucrose biosynthetic pathway. The estimated rate-limiting steps of photosynthesis were low or negatively correlated with yield suggesting that these traits are not influenced by the same genetic mechanisms and are not limiting yield in the soybean NAM population. Leaf carbon percentage, leaf nitrogen percentage, and specific leaf area showed strong correlations with yield and may be of interest in breeding programs as a proxy for yield. This work is among the first to use hyperspectral reflectance to model and map the genetic architecture of the rate-limiting steps of photosynthesis.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

XaaS: Acceleration as a Service to Enable Productive High-Performance Cloud Computing

High-performance computing (HPC) and the cloud have evolved independently, specializing their innovations into performance or productivity. Acceleration as a Service (XaaS) is a recipe to empower both fields with a shared execution platform that provides transparent access to computing resources, regardless of the underlying cloud or HPC service provider. Bridging HPC and cloud advancements, XaaS presents a unified architecture built on performance-portable containers. Here, our converged model concentrates on low-overhead, high-performance communication and computing, targeting resource-intensive workloads from climate simulations to machine learning. XaaS lifts the restricted allocation model of Function as a Service (FaaS), allowing users to benefit from the flexibility and efficient resource utilization of serverless computing while supporting long-running and performance-sensitive workloads from HPC.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Cryo-EM analysis of S. aureus TarL, a polymerase in wall teichoic acid biogenesis central to virulence and antibiotic resistance

Wall teichoic acid (WTA), a covalent adduct of Gram-positive bacterial cell wall peptidoglycan, contributes directly to virulence and antibiotic resistance in pathogenic species. Polymerization of the Staphylococcus aureus WTA ribitol-phosphate chain is catalyzed by TarL, a member of the largely uncharacterized TagF-like family of membrane-associated enzymes. We report the cryo–electron microscopy structure of TarL, showing a tetramer that forms an extensive membrane-binding platform of monotopic helices. TarL is composed of an amino-terminal immunoglobulin-like domain and a carboxyl-terminal glycosyltransferase-B domain for ribitol-phosphate polymerization. The active site of the latter is complexed to donor substrate cytidine diphosphate–ribitol, providing mechanistic insights into the catalyzed phosphotransfer reaction. Furthermore, the active site is surrounded by electropositive residues that serve to retain the lipid-linked acceptor for polymerization. Our data advance general insight into the architecture and membrane association of the still poorly characterized monotopic membrane protein class and present molecular details of ribitol-phosphate polymerization that may aid in the design of new antimicrobials.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2011

Nanoparticle superlattice engineering with DNA.

A current limitation in nanoparticle superlattice engineering is that the identities of the particles being assembled often determine the structures that can be synthesized. Therefore, specific crystallographic symmetries or lattice parameters can only be achieved using specific nanoparticles as building blocks (and vice versa). We present six design rules that can be used to deliberately prepare nine distinct colloidal crystal structures, with control over lattice parameters on the 25- to 150-nanometer length scale. These design rules outline a strategy to independently adjust each of the relevant crystallographic parameters, including particle size (5 to 60 nanometers), periodicity, and interparticle distance. As such, this work represents an advance in synthesizing tailorable macroscale architectures comprising nanoscale materials in a predictable fashion.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Lustre Unveiled: Evolution, Design, Advancements, and Current Trends

The Lustre filesystem serves as a vital element in high-performance parallel storage, meeting the rising demands of scientific, research, and enterprise environments. Widely deployed across HPC environments, ranging from small-scale applications in AI/ML, to domains like oil and gas, drug discovery, and meteorology, and manufacturing, Lustre addresses the universal challenge of efficiently accessing vast and ever-increasing volumes of data. Lustre is the filesystem of choice on six out of the top 10 fastest supercomputers in the world today, over 65% of the top 100, and also for over 60% of the top 500. Despite its widespread popularity, there is a lack of a complete and up-to-date reference, covering Lustre’s evolution, design, and various advancements made over the years. In this journal, we aim to fill this gap by providing a comprehensive journey of Lustre, including its history with significant contributions to HPC, detailed architecture and design elements, exploration of advancements added through its evolution, and future directions. Additionally, we present a comparison of Lustre with other prominent storage technologies of the era. To illustrate the current state of Lustre, we analyze several filesystem trends, including utilization, performance, and usage patterns on Orion, the Lustre filesystem on the first exascale supercomputer Frontier. We hope that this journal serves as a comprehensive educational reference for the current and future generations interested in HPC filesystem storage aspects.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Quantum light: creation, integration, and applications

In today’s rapidly evolving quantum landscape, the generation and manipulation of quantum light not only represent fundamental challenges but also herald unprecedented opportunities in communication, computing, sensing, and imaging. This special issue brings together a collection of contributions that span the entire journey, from the creation of quantum light using novel materials and emitters to its seamless integration into photonic architectures and eventual deployment in advanced quantum applications. This special issue, “Quantum Light: Creation, Integration, and Applications,” features a collection of three review articles, five perspectives, and 23 original research papers, highlighting both the timeliness of the topic and the remarkable breadth and richness of ongoing advancements in the field.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2021

Randomized Algorithms for Scientific Computing (RASC)

Randomized algorithms have propelled advances in artificial intelligence (AI) and represent a foundational research area in advancing AI for Science. Future advancements in DOE Office of Science priority areas such as climate science, astrophysics, fusion, advanced materials, combustion, and quantum computing all require randomized algorithms for surmounting challenges of complexity, robustness, and scalability. Advances in data collection and numerical simulation have changed the dynamics of scientific research and motivate the need for randomized algorithms. For instance, advances in imaging technologies such as X-ray ptychography, electron microscopy, electron energy loss spectroscopy, or adaptive optics lattice light-sheet microscopy collect hyperspectral imaging and scattering data in terabytes, at breakneck speed enabled by state-of-the-art detectors. The data collection is exceptionally fast compared with its analysis. Likewise, advances in high-performance architectures have made exascale computing a reality and changed the economies of scientific computing in the process. Floating-point operations that create data are essentially free in comparison with data movement. Thus far, most approaches have focused on creating faster hardware. Ironically, this faster hardware has exacerbated the problem by making data still easier to create. Under such an onslaught, scientists often resort to heuristic deterministic sampling schemes (e.g., low-precision arithmetic, sampling every nth element) and sacrifice potentially valuable accuracy. Dramatically better results can be achieved via randomized algorithms, reducing the data size as much as or more than naive deterministic subsampling can achieve, while retaining the high accuracy of computing on the full data set. By randomized algorithms we mean those algorithms that employ some form of randomness in internal algorithmic decisions to accelerate time to solution, increase scalability, or improve reliability. Examples include matrix sketching for solving large-scale least-squares problems (see Figure 1) and stochastic gradient descent for training machine learning models. We are not recommending heuristic methods but rather randomized algorithms that have certificates of correctness and probabilistic guarantees of optimality and near-optimality. Such approaches can be useful beyond acceleration, for example, in understanding how to avoid measure zero worst-case scenarios that plague methods such as QR matrix factorization.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Challenges for Megawatt-Scale Artificial Intelligence Rack Infrastructure

As artificial intelligence (AI) computing densities continue to increase, industry is pursuing megawatt-scale rack architectures that require tightly coordinated advances in electrical power delivery, thermal management, operations, and infrastructure integration. This document summarizes the primary technical challenges for achieving this target.

Nawaz, Kashif [ORNL] (ORCID:0000000251612491)↗
DOE OSTI2022

PyZebrascope: An Open-Source Platform for Brain-Wide Neural Activity Imaging in Zebrafish

Understanding how neurons interact across the brain to control animal behaviors is one of the central goals in neuroscience. Recent developments in fluorescent microscopy and genetically-encoded calcium indicators led to the establishment of whole-brain imaging methods in zebrafish, which record neural activity across a brain-wide volume with single-cell resolution. Pioneering studies of whole-brain imaging used custom light-sheet microscopes, and their operation relied on commercially developed and maintained software not available globally. Hence it has been challenging to disseminate and develop the technology in the research community. Here, we present PyZebrascope, an open-source Python platform designed for neural activity imaging in zebrafish using light-sheet microscopy. PyZebrascope has intuitive user interfaces and supports essential features for whole-brain imaging, such as two orthogonal excitation beams and eye damage prevention. Its camera module can handle image data throughput of up to 800 MB/s from camera acquisition to file writing while maintaining stable CPU and memory usage. Its modular architecture allows the inclusion of advanced algorithms for microscope control and image processing. As a proof of concept, we implemented a novel automatic algorithm for maximizing the image resolution in the brain by precisely aligning the excitation beams to the image focal plane. PyZebrascope enables whole-brain neural activity imaging in fish behaving in a virtual reality environment. Thus, PyZebrascope will help disseminate and develop light-sheet microscopy techniques in the neuroscience community and advance our understanding of whole-brain neural dynamics during animal behaviors.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

Has the Sun Set on Quantum Dot-Sensitized Solar Cells?

This is a reminder, a review and a look toward the future prospects for quantum dot-sensitized solar cells - a reminder of the highly viable, energy-efficient solar cells achievable. This is also a review of ground-breaking devices and their similarities to the near unity photon-to-electron mechanisms of photosynthesis; a look toward architectures that capitalize on the advances observed in previous work.

14 SOLAR ENERGY↗
NASA NTRS1984

Design implications from AFTI/F-16 flight test

Advanced fighter technologies are evolving into highly complex systems. Flight controls are being integrated with advanced avionics to achieve a total system. The advanced fighter technology integration (AFTI) F-16 aircraft is an example of a highly complex digital flight control system integrated with advanced avionics and cockpit. The architecture of these new systems involves several general issues. The use of dissimilar backup modes if the primary system fails requires the designer to trade off system simplicity and capability. This tradeoff is evident in the AFTI/F-16 aircraft with its limited stability and fly-by-wire digital flight control systems. In case of a generic software failure, the backup or normal mode must provide equivalent envelope protection during the transition to degraded flight control. The complexity of systems like the AFTI/F-16 system defines a second design issue, which can be divided into two segments: the effect on testing, and the pilot's ability to act correctly in the limited time available for cockpit decisions. The large matrix of states possible with the AFTI/F-16 flight control system illustrates the difficulty of both testing the system and choosing real-time pilot actions.

Ishmael, S. D.↗
NASA NTRS1991

Analysis of an initial lunar outpost life support system preliminary design

A preliminary design of a life-support system (LSS) was developed as part of an ongoing comprehensive trade study of advanced processor technologies and system architectures for an initial lunar outpost. The design is based on a mission scenario requiring intermittent occupation of a lunar-surface habitat by a crew of four. It incorporates physiochemical process technologies that were considered for Space Station Freedom. A system-level simulation model of the design was developed to obtain steady-state material balances for each LSS processor. The mass-flow rate predictions were used to obtain estimates of the LSS mass, volume, and power consumption by means of processor-sizing correlations that were extrapolated from Space Station Freedom processor designs. The results were used to analyze the impacts of varying crew size, mission duration, processor-operation strategy, and crew-cabin loads on the LSS mass, average power consumption, volume, periodic resupply mass, and waste-accumulation rates. The merits of the design were quantified relative to an open-loop LSS, and the implications of this assessment for future LSS research and technology development were identified.

Ballin, Mark G.↗