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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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Electronic system automatically focuses camera or spotlight on moving object. Subject is equipped with miniature ultrasonic or radio transmitter; its signal is picked up by two or more detectors, is phase detected and fed into computer which determines position of subject and sends command signals to servo for camera or spotlight.
The authors derive the fundamental strip-mapping SAR (synthetic aperture radar) imaging equations from first principles. They show that the resolution mechanism relies on the geometry of the imaging situation rather than on the Doppler effect. Both the airborne and spaceborne cases are considered. Range processing is discussed by presenting an analysis of pulse compression and formulating a mathematical model of the radar return signal. This formulation is used to obtain the airborne SAR model. The authors study the resolution mechanism and derive the signal processing relations needed to produce a high-resolution image. They introduce spotlight-mode SAR and briefly indicate how polar-format spotlight processing can be used in strip-mapping SAR. They discuss a number of current and future research directions in SAR imaging.
The problem of an ultrasonic reflectivity tomography is similar to that of a spotlight-mode aircraft Synthetic Aperture Radar (SAR) system. The analysis for a circular path spotlight mode SAR in this paper leads to the insight of the system characteristics. It indicates that such a system when operated in a wide bandwidth is capable of achieving the ultimate resolution; one quarter of the wavelength of the carrier frequency. An efficient processing algorithm based on the exact two dimensional spectrum is presented. The results of simulation indicate that the impulse responses meet the predicted resolution performance. Compared to an algorithm previously developed for the ultrasonic reflectivity tomography, the throughput rate of this algorithm is about ten times higher.
Topics discussed during the workshop include: (1) Multinational-Multiple media collections and activities spanning many countries; (2) Multiple media in North American trade and commerce; (3) African spotlight; (4) Europe-Multiple media in national libraries and services; (5) Scandinavian spotlight; (6) Internet update; (7) Multiple media in US federal agencies; (8) Open-source multiple media in US federal agencies; and (9) Multiple media at US federal technical agencies-NIST and NOAA.
In the dynamic realm of atmospheric sciences, the convergence of data science methodologies and open data marks a transformative era, driving research advancements and nurturing aspiring scientists. This abstract highlights two pivotal projects that epitomize open science principles, aligning seamlessly with the session's objective of interdisciplinary synergy and the cultivation of emerging talent. As a NASA-certified data center, our foremost endeavor focuses on enhancing the visibility and traceability of NASA datasets within atmospheric science research. This initiative not only elevates these datasets' prominence but also establishes a robust framework ensuring their credibility in scholarly discourse. By bridging the gap between data sources and research publications, this project serves as an educational catalyst, nurturing a new generation of scholars in open collaboration and dataset authenticity. Concurrently, our second project pioneers an early warning system for flooding events, utilizing machine learning algorithms to predict flooded fractions. Through multi-source data fusion and predictive modeling, this initiative goes beyond forecasting; it embodies the core of open science by enabling proactive risk mitigation strategies. This project not only advances atmospheric sciences but also fosters an environment where young scholars engage in practical, data-driven solutions. These intertwined projects exemplify the fusion of data science with open data solutions, ensuring both the usability of quality datasets and the cultivation of scientific knowledge among emerging scholars. By spotlighting these impactful use cases, our aim is to foster discussions emphasizing the importance of open collaboration, data integrity, and the nurturing of scientific talent in atmospheric sciences." "In the dynamic realm of atmospheric sciences, the convergence of data science methodologies and open data marks a transformative era, driving research advancements and nurturing aspiring scientists. This abstract highlights two pivotal projects that epitomize open science principles, aligning seamlessly with the session's objective of interdisciplinary synergy and the cultivation of emerging talent. As a NASA-certified data center, our foremost endeavor focuses on enhancing the visibility and traceability of NASA datasets within atmospheric science research. This initiative not only elevates these datasets' prominence but also establishes a robust framework ensuring their credibility in scholarly discourse. By bridging the gap between data sources and research publications, this project serves as an educational catalyst, nurturing a new generation of scholars in open collaboration and dataset authenticity. Concurrently, our second project pioneers an early warning system for flooding events, utilizing machine learning algorithms to predict flooded fractions. Through multi-source data fusion and predictive modeling, this initiative goes beyond forecasting; it embodies the core of open science by enabling proactive risk mitigation strategies. This project not only advances atmospheric sciences but also fosters an environment where young scholars engage in practical, data-driven solutions. These intertwined projects exemplify the fusion of data science with open data solutions, ensuring both the usability of quality datasets and the cultivation of scientific knowledge among emerging scholars. By spotlighting these impactful use cases, our aim is to foster discussions emphasizing the importance of open collaboration, data integrity, and the nurturing of scientific talent in atmospheric sciences.
This review spotlights the role of atomic-level modeling in research on metal-organic frameworks (MOFs), especially the key methodologies of density functional theory (DFT), Monte Carlo (MC) simulations, and molecular dynamics (MD) simulations. The discussion focuses on how periodic and cluster-based DFT calculations can provide novel insights into MOF properties, with a focus on predicting structural transformations, understanding thermodynamic properties and catalysis, and providing information or properties that are fed into classical simulations such as force field parameters or partial charges. Classical simulation methods, highlighting force field selection, databases of MOFs for high-throughput screening, and the synergistic nature of MC and MD simulations, are described. By predicting equilibrium thermodynamic and dynamic properties, these methods offer a wide perspective on MOF behavior and mechanisms. Additionally, the incorporation of machine learning (ML) techniques into quantum and classical simulations is discussed. These methods can enhance accuracy, expedite simulation setup, reduce computational costs, as well as predict key parameters, optimize geometries, and estimate MOF stability. By charting the growth and promise of computational research in the MOF field, the aim is to provide insights and recommendations to facilitate the incorporation of computational modeling more broadly into MOF research.
Abstract Expansion of distributed solar photovoltaic (PV) and natural gas‐fired generation capacity in the United States has put a renewed spotlight on methods and tools for power system planning and grid modernization. This article investigates the impact of increasing natural gas‐fired electricity generation assets on installed distributed solar PV systems in the Pennsylvania–New Jersey–Maryland (PJM) Interconnection in the United States over the period 2008–2018. We developed an empirical dynamic panel data model using the system‐generalized method of moments (system‐GMM) estimation approach. The model accounts for the impact of past and current technical, market and policy changes over time, forecasting errors, and business cycles by controlling for PJM jurisdictions‐level effects and year fixed effects. Using an instrumental variable to control for endogeneity, we concluded that natural gas does not crowd out renewables like solar PV in the PJM capacity market; however, we also found considerable heterogeneity. Such heterogeneity was displayed in the relationship between solar PV systems and electricity prices. More interestingly, we found no evidence suggesting any relationship between distributed solar PV development and nuclear, coal, hydro, or electricity consumption. In addition, considering policy effects of state renewable portfolio standards, net energy metering, differences in the PJM market structure, and other demand and cost‐related factors proved important in assessing their impacts on solar PV generation capacity, including energy storage as a non‐wire alternative policy technique. This article is categorized under: Photovoltaics > Economics and Policy Fossil Fuels > Climate and Environment Energy Systems Economics > Economics and Policy
Accidental symmetries in effective field theories can be established by computing and comparing Hilbert series. This invites us to study them with the tools of invariant theory. Applying this technology, we spotlight three classes of accidental symmetries that hold to all orders for non-derivative interactions. They are broken by derivative interactions and become ordinary finite-order accidental symmetries. To systematically understand the origin and the patterns of accidental symmetries, we introduce a novel mathematical construct — a (non-transitive) binary relation between subgroups that we call friendship. Equipped with this, we derive new criteria for all-order accidental symmetries in terms of friends, and criteria for finite-order accidental symmetries in terms of friends ma non troppo. They allow us to verify and identify accidental symmetries more efficiently without computing the Hilbert series. We demonstrate the success of our new criteria by applying them to a variety of sample accidental symmetries, including the custodial symmetry in the Higgs sector of the Standard Model effective field theory.
Here, we compared the oxidation of Ti and Ti-2 at.% Nb at 800°C in Ar-20% O 2 and in sequential 16 O 2 - 18 O 2 atmospheres to clarify the role of niobium in the high-temperature oxidation of titanium. Niobium had no effect on the amount of oxygen dissolved in the metal or on oxygen diffusion in the metal. Instead, niobium enhanced oxidation resistance by segregating to TiO 2 grain boundaries, where it likely slowed outward Ti diffusion. These findings spotlight doping of TiO 2 grain boundaries as a strategy for improving the oxidation resistance of Ti alloys and, more generally, TiO 2 -forming alloys.
Sodium-ion batteries (SIBs) have stepped into the spotlight as a promising alternative to lithium-ion batteries for large-scale energy storage systems. However, SIB electrode materials, in general, have inferior performance than their lithium counterparts because Na + is larger and heavier than Li + . Heterostructure engineering is a promising strategy to overcome this intrinsic limitation and achieve practical SIBs. We provide a brief review of recent progress in heterostructure engineering of electrode materials and research on how the phase interface influences Na + storage and transport properties. Efficient strategies for the design and fabrication of heterostructures (in situ methods) are discussed, with a focus on the heterostructure formation mechanism. The heterostructure's influence on Na + storage and transport properties arises primarily from local distortions of the structure and chemomechanical coupling at the phase interface, which may accelerate ion/electron diffusion, create additional active sites, and bolster structural stability. Finally, we offer our perspectives on the existing challenges, knowledge gaps, and opportunities for the advancement of heterostructure engineering as a means to develop practical, high-performance sodium-ion batteries.
The increasing global emphasis on energy efficiency and sustainability has put heat pump water heaters (HPWHs) in the spotlight as an energy-efficient alternative to traditional water heating systems. However, their widespread adoption is limited by challenges such as insufficient First Hour Rating (FHR), suboptimal control mechanisms, and limited flexibility for demand response operations. Here, to address these limitations, this study proposes an innovative HPWH system integrated with embedded phase change material (PCM)-based thermal energy storage (TES). The research introduces a novel design and control strategy that leverages optimized PCM integration to enhance thermal storage capacity, improve hot water delivery during peak demand, and increase load-shifting potential. A combination of system modeling, performance simulation, and demand response control strategy evaluation was employed to quantify the benefits of PCM integration. Results demonstrate that the proposed PCM-TES HPWH system significantly enhances FHR, with an optimal 7.0 lb. of PCM increasing FHR by over 26 %—from 62 to 78 gal—for a standard 50-gal HPWH. Additionally, under advanced demand response operation using a preheat strategy, the system reduces the percentage of control temperature out-of-band time from 65 % (conventional HPWH) to just 11.6 %, enabling a more stable and efficient hot water supply. This research contributes a novel PCM-embedded HPWH design and control framework that addresses both performance and grid-interactivity challenges. The findings offer a viable pathway to enhancing the operational efficiency, flexibility, and grid responsiveness of residential water heating systems.
The Picochlorum genus is a distinctive eukaryotic green-algal clade that is the focus of several current biotechnological studies. It is capable of extremely rapid growth rates and has exceptional tolerances to high salinity, intense light, and elevated temperatures. Importantly, it has robust stability and high-biomass productivities in outdoor field trials in seawater. These features have propelled Picochlorum into the spotlight as a promising model for both fundamental and biotechnological research. Recently, several genetic tools, including genome editing, were developed for these algae, enabling insights into Picochlorum photophysiology and algal transformations for expanded capabilities. Here, we survey the Picochlorum genus, its genetic toolbox, recently characterized transformants, and discuss the commercial potential of Picochlorum as a salt-water photoautotrophic biocatalyst.
We report crystals are ubiquitous and play an important role in our daily life. Recent studies on properties and formation of crystals have proven the attachment of particle ranging from ion pairs to well-crystallized nanocrystal is one of the most important ways for crystallization. Compared with the monomer-by-monomer (i.e., atoms, ions, or molecules) addition described in longstanding classical theories, so-called nonclassical crystallization pathways are more complex as the non-specific interaction of variation in system free energy and reaction kinetics. In view of the detailed insights into nonclassical crystallization pathways has broadened the scope of research across various disciplines such as geological events, biomineralization mechanisms, environmental remediation, and the development of functional materials, this paper reviews the current state of the art in nonclassical nucleation (the prenucleation clusters pathway, aggregation pathway, etc.) and growth pathways (oriented attachment and random attachment) based on several spotlights. In addition, the observed specific phenomena on crystallization in the last 10 years as well as recent advancements and achievements made on the synthesis of mesocrystals are also elucidated. With implications and perspectives of nonclassical crystallization researches proposed in this paper, this review aims to summarize research advancement regarding crystallizing systems. Emphasis will be placed on novel insights into nonclassical crystallization of materials, which are expected to provide completely new perspectives on the underlying crystallization mechanisms.
Real-time detection of volatile organic compounds (VOCs) is being spotlighted for its importance in environmental monitoring and disease detection from the breath. However, the selective detection of VOCs in a small form factor gas sensor remains a challenge. Here, we present the VOC sensing performance of phthalocyanine (Pc)-functionalized graphene chemiresistors supported by the theoretical prediction of Pc's VOC interactions. Pc functionalization, with and without metalation, was studied parametrically with varying deposition parameters to explore impacts on the gas sensing response toward VOCs as a function of substrate coverage. Sensing data were collected to establish fingerprint signatures for a variety of VOCs. In conclusion, improvement in selectivity is shown by successfully differentiating the VOCs from each other when combined into a gas sensor array tested with acetone, ethanol, formaldehyde, and toluene.
Cu 2 BaSn(S,Se) 4 is currently in the spotlight for prospective environmentally friendly, stable, thin-film solar cell application, with demonstrated device power conversion efficiency (PCE) exceeding 5% for vacuum-deposited absorbers. As suggested by first-principles calculations, experimental studies involving related Cu 2 ZnSn(S,Se) 4 and Cu(In,Ga)(S,Se) 2 absorbers prove that the detailed chemical composition typically plays a sensitive role in altering defects and electronic properties of these complicated compound semiconductors. Herein, the copper composition of Cu 2 BaSn(S,Se) 4 has been systematically modified, employing a solution-based deposition approach, to provide a more complete picture of the phase stability and optoelectronic property sensitivity for this material. X-ray diffraction and scanning electron microscopy show that phase purity is preserved over a film Cu content range of nominally 0.94 ≤ [Cu]/[Ba + Sn] ≤ 1.01. Terahertz spectroscopy and Hall effect measurements reveal that the majority carrier hole density of ~10 13 cm –3 and mobility (~5 cm 2 /V s), as well as the minority carrier lifetime (a bulk lifetime of 180 ps and a surface recombination velocity >106 cm/s), are nominally independent of Cu content. The champion PCEs exceed 4.7% for all copper compositions in the phase-pure region, with a record value of 5.1%, similar to the reported values for record vacuum-deposited devices. Furthermore, these results suggest that Cu 2 BaSn(S,Se) 4 films and solar cells (at the current performance level) may be less sensitive to Cu stoichiometry compared to kesterite materials and therefore may provide a more stable material platform to prepare thin-film solar cells.
Organic–inorganic halide perovskites are well-known for their unique self-healing ability. In the presence of strong external stimuli, such as light, temperature, and moisture, high-energy defects are created which can be healed by removing the perovskite from the degradation source. Furthermore, this self-healing ability has been showcased in devices with recoverable performance and day-and-night cycling operation to dramatically extend the device lifetime and even mechanical durability. However, to date, the mechanistic details and theory around this captivating trait are sparse and convoluted by the complex nature of perovskites. With a clear understanding of the intrinsic self-healing property, perovskite solar cells with extended lifetimes and durability can be designed to realize the large-scale commercialization of perovskite solar cells. Here, we spotlight the relevant degradation and self-healing literature and then propose design strategies to help conceptualize future research.
Abstract. Steady progress in unveiling nature’s long-range charge transport mechanisms in redox proteins, and in the development of versatile self-assembling scaffolds and de novo proteins by design are separate fields that soon may intersect to yield the first artificial bioelectronic wires. Here we summarize compelling developments in these areas that put a spotlight on the prospect of their convergence, featuring in particular recent work by Dai et al. that clearly illustrates success in intentional design with nuanced control, binding multiple c-type hemes into a specific ordered array bearing the essential hallmarks of heme chains in bacterial multiheme cytochromes.
Metastable compounds have greatly expanded the synthesizable compositions of solid-state materials and have attracted enormous amounts of attention in recent years. Especially, mechanochemically enabled metastable materials synthesis has been very successful in realizing cation-disordered materials with highly simple crystal structures, such as rock salts. Application of the same strategy for other structural types, especially for non-close-packed structures, is peculiarly underexplored. Niobium tungsten oxides (NbWOs), a class of materials that have been under the spotlight because of their diverse structural varieties and promising electrochemical and thermoelectric properties, are ideally suited to fill such a knowledge gap. In this work, we develop a new series of metastable NbWOs and realize one with a fully cation-disordered structure. Furthermore, we find that metastable NbWOs transform to a cation-disordered cubic structure when applied as a Li-ion battery anode, highlighting an intriguing non-close-packed–close-packed conversion process, as evidenced in various physicochemical characterizations, in terms of diffraction, electronic, and vibrational structures. Lastly, by comparing the cation-disordered NbWO with other trending cation-disordered oxides, we raise a few key structural features for cation disorder and suggest a few possible research opportunities for this field.