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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 1,207 records · Page 67
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Improving Electronic Conductivity of Layered Oxides through the Formation of Two-Dimensional Heterointerface for Intercalation Batteries

Synthetic strategies for the improvement in electronic conductivities and electrochemical stabilities of transition metal oxide cathodes, which are limiting factors in the performance of commercial intercalation batteries, are required for next-generation, high-performance battery systems. Furthermore, the chemical preintercalation approach, consisting of a combined sequence of a sol–gel process, extended aging, and a hydrothermal treatment, is a versatile, wet synthesis technique that allows for the incorporation of a polar species between the layers of transition metal oxides. Here, formation of a layered 2D δ-C x V 2 O 5 · n H 2 O heterostructure occurs via chemical preintercalation of dopamine molecules between bilayers of vanadium oxide followed by the hydrothermal treatment of the precipitate, leading to carbonization of the organic molecules. The presence of carbon layers within the structure has been confirmed via a combined analysis of scanning electron microscopy, X-ray diffraction, thermogravimetric analysis, Raman spectroscopy, X-ray photoelectron spectroscopy, electrochemical impedance spectroscopy, four-probe conductivity measurements, and scanning transmission electron microscopy characterization. 2D δ-C x V 2 O 5 · n H 2 O heterostructure electrodes demonstrated significantly improved electrochemical performance, particularly at higher current densities, in Li-ion cells. The heterostructure electrodes exhibited 75% of the capacity retention when the current was changed from 20 mA g –1 (206 mAh g –1 ) to 300 mA g –1 (155 mAh g –1 ), while the reference δ-V 2 O 5 · n H 2 O electrodes exhibited only 10% capacity retention in the same experiment. Remarkably, 2D δ-C x V 2 O 5 · n H 2 O heterostructure electrodes demonstrated significantly improved capacity retention (94% after 30 cycles) for bilayered vanadium oxide electrodes in Li-ion cells during galvanostatic cycling at 20 mA g –1 . The improved electrochemical performance, in both extended cycling and rate capability studies, of the 2D δ-C x V 2 O 5 · n H 2 O heterostructure electrodes in the Li-ion system is ascribed to the intermittent formation of carbon layers within the bilayered structure, which leads to increased electronic conductivity and improved structural stability of the heterostructure compared to the reference δ-V 2 O 5 · n H 2 O electrodes.

25 ENERGY STORAGE↗
DOE OSTI2026

Continental-Scale Controls on Hyporheic Respiration Revealed by Knowledge-Guided Machine Learning

Hyporheic zone sediments regulate organic matter turnover and in-stream respiration, yet controls on sediment respiration remain poorly constrained across heterogeneous river networks, limiting prediction of stream metabolism and carbon processing at continental scales. Here, we integrate observations from ~90 river corridors across the United States in the WHONDRS consortium with a knowledge-guided machine learning (KGML) framework that couples thermodynamic rate theory with machine learning to identify dominant controls on hyporheic respiration. Diagnostic analyses show that organic matter concentration and thermodynamic favorability define an upper bound on respiration potential, whereas biological catalytic capacity and physical accessibility jointly govern realized respiration rates through interaction effects. To represent unmeasurable accessibility constraints, we use the mechanistic model as a scaffold for KGML, allowing machine learning to target residual structure not explained by process theory. This hybrid framework improves predictive skill relative to both the mechanistic model alone and fully data-driven models while preserving interpretability. These results indicate that variability in hyporheic respiration is largely mechanistically structured and demonstrate how integrating process theory with explainable AI enhances predictive performance while enabling scalable synthesis of river corridor observations.

Zheng, Jianqiu↗
DOE OSTI2022

Twin-free, directly synthesized MFI nanosheets with improved thickness uniformity and their use in membrane fabrication

Zeolite nanosheets can be used for the fabrication of low-defect-density, thin, and oriented zeolite separation membranes. However, methods for manipulating their morphology are limited, hindering progress toward improved performance. We report the direct synthesis (i.e., without using exfoliation, etching, or other top-down processing) of thin, flat MFI nanosheets and demonstrate their use as high-performance membranes for xylene isomer separations. Our MFI nanosheets were synthesized using nanosheet fragments as seeds instead of the previously used MFI nanoparticles. The obtained MFI nanosheets exhibit improved thickness uniformity and are free of rotational and MEL intergrowths as shown by transmission electron microscopy (TEM) imaging. The nanosheets can form well-packed nanosheet coatings. Upon gel-free secondary growth, the obtained zeolite MFI membranes show high separation performance for xylene isomers at elevated temperature (e.g., p-xylene flux up to 1.5 × 10 –3 mol m –2 s –1 and p-/o-xylene separation factor of ~600 at 250°C).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Chemical and architectural intricacy from nanoscale tetrahedra and their analogues

The tetrahedron, as the simplest platonic shape, is a profound building block with the potential to create intricate superstructures. Noteworthy designs utilizing tetrahedral building blocks include the Sierpiński tetrahedron (the most fundamental three-dimensional fractal), a one-dimensional helical structure known as the tetrahelix, and various crystalline and quasicrystalline packings. Historically, the practicality of tetrahedral superstructures has been evident, providing stable, well-defined frameworks for various constructions, including truss bridges, tower cranes, and electricity transmission line pylons. In the field of self-assembled nanocrystal superlattices, tetrahedral nanocrystals, as building blocks, occupy a unique place among all the possible nanoscale particles. Mathematical models, simulation work, and experimental studies using nanocrystals in the laboratory have suggested that self-assembled structures derived from nanoscale tetrahedral building blocks are notably intricate, giving rise to new horizons of high-entropy nanocrystal superlattices. An important implication from previous works is that such tetrahedral nanocrystal superlattices form through highly delicate interparticle interactions, emphasizing the importance of the fine features of these nanocrystals. In this article, we summarize the advances in superlattices assembled from tetrahedral nanocrystals. Here, we first define the tetrahedron and tetrahedron analogues based on Conway’s transformation and graph theory, underscoring their relevance to the crystallization process producing tetrahedral nanocrystals. Then, we showcase previous reports on the synthesis of tetrahedral nanocrystals and the resulting nanocrystal superstructures. Finally, we conclude by offering insights and perspective into the chemical and architectural intricacy that could emerge from tetrahedral nanocrystals.

Nanostructure↗
DOE OSTI2023

Crystal growth and nucleation at metal-organic framework / solution interfaces

Metal-organic frameworks (MOFs) represent an incredibly diverse class of materials with equally diverse applications in catalysis, separations, and gas storage. Despite the prevalence of MOF structures in the literature, in many cases the synthesis of pure, crystalline MOF materials remains a significant challenge, with failed syntheses often yielding mixed crystalline or non-porous amorphous products. Our recent work aims to enable targeted MOF synthesis by developing a comprehensive and predictive model of the fundamental processes occurring at the MOF-solution interface under synthetically-relevant conditions. Our recent accomplishments include: (i) development and implementation of a graphics processor-accelerated approach to simulation the nucleation of weak electrolytes, and the extension of these methods to large/complex solutes such as MOFs; and (ii) studies of the structure of ZIF interfaces under conditions relevant to crystal growth; and (iii) addressing important open questions in the mechanism of MOF solvent-assisted linker exchange, and important synthetic pathway for MOFs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1964

Speech communications

Analysis and synthesis of speech, and use of procedures for studying human speech processes

SPEECH↗
NASA NTRS1979

Feasibility study on the development of tough, moisture-resistant laminating resins

The potential of cyanate resins as replacement for epoxy resins in composites with graphite fiber reinforcement was investigated in an effort to provide improved moisture resistance and toughness in laminating systems at a projected cost, handleability, and processing requirements equivalent to 400 K (260 F) curing epoxies. Monomer synthesis, formulation, blending, resin preparation, catalysis studies, prepreg preparation, laminate fabrication, and testing are discussed. A graphite fiber reinforced laminate was developed with 95 percent retention of the original 363 K (180 F) flexural strength and 70 percent retention of the 363 K (180 F) short beam shear strength after 500 hour exposure to 95 + 7 relative humidity at 324 K (120 F).

Brand, R. A.↗
NASA NTRS1981

Optical processing for landmark identification

A study of optical pattern recognition techniques, available components and airborne optical systems for use in landmark identification was conducted. A data base of imagery exhibiting multisensor, seasonal, snow and fog cover, exposure, and other differences was assembled. These were successfully processed in a scaling optical correlator using weighted matched spatial filter synthesis. Distinctive data classes were defined and a description of the data (with considerable input information and content information) emerged from this study. It has considerable merit with regard to the preprocessing needed and the image difference categories advanced. A optical pattern recognition airborne applications was developed, assembled and demontrated. It employed a laser diode light source and holographic optical elements in a new lensless matched spatial filter architecture with greatly reduced size and weight, as well as component positioning toleranced.

Casasent, D.↗
NASA NTRS1982

A two-dimensional phase separation on the spherical surface of the metallic glass Au55Pb22.5Sb22.5

Recent experiments indicate that a phase separation in a spherical sample of the metallic glass Au55Pb22.5Sb22.5 occurs near the surface of the sphere. This strongly suggests either a contribution of surface-free energy to the decomposition process or a possible influence of near surface impurities absorbed during synthesis of the sphere. The surface phase separation has been studied as a function of cooling rate of the sphere. At high cooling rates (small sphere sizes), the surface separation disappears altogether suggesting that the surface of the parent liquid droplet is initially homogeneous.

Lee, M. C.↗
NASA NTRS1984

Potential utilization of glass experiments in space

Materials processing in space utilizing the microgravity environment is discussed; glass processing in particular is considered. Attention is given to the processing of glass shells, critical cooling rate and novel glasses, gel synthesis of glasses, immiscibility, surface tension, and glass composites. Soviet glass experiments in space are also enumerated.

Kreidl, N. J.↗
NASA NTRS1988

Synthesis, curing and physical behavior of maleimide terminated poly(arylene ethers)

This paper describes the synthesis of maleimide terminated poly(ether ketones) using the solution imidization process described by Summers et al. (1987). Amorphous poly(arylene ether ketones), as well as poly(arylene ether sulfones, of controlled end group functionalities and molecular weights were synthesized by nucleophilic step polymerization of bisphehol-A phenolates with activated halides, such as 4,4'-difluorobenzophenone, and 'monofunctional' end cappers such as m-aminophenol. The thermal properties of the system included glass transition temperature (Tg) values of 160-170 C, with modulus above Tg proportional to cross-link density, which in turn was reciprocally related to oligomer molecular weight. The measurements of the fracture toughness values showed the materials to be very ductile, with the toughness increasing with oligomer molecular weight.

Lyle, G. D.↗
NASA NTRS1994

Synthesis and characterization of advanced materials for Navy applications

The synthesis of ceramics and ceramic coatings through the sol-gel process has extensive application with the United States Navy and a broad range of potential commercial applications as well. This paper surveys seven specific applications for which the Navy is investigating these advanced materials. For each area, the synthetic process is described and the characteristics of the materials are discussed.

Covino, J.↗
NASA NTRS2004

Combining Model-driven and Schema-based Program Synthesis

We describe ongoing work which aims to extend the schema-based program synthesis paradigm with explicit models. In this context, schemas can be considered as model-to-model transformations. The combination of schemas with explicit models offers a number of advantages, namely, that building synthesis systems becomes much easier since the models can be used in verification and in adaptation of the synthesis systems. We illustrate our approach using an example from signal processing.

Denney, Ewen↗
NASA NTRS2010

Modeling Common-Sense Decisions in Artificial Intelligence

A methodology has been conceived for efficient synthesis of dynamical models that simulate common-sense decision- making processes. This methodology is intended to contribute to the design of artificial-intelligence systems that could imitate human common-sense decision making or assist humans in making correct decisions in unanticipated circumstances. This methodology is a product of continuing research on mathematical models of the behaviors of single- and multi-agent systems known in biology, economics, and sociology, ranging from a single-cell organism at one extreme to the whole of human society at the other extreme. Earlier results of this research were reported in several prior NASA Tech Briefs articles, the three most recent and relevant being Characteristics of Dynamics of Intelligent Systems (NPO -21037), NASA Tech Briefs, Vol. 26, No. 12 (December 2002), page 48; Self-Supervised Dynamical Systems (NPO-30634), NASA Tech Briefs, Vol. 27, No. 3 (March 2003), page 72; and Complexity for Survival of Living Systems (NPO- 43302), NASA Tech Briefs, Vol. 33, No. 7 (July 2009), page 62. The methodology involves the concepts reported previously, albeit viewed from a different perspective. One of the main underlying ideas is to extend the application of physical first principles to the behaviors of living systems. Models of motor dynamics are used to simulate the observable behaviors of systems or objects of interest, and models of mental dynamics are used to represent the evolution of the corresponding knowledge bases. For a given system, the knowledge base is modeled in the form of probability distributions and the mental dynamics is represented by models of the evolution of the probability densities or, equivalently, models of flows of information. Autonomy is imparted to the decisionmaking process by feedback from mental to motor dynamics. This feedback replaces unavailable external information by information stored in the internal knowledge base. Representation of the dynamical models in a parameterized form reduces the task of common-sense-based decision making to a solution of the following hetero-associated-memory problem: store a set of m predetermined stochastic processes given by their probability distributions in such a way that when presented with an unexpected change in the form of an input out of the set of M inputs, the coupled motormental dynamics converges to the corresponding one of the m pre-assigned stochastic process, and a sample of this process represents the decision.

Zak, Michail↗
NASA NTRSDate not supplied

Operational Evaluation of NASA SPoRT Lightning Safety Applications for Impact Based Decision Support Services

The NWS Office in Huntsville is tasked with monitoring and predicting the threat for lightning within its County Warning Area. These impact-based decision support services (IDSS) are provided routinely for aviation operations, irregularly for large-scale, outdoor events, and can have varying safety requirements, such as proximity to location and duration. Lightning monitoring and prediction can require the rapid synthesis of a plethora of data, so products that make this process more efficient and effective are sought by the operational community. The Huntsville NWS Office benefits from close collaboration with the NASA SPoRT Center, which is developing several products to address these operational challenges in concentrated R2O/O2R efforts. One example of this is the StopLight product, which uses Geostationary Lightning Mapper (GLM) flash extent density (FED) to provide an easy-to-interpret visual aid of lightning occurring within the last 30 minutes. The StopLight product shows both the age and location of the last lightning flash within each GLM pixel, which can be particularly useful for IDSS with determining when to resume activities or operations that have been shut down due to lightning. This presentation highlights results of collaboration between NASA SPoRT and NWS Huntsville, including testing of the Stoplight product, and additional experimental products in development. A brief summary of the lightning products are provided while the main focus will discuss product evaluation and forecaster perspective during real-time weather watch activities to support aviation operations and events where IDSS was necessary.

Kristopher White↗
NASA NTRSDate not supplied

Kaona: Deep Searching and Curating Data from Aviation Safety Reporting Systems

Context: Several works in the literature have examined how safety narrative databases can be leveraged to share lessons learned. However, less attention has been given to augmenting existing processes for mining these safety reporting system databases. Aim: In this work, we introduce Kaona: An interface that weaves machine learning in existing aviation safety database mining activities. Method: We provide a use case of search, curation and newsletter writing to showcase how Kaona features build on existing processes and on its own to enhance information retrieval, curation and synthesis of narratives. Results: We created two instances of Kaona internally for evaluation, one using publicly available NASA’s ASRS narratives and another using publicly available C3RS narratives. Data ranged from 1998 to 2024. Conclusion: Our tool provides a new way to explore safety narratives, serving to re-imagine how text databases can benefit of novel information retrieval mechanisms in the era of large language models.

ASRS↗
NASA NTRSDate not supplied

Kaona: Deep Searching and Curating Aviation Safety Reporting Systems

Context: Several works in the literature have examined how safety narrative databases can be leveraged to share lessons learned. However, less attention has been given in augmenting existing processes of safety reporting systems. Aim: In this work, we introduce Kaona: An interface that weaves machine learning in existing aviation safety reporting systems activities. Method: We provide a use case of search, curation and newsletter writing to showcase how Kaona features build on existing processes and on its own to enhance information retrieval, curation and synthesis of narratives. Results: We created two instances of Kaona internally for evaluation, one using all public NASA's ASRS narratives and another using all public C3RS narratives. Data ranged from 1998 to 2024. Conclusion: Our tool provides a new way to explore safety narratives, serving to re-imagine how text databases can benefit of novel information retrieval mechanisms in the era of large language models.

asrs↗