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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

A NEW DETERMINATION OF THE BINDING ENERGY OF ATOMIC OXYGEN ON DUST GRAIN SURFACES: EXPERIMENTAL RESULTS AND SIMULATIONS

The energy to desorb atomic oxygen from an interstellar dust grain surface, E{sub des}, is an important controlling parameter in gas-grain models; its value impacts the temperature range over which oxygen resides on a dust grain. However, no prior measurement has been done of the desorption energy. We report the first direct measurement of E{sub des} for atomic oxygen from dust grain analogs. The values of E{sub des} are 1660 ± 60 and 1850 ± 90 K for porous amorphous water ice and for a bare amorphous silicate film, respectively, or about twice the value previously adopted in simulations of the chemical evolution of a cloud. We use the new values to study oxygen chemistry as a function of depth in a molecular cloud. For n = 10{sup 4} cm{sup −3} and G{sub 0} = 10{sup 2} (G{sub 0} = 1 is the average local interstellar radiation field), the main result of the adoption of the higher oxygen binding energy is that H{sub 2}O can form on grains at lower visual extinction A{sub V}, closer to the cloud surface. A higher binding energy of O results in more formation of OH and H{sub 2}O on grains, which are subsequently desorbed by far-ultraviolet radiation, with consequences for gas-phase chemistry. For higher values of n and G{sub 0}, the higher binding energy can lead to a large increase in the column of H{sub 2}O but a decrease in the column of O{sub 2}.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Interactive XCMS Online: Simplifying Advanced Metabolomic Data Processing and Subsequent Statistical Analyses

XCMS Online (xcmsonline.scripps.edu) is a cloud-based informatic platform designed to process and visualize mass-spectrometry-based, untargeted metabolomic data. Initially, the platform was developed for two-group comparisons to match the independent, “control” versus “disease” experimental design. Here, we introduce an enhanced XCMS Online interface that enables users to perform dependent (paired) two-group comparisons, meta-analysis, and multigroup comparisons, with comprehensive statistical output and interactive visualization tools. Newly incorporated statistical tests cover a wide array of univariate analyses. Multigroup comparison allows for the identification of differentially expressed metabolite features across multiple classes of data while higher order meta-analysis facilitates the identification of shared metabolic patterns across multiple two-group comparisons. Given the complexity of these data sets, we have developed an interactive platform where users can monitor the statistical output of univariate (cloud plots) and multivariate (PCA plots) data analysis in real time by adjusting the threshold and range of various parameters. On the interactive cloud plot, metabolite features can be filtered out by their significance level (p-value), fold change, mass-to-charge ratio, retention time, and intensity. The variation pattern of each feature can be visualized on both extracted-ion chromatograms and box plots. The interactive principal component analysis includes scores, loadings, and scree plots that can be adjusted depending on scaling criteria. The utility of XCMS functionalities is demonstrated through the metabolomic analysis of bacterial stress response and the comparison of lymphoblastic leukemia cell lines.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Dynamical observation and detailed description of catalysts under strong metal–support interaction

Understanding the structures of catalysts under realistic conditions with atomic precision is crucial to design better materials for challenging transformations. Under reducing conditions, certain reducible supports migrate onto supported metallic particles and create strong metal–support states that drastically change the reactivity of the systems. The details of this process are still unclear and preclude its thorough exploitation. Here, we report an atomic description of a palladium/titania (Pd/TiO 2 ) system by combining state-of-the-art in situ transmission electron microscopy and density functional theory (DFT) calculations with structurally defined materials, in which we visualize the formation of the overlayers at the atomic scale under atmospheric pressure and high temperature. We show that an amorphous reduced titania layer is formed at low temperatures, and that crystallization of the layer into either mono- or bilayer structures is dictated by the reaction environment and predicted by theory. Moreover, it occurs in combination with a dramatic reshaping of the metallic surface facets.

36 MATERIALS SCIENCE↗

Direct observation of mineral–organic composite formation reveals occlusion mechanism

Manipulation of inorganic materials with organic macromolecules enables organisms to create biominerals such as bones and seashells, where occlusion of biomacromolecules within individual crystals generates superior mechanical properties. Current understanding of this process largely comes from studying the entrapment of micron-size particles in cooling melts. Here, by investigating micelle incorporation in calcite with atomic force microscopy and micromechanical simulations, we show that different mechanisms govern nanoscale occlusion. By simultaneously visualizing the micelles and propagating step edges, we demonstrate that the micelles experience significant compression during occlusion, which is accompanied by cavity formation. This generates local lattice strain, leading to enhanced mechanical properties. Furthermore, these results give new insight into the formation of occlusions in natural and synthetic crystals, and will facilitate the synthesis of multifunctional nanocomposite crystals.

36 MATERIALS SCIENCE↗

Sparse Symmetric Format for Tucker Decomposition

Tensor-based methods are receiving renewed attention in recent years due to their prevalence in diverse real-world applications. There is considerable literature on tensor representations and algorithms for tensor decompositions, both for dense and sparse tensors. Many applications in hypergraph analytics, machine learning, psychometry, and signal processing result in tensors that are both sparse and symmetric, making them an important class for further study. Similar to the critical Tensor Times Matrix chain operation (TTM c ) in general sparse tensors, the $\underline{S}$ parse $\underline{S}$ ymmetric $\underline{T}$ ensor $\underline{T}$ imes $\underline{S}$ ame $\underline{M}$ atrix $\underline{c}$ hain (S 3 TTM c ) operation is compute and memory intensive due to high tensor order and the associated factorial explosion in the number of non-zeros. We present the novel Compressed Sparse Symmetric (CSS) format for sparse symmetric tensors, along with an efficient parallel algorithm for the S 3 TTM c operation. We theoretically establish that S 3 TTM c on CSS achieves a better memory versus run-time trade-off compared to state-of-the-art implementations, and visualize the variation of the performance gap over the parameter space. We demonstrate experimental findings that confirm these results and achieve up to 2.72× speedup on synthetic and real datasets. The scaling of the algorithm on different test architectures is also showcased to highlight the effect of machine characteristics on algorithm performance.

42 ENGINEERING↗

Detecting Cage Crossing and Filling Clusters of Magnesium and Carbon Atoms in Zeolite SSZ-13 with Atom Probe Tomography

The conversion of methanol to valuable hydrocarbon molecules is of great commercial interest, as the process serves as a sustainable alternative for the production of, for instance, the base chemicals for plastics. The reaction is catalyzed by zeolite materials. By the introduction of magnesium as a cationic metal, the properties of the zeolite, and thereby the catalytic performance, are changed. With atom probe tomography (APT), nanoscale relations within zeolite materials can be revealed: i.e., crucial information for a fundamental mechanistic understanding. We show that magnesium forms clusters within the cages of zeolite SSZ-13, while the framework elements are homogeneously distributed. These clusters of just a few nanometers were analyzed and visualized in 3-D. Magnesium atoms seem to initially be directed to the aluminum sites, after which they aggregate and fill one or two cages in the zeolite SSZ-13 structure. The presence of magnesium in zeolite SSZ-13 increases the lifetime as well as the propylene selectivity. By using operando UV–vis spectroscopy and X-ray diffraction techniques, we are able to show that these findings are related to the suppression of aromatic intermediate products, while maintaining the formation of polyaromatic compounds. Further nanoscale analysis of the spent catalysts showed indications of magnesium redistribution after catalysis. Unlike zeolite H-SSZ-13, for which only a homogeneous distribution of carbon was found, carbon can be either homogeneously or heterogeneously distributed within zeolite Mg-SSZ-13 crystals as the magnesium decreases the coking rate. Carbon clusters were isolated, visualized, and analyzed and were assumed to be polyaromatic compounds. Small one-cage-filling polyaromatic compounds were identified; furthermore, large-cage-crossing aromatic molecules were found by isolating large coke clusters, demonstrating the unique coking mechanism in zeolite SSZ-13. Short-length-scale evidence for the formation of polyaromatic compounds at acid sites is discovered, as clear nanoscale relations between aluminum and carbon atoms exist.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

In situ nanoscale imaging of moiré superlattices in twisted van der Waals heterostructures

Abstract Direct visualization of nanometer-scale properties of moiré superlattices in van der Waals heterostructure devices is a critically needed diagnostic tool for study of the electronic and optical phenomena induced by the periodic variation of atomic structure in these complex systems. Conventional imaging methods are destructive and insensitive to the buried device geometries, preventing practical inspection. Here we report a versatile scanning probe microscopy employing infrared light for imaging moiré superlattices of twisted bilayers graphene encapsulated by hexagonal boron nitride. We map the pattern using the scattering dynamics of phonon polaritons launched in hexagonal boron nitride capping layers via its interaction with the buried moiré superlattices. We explore the origin of the double-line features imaged and show the mechanism of the underlying effective phase change of the phonon polariton reflectance at domain walls. The nano-imaging tool developed provides a non-destructive analytical approach to elucidate the complex physics of moiré engineered heterostructures.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

A Finite Element Method for Compressible and Turbulent Multiphase Flow Instabilities with Heat Transfer

We present a new finite element framework for modeling compressible, turbulent multiphase flows with heat transfer. For two-fluid systems with a free surface, the Volume of Fluid (VOF) method is implemented without the need for interface reconstruction, while turbulence is resolved using a dynamic Vreman large eddy simulation (LES) model. Unlike most two-phase VOF studies, which neglect heat transfer, the present approach incorporates energy transport equations within the VOF formulation to account for heat exchange, an effect particularly important in turbulent flows. Conjugate heat transfer is often challenging in finite volume methods, which require explicit specification of heat fluxes at the solid–fluid interface, limiting accuracy and predictive capability. By contrast, the finite element formulation does not require heat flux inputs, allowing more accurate and robust simulation of heat transfer between solids and fluids. The method is demonstrated through three representative cases. First, a two-fluid instability with a single-mode perturbation is simulated and validated against analytical growth rates. Second, conjugate heat transfer is examined in a high-temperature flow over a cold metal cylinder, with validation performed both quantitatively—via pressure coefficient comparisons with experimental data—and qualitatively using vector field topology. Finally, compressible spray injection and breakup are modeled, demonstrating the ability of the framework to capture interfacial dynamics and atomization under turbulent, high-speed conditions. In the compressible spray injection and breakup case, the results indicate that the finite element formulation achieved higher predictive accuracy and robustness than the finite-volume method. With the same mesh resolution, the FEM reduced the root mean square error (RMSE) and mean absolute percentage error (MAPE) from 6.96 mm and 26.0% (for the FVM) to 4.85 mm and 12.7%, respectively, demonstrating improved accuracy and robustness in capturing interfacial dynamics and heat transfer. The study also introduced vector field topology to visualize and interpret coherent flow structures and instabilities, offering insights beyond conventional scalar-field analyses.

97 MATHEMATICS AND COMPUTING↗

Repulsive tip tilting as the dominant mechanism for hydrogen bond-like features in atomic force microscopy imaging

Experimental atomic force microscopy (AFM) studies have reported distinct features in regions with little electron density for various organic systems. These unexpected features have been proposed to be a direct visualization of intermolecular hydrogen bonding. Here, we apply a computational method using ab initio real-space pseudopotentials along with a scheme to account for tip tilting to simulate AFM images of the 8-hydroxyquinoline dimer and related systems to develop an understanding of the imaging mechanism for hydrogen bonds. We find that contrast for the observed “hydrogen bond” feature comes not from the electrostatic character of the bonds themselves but rather from repulsive tip tilting induced by neighboring electron-rich atoms.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Extraction and Analysis of Time Series Data from Building Automation Systems Using Large Language Models

Semantic schemas like Haystack 4, Brick and ASHRAE standard 223 enable the structured, standardized, and machine-readable representation of building data, facilitating interoperability, data integration, and advanced analytics. However, extracting information from these models requires specialized expertise in SPARQL and other programming languages, skills that are not commonly found among building professionals. Recent advancements in Large Language Models (LLMs), such as ChatGPT, enable the construction of queries using natural language, making it easier for individuals to interact with these systems in a manner that resembles everyday speech. However, these methods have not yet been tested on building semantic ontologies. This paper introduces a novel workflow and tool for enabling users to ask questions about a specific building's data, using natural language and receive answers automatically generated by GPT-4o. Our approach integrates semantic ontologies with advanced LLM capabilities to automate three critical steps: (1) generating SPARQL queries to retrieve time series references from ontological models, (2) extracting the corresponding time series data from the Building Automation System, and (3) performing computations and visualizations tailored to the user's query. The proposed method simplifies access to BAS data, allowing both domain experts and non-specialists to conduct sophisticated analyses without needing extensive technical knowledge of semantic web technologies. By demonstrating this pipeline, we facilitate more accessible and scalable data-driven decision-making in building operations and management.

Mulayim, Ozan Baris↗

Extraction and Analysis of Time Series Data from Building Automation Systems Using Large Language Models

Semantic schemas like Haystack 4, Brick and ASHRAE standard 223 enable the structured, standardized, and machine-readable representation of building data, facilitating interoperability, data integration, and advanced analytics. However, extracting information from these models requires specialized expertise in SPARQL and other programming languages, skills that are not commonly found among building professionals. Recent advancements in Large Language Models (LLMs), such as ChatGPT, enable the construction of queries using natural language, making it easier for individuals to interact with these systems in a manner that resembles everyday speech. However, these methods have not yet been tested on building semantic ontologies. This paper introduces a novel workflow and tool for enabling users to ask questions about a specific building's data, using natural language and receive answers automatically generated by GPT-4o. Our approach integrates semantic ontologies with advanced LLM capabilities to automate three critical steps: (1) generating SPARQL queries to retrieve time series references from ontological models, (2) extracting the corresponding time series data from the Building Automation System, and (3) performing computations and visualizations tailored to the user's query. The proposed method simplifies access to BAS data, allowing both domain experts and non-specialists to conduct sophisticated analyses without needing extensive technical knowledge of semantic web technologies. By demonstrating this pipeline, we facilitate more accessible and scalable data-driven decision-making in building operations and management.

Mulayim, Ozan Baris↗

A Multi-modal Approach to Understanding Degradation of Organic Photovoltaic Materials

State-of-the-art organic photovoltaic (OPV) materials are composed of complex, chemically diverse polymeric and molecular structures that form highly intricate solid-state interactions, collectively yielding exceptional tunability in performance and aesthetics. These properties are especially attractive for semitransparent power-generating windows or shades in living environments, greenhouses, or other architectural integrations. However, before such a future is realized, a broader and deeper understanding of property stability must be acquired. Stability during operating and environmental conditions is critical, namely, material color steadfastness, optoelectronic performance retention, morphological rigidity, and chemical robustness. To date, no single investigation encompasses all four distinct, yet interconnected, metrics. Here, we present a multimodal strategy that captures a dynamic and interconnected evolution of each property during the course of an accelerated photobleaching experiment. We demonstrate this approach across relevant length scales (from molecular to visual macroscale) using X-ray photoelectron spectroscopy, grazing-incidence X-ray scattering, microwave conductivity, and time-dependent photobleaching spectroscopies for two high-performance semitransparent OPV blends—PDPP4T:PC 60 BM and PDPP4T:IEICO-4F, with comparisons to the stabilities of the individual components. We present direct evidence that specific molecular acceptor (fullerene vs nonfullerene) designs and the resulting donor–acceptor interactions lead to distinctly different mechanistic routes that ultimately arrive at what is termed “OPV degradation.” We directly observe a chemical oxidation of the cyano endcaps of the IEICO-4F that coincides with a morphological change and large loss in photoconductivity while the fullerene acceptor-containing blend demonstrates a significantly greater fraction of oxygen uptake but retains 55% of the photoconductivity. Finally, this experimental roadmap provides meaningful guidance for future high-throughput, multimodal studies, benchmarking the sensitivity of the different analytical techniques for assessing stability in printable active layers, independent of complete device architectures.

14 SOLAR ENERGY↗

Solid-State Ionic Rectification in Perovskite Nanowire Heterostructures

Halide perovskites have attracted increasing research attention with regard to their potential for optoelectronic applications. Because of its low activation energy, ion migration is implicated in the long-term stability and many unusual transport behaviors of halide perovskite devices. However, direct observation and precise control of the ionic transport in halide perovskite crystals remain challenging. Here, we have designed an axial CsPbBr 3 -CsPbCl 3 nanowire heterostructure, in which electric-field-induced halide ion migration was clearly visualized and quantified. We demonstrated that halide ion migration is dependent on the applied electric field and exhibits ionic rectification in this solid-state system, which is due to the nonuniform distribution of the ionic vacancies in the nanowire that results from a competition between electrical screening and their creation/destruction at the electrodes' interfaces. Furthermore, the asymmetric heterostructure characteristics add an additional knob to control the ion movement in the design of advanced ionic circuits with halide perovskites as building blocks.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Ion correlations drive charge overscreening and heterogeneous nucleation at solid–aqueous electrolyte interfaces

Significance Ion distributions at charged solid–water interfaces, referred to as the electrical double layer (EDL), are poorly understood at high ion concentrations, in part due to the lack of molecular-scale descriptions of the interactions between adsorbed hydrated ions. Here, direct visualization of the salinity-dependent evolution of EDL structure reveals molecular origins of nonclassical transformation of the EDL, in which charge overscreening and heterogeneous nucleation are driven by ion–ion correlations at the interfaces. This manifestation of the atomistic basis of nonclassical behaviors provides a much-needed understanding of the impact of ion cooperativity at charged interfaces for the development of predictive models for element transport in natural environments and advanced technologies for material growth and synthesis in saline environments.

36 MATERIALS SCIENCE↗

Tracking single particle rotation: Probing dynamics in four dimensions

Direct visualization and tracking of small particles at high spatial and temporal resolution provides a powerful approach to probing complex dynamics and interactions in chemical and biological processes. Analysis of the rotational dynamics of particles adds a new dimension of information that is otherwise impossible to obtain with conventional 3-D particle tracking. In this review, we survey recent advances in single-particle rotational tracking, with highlights on the rotational tracking of optically anisotropic Janus particles. Furthermore, strengths and weaknesses of the various particle tracking methods, and their applications are discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Understanding multi-scale battery degradation with a macro-to-nano zoom through its hierarchy

Lithium-ion batteries (LIBs) feature structural and chemical complexities across a broad range of length scales. It is the hierarchy of the battery structure that determines its functionality. An in-depth understanding of the battery function, degradation, and failure mechanisms requires a thorough and systematic investigation from structural, chemical, mechanical, and dynamic perspectives. Here we present a macro-to-nano zoom through the hierarchy of a commercial 18650 type LIB using a suite of state-of-the-art X-ray microscopy techniques. Damage, deformation, and heterogeneity at different length scales are visualized and are associated with different degradation phenomena and mechanisms. Our results highlight the importance of the mechanical properties of the cathode material, which could impact both the immediate and the long-term cell behaviors significantly. While this study focuses on a commercial lithium cell with a standard configuration, our findings can be extrapolated and are applicable to the development of next-generation energy storage technology, e.g. solid-state batteries.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

SAFE-OCC: A novelty detection framework for Convolutional Neural Network sensors and its application in process control

Herein we present a novelty detection framework for Convolutional Neural Network (CNN) sensors that we call Sensor-Activated Feature Extraction One-Class Classification (SAFE-OCC). We show that this framework enables the safe use of computer vision sensors in process control architectures. Emergent control applications use CNN models to map visual data to a state signal that can be interpreted by the controller. Incorporating such sensors introduces a significant system operation vulnerability because CNN sensors can exhibit high prediction errors when exposed to novel (abnormal) visual data. Unfortunately, identifying such novelties in real-time is nontrivial. To address this issue, the SAFE-OCC framework leverages the convolutional blocks of the CNN to create an effective feature space to conduct novelty detection using a desired one-class classification technique. This approach engenders a feature space that directly corresponds to that used by the CNN sensor and avoids the need to derive an independent latent space. We demonstrate the effectiveness of SAFE-OCC via simulated control environments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Phase-enabled metal-organic framework homojunction for highly selective CO 2 photoreduction

Conversion of clean solar energy to chemical fuels is one of the promising and up-and-coming applications of metal–organic frameworks. However, fast recombination of photogenerated charge carriers in these frameworks remains the most significant limitation for their photocatalytic application. Although the construction of homojunctions is a promising solution, it remains very challenging to synthesize them. Herein, we report a well-defined hierarchical homojunction based on metal–organic frameworks via a facile one-pot synthesis route directed by hollow transition metal nanoparticles. The homojunction is enabled by two concentric stacked nanoplates with slightly different crystal phases. The enhanced charge separation in the homojunction was visualized by in-situ surface photovoltage microscopy. Moreover, the as-prepared nanostacks displayed a visible-light-driven carbon dioxide reduction with very high carbon monooxide selectivity, and excellent stability. Our work provides a powerful platform to synthesize capable metal–organic framework complexes and sheds light on the hierarchical structure-function relationships of metal–organic frameworks.

14 SOLAR ENERGY↗