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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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204 records · Page 12

Electrospun porous La–Sr–Co–Ni–O nanofibers for highly sensitive non-enzymatic glucose detection

Glucose biosensors are widely used for clinical, industrial, and environmental applications. Nonenzymatic electrochemical glucose biosensors based on metal oxides with a perovskite structure have exhibited high sensitivity, excellent stability, and cost efficiency. In this work, porous La–Sr–Co–Ni–O (LSCNO) nanofibers, with an ABO 3 -type perovskite structure, were prepared through optimizing the A-site and B-site elements by electrospinning, followed with calcination at 700 °C for 5 h. Characterized by scanning and transmission electron microscopy, X-ray diffraction, and X-ray photoelectron spectroscopy, fabricated nanofibers were confirmed to be porous and nanosized polycrystalline grains with high crystallinity. A novel La 0.75 Sr 0.25 Co 0.5 Ni 0.5 O 3 -based nonenzymatic electrochemical biosensor was developed, which is sensitive to glucose because of an electrochemically catalytic mechanism, a mediated electron transfer involving Ni(II)/Ni(III) or Co(II)/Co(III), accompanying with gluconic acid complexation. The glucose biosensor presented a linear response in the range of 0.1–1.0 mM with a calibration sensitivity of 924 ± 28 μA mM –1 , a proportion of the variance of 0.9926, and a lower limit of detection of 0.083 mM, respectively, demonstrating an outstanding analytical performance. The biosensor showed no response to the most widely used anionic surfactant, sodium dodecyl sulfate, and low sensitivity to other biomolecules, such as fructose, lactose, galactose, mannose, dopamine, and ascorbic acid. A urine sample was tested by this novel nonenzymatic electrochemical biosensor by standard addition method, suggesting a potential application for clinical test.

36 MATERIALS SCIENCE↗

Accelerated Sequence Design of Star Block Copolymers: An Unbiased Exploration Strategy via Fusion of Molecular Dynamics Simulations and Machine Learning

Star block copolymers (s-BCPs) have potential applications as novel surfactants or amphiphiles for emulsification, compatibilization, chemical transformations, and separations. s-BCPs have chain architectures where three or more linear diblock copolymer arms comprised of two chemically distinct linear polymers, e.g., solvophobic and solvophilic chains, are covalently joined at one point. The chemical composition of each of the subunit polymer chains comprising the arms, their molecular weights, and the number of arms can be varied to tailor the surface and interfacial activity of these architecturally unique molecules. Further, this makes identification of the optimal s-BCP design nontrivial as the total number of plausible s-BCP architectures is experimentally or computationally intractable. In this work, we use molecular dynamics (MD) simulations coupled with a reinforcement learning-based Monte Carlo tree search (MCTS) to identify s-BCP designs that minimize the interfacial tension between polar and nonpolar solvents. We first validate the MCTS approach for the design of small- and medium-sized s-BCPs and then use it to efficiently identify sequences of copolymer blocks for large-sized s-BCPs. The structural origins of interfacial tension in these systems are also identified by using the configurations obtained from MD simulations. Chemical insights into the arrangement of copolymer blocks that promote lower interfacial tension were mined using machine learning (ML) techniques. Overall, this work provides an efficient approach to solve design problems via fusion of simulations and ML and provides important groundwork for future experimental investigation of s-BCPs for various applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Hyperspectral Detection of the Fluorescence Shift between Chirality-Sorted Empty and Water-Filled Single-Wall Carbon Nanotube Enantiomers

Single-wall carbon nanotubes (SWCNTs) have extraordinary electronic and optical properties that depend strongly on their exact chiral structure and their interaction with their inner and outer environment. The fluorescence (PL) of semiconducting SWCNTs, for instance, will shift depending on the molecules with which the SWCNT’s hollow core is filled. These interaction-induced shifts are challenging to resolve on the ensemble level in samples containing a mixture of different filling contents due to the relatively large inhomogeneous line width of the ensemble SWCNT PL compared to the size of these shifts. To circumvent this inhomogeneous broadening, single-tube spectroscopy and hyperspectral imaging are often applied, which until now required time-consuming statistical studies. Here, we present hyperspectral PL microscopy combined with automated SWCNT segmenting based on either principal component analysis or a convolutional neural network, capable of both spatially and spectrally resolving the PL along the length of many individual SWCNTs at the same time and automatically fitting peak positions and line widths of individual SWCNTs. The methodology is demonstrated by accurately determining the emission shifts and line widths of thousands of left- and right-handed empty and water-filled SWCNTs coated with a chiral surfactant, resulting in four statistical distributions which cannot be resolved in ensemble spectroscopy of unsorted samples. The results demonstrate a robust method to quickly probe ensemble properties with single-enantiomer spectral resolution. Moreover, it promises to be an absolute quantitative method to characterize the relative abundances of SWCNTs with different handedness or filling content in macroscopic samples, simply by counting individual species.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Zeolite‐Based Catalysts for Conversion of Oxygenated Polymer Waste by Positron Annihilation

Positron Annihilation Lifetime Spectroscopy (PALS) has been employed to investigate the catalysts HZSM-5 and MESO−Y, which play a pivotal role in catalyzing and upgrading plastics, with a primary focus on oxygenated polymers, thereby transforming existing plastic materials into simpler, higher-quality value-added products. Here, in this study, PALS was systematically compared with other complementary analytical techniques. The research outcomes have successfully demonstrated the efficacy of PALS in elucidating the morphology and topology of zeolites at micro/meso-meter scales. The first experiment focuses on H-ZSM-5 zeolite subjected to treatments involving polyurethane and polypropylene. The second experiment delves into H-ZSM-5 zeolites with varying Si/Al ratios, both before and after conversion. The third experiment investigates Y zeolites that are surfactant templated to induce meso-porosity, examining their fresh state as well as their post-conversion condition. The PALS analysis was supplemented by BET (Brunauer-Emmett-Teller) analysis and NMR (Nuclear Magnetic Resonance) spectroscopies. Notably, PALS exhibits superior sensitivity, at the sub-nanometer scale, suggesting its potential as a preferred complementary method for catalysis studies. In conclusion, the integration of PALS into the repertoire of analytical tools enhances our understanding of catalyst behavior and catalytic processes, offering valuable insights for the advancement of plastic recycling and catalysis research.

32 - ENERGY CONSERVATION, CONSUMPTION, AND UTILIZA↗

A Study of Bubble and Slug Gas-Liquid Flow in a Microgravity Environment

The influence of gravity on the two-phase flow dynamics is obvious.As the gravity level is reduced,there is a new balance between inertial and interfacial forces, altering the behavior of the flow. In bubbly flow,the absence of drift velocity leads to spherical-shaped bubbles with a rectilinear trajectory.Slug flow is a succession of long bubbles and liquid slug carrying a few bubbles. There is no flow reversal in the thin liquid film as the long bubble and liquid slug pass over the film. Although the flow structure seems to be simpler than in normal gravity conditions,the models developed for the prediction of flow behavior in normal gravity and extended to reduced gravity flow are unable to predict the flow behavior correctly.An additional benefit of conducting studies in microgravity flows is that these studies aide the development of understanding for normal gravity flow behavior by removing the effects of buoyancy on the shape of the interface and density driven shear flows between the gas and the liquid phases. The proposal calls to study specifically the following: 1) The dynamics of isolated bubbles in microgravity liquid flows will be analyzed: Both the dynamics of spherical isolated bubbles and their dispersion by turbulence, their interaction with the pipe wall,the behavior of the bubbles in accelerated or decelerated flows,and the dynamics of isolated cylindrical bubbles, their deformation in accelerated/decelerated flows (in converging or diverging channels), and bubble/bubble interaction. Experiments will consist of the use of Particle Image Velocimetry (PIV) and Laser Doppler Velocimeters (LDV) to study single spherical bubble and single and two cylindrical bubble behavior with respect to their influence on the turbulence of the surrounding liquid and on the wall 2) The dynamics of bubbly and slug flow in microgravity will be analyzed especially for the role of the coalescence in the transition from bubbly to slug flow (effect of fluid properties and surfactant), to identify clusters that promote coalescence and transition the void fraction distribution in bubbly and slug flow,to measure the wall friction in bubbly flow. These experiments will consist of multiple bubbles type flows and will utilize hot wire and film anemometers to measure liquid velocity and wall shear stress respectively and double fiber optic probes to measure bubble size and velocity as a function of tube radius and axial location.

McQuillen, J.↗

Extending the capillary wave model to include the effect of bending rigidity: X-ray reflectivity and diffuse scattering

The surface roughness of a thin film at a liquid interface exhibits contributions of thermally excited fluctuations. This thermal roughness depends on temperature (𝑇), surface tension (𝛾), and elastic material properties, specifically the bending modulus (𝜅) of the film. A nonzero 𝜅 suppresses the thermal roughness at small length scales compared to an interface with zero 𝜅, as expressed by the power spectral density of the thermal roughness. The description of the x-ray scattering of the standard capillary wave model (CWM), which is valid for zero 𝜅, is extended to include the effect of 𝜅. The extended CWM (eCWM) provides a single analytical form for both the specular x-ray reflectivity (XRR) and the diffuse scattering around the specular reflection, and recovers the expression of the CWM at its zero 𝜅 limit. This theoretical approach enables the use of single-shot grazing incidence x-ray off-specular scattering (GIXOS) measurements for characterizing the structure of thin films on a liquid surface. The eCWM analysis approach decouples the thermal roughness factor from the surface scattering signal, providing direct access to the intrinsic surface-normal structure of the film and its bending modulus. Moreover, the eCWM facilitates the calculation of reflectivity at any desired resolution (pseudo-XRR approach). The transformation into pseudo-XRR provides the benefit of using widely available XRR software to perform GIXOS analysis. The extended range of the vertical scattering vector (𝑄 𝑧 ) available with the GIXOS pseudo-XRR approach allows for a higher spatial resolution than with conventional XRR. Experimental results are presented for various lipid systems, showing strong agreement between conventional specular XRR and pseudo-XRR methods. This agreement validates the proposed approach and highlights its utility for analyzing soft, thin films.

36 MATERIALS SCIENCE↗