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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 91 records · Page 5

Spectral Deconvolution of Electron-Bifurcating Flavoproteins

Electron-bifurcating flavoproteins catalyze the tightly coupled reduction of high- and low-potential acceptors using a median-potential electron donor, and are invariably complex systems with multiple redox-active centers in two or more subunits. Methods are described that permit, in favorable cases, the deconvolution of spectral changes associated with reduction of specific centers, making it possible to dissect the overall process of electron bifurcation into individual, discrete steps.

electron bifurcation↗

Hydrogen charging and desorption from microstructural viewpoint: A method for deconvoluting hydrogen desorption spectra and unveiling the hydrogen-microstructure interaction

Understanding the interaction of hydrogen with microstructural features in metallic materials is crucial for designing hydrogen-resistant alloys. Although thermal desorption spectroscopy (TDS) is widely used for investigating the hydrogen binding behavior of various microstructural features, its application to face-centered cubic (fcc) metals and alloys that exhibit low hydrogen diffusivity is limited due to the lumped TDS desorption signals. This paper shows that, by coupling a Sofronis–McMeeking type hydrogen transport model with a microstructure-informed finite-element model, TDS data can be deconvoluted to reveal the underlying adsorption–diffusion–desorption processes, hydrogen diffusivity, and trap-binding energies. In conclusion, the austenitic steel SS316L in solution-annealed condition is used as a demonstration material, and we focused on investigating the interaction of deuterium (hydrogen isotope) with grain boundaries, which is difficult to investigate from experiments alone but critical for design of alloys for hydrogen infrastructure.

Finite element simulation, Polycrystalline Microst↗

Deconvoluting sources of failure in lithium metal batteries containing NMC and PEO-based electrolytes

Solid-state lithium metal batteries (SSLMBs) containing polyethylene oxide (PEO)-derived polymer electrolytes and high-voltage (> 4 V vs. Li/Li + ) cathode materials suffer from three sources of failure: (1) instability between the polymer electrolyte and cathode at high voltage, (2) instability of the polymer electrolyte with Li metal, and (3) poorly-designed cathodes. In this study, these three sources of failure are deconvoluted by studying Ni-rich LiNi x Mn y Co 1-x-y O 2 (NMC, x ≥ 0.6) cathodes and a gel polymer electrolyte (GPE) derived from PEO. Initial cycling data reveals that rapid capacity fade occurs regardless of whether soft short circuits form due to Li dendrites. Cyclic voltammetry scans on cells featuring a Li metal electrode, GPE, and a NMC811 electrode free of additives suggest that there are no runaway reactions between the GPE and NMC811 up to 4.5 V vs. Li/Li + . Cathode/cathode symmetric cell cycling demonstrates that Li metal reactivity is a prime source of failure, though a poorly-designed cathode leads to subpar performance. A cathode with single-crystal NMC particles was demonstrated to achieve better initial capacity and longer cycle life, indicating room for improvement in SSLMB cathode design. Therefore, the sources of failure as enumerated may be ranked as follows from most to least concerning: 2 > 3 > 1.

25 ENERGY STORAGE↗

Deconvolution of Water-Splitting on the Triple-Conducting Ruddlesden–Popper-Phase Anode for Protonic Ceramic Electrolysis Cells

Triple-conducting materials have been proved to improve the performance of popular protonic ceramic electrolysis cells. However, partially because of the complexity of the water splitting reaction involving three charge carriers, that is, oxygen (O 2– ), proton (H + ), and electron (e – ), the triple-conducting reaction mechanism was not clear, and the reaction conducting pathways have seldom been addressed. In this study, the triple conducting Ruddlesden–Popper phase Pr 1.75 Ba 0.25 NiO 4+δ as an anode on the BaCe 0.7 Zr 0.1 Y 0.1 Yb 0.1 O 3–δ electrolyte was fabricated and its electroresponses were characterized by electrochemical impedance spectroscopy with various atmospheres and temperatures. The impedance spectra are deconvoluted by means of the distribution of the relaxation time method. The surface exchange rate and chemical diffusivity of H + and O 2– are characterized by electrical conductivity relaxation. The physical locations of electrochemical processes are also identified by atomic layer deposition with a surface inhibitor. A microkinetics model is proposed toward conductivities, triple-conducting pathways, reactant dependency, surface exchange and bulk diffusion capabilities, and other relevant properties. Lastly, the rate-limiting steps and suggestions for further improvement of electrode performance are presented.

25 ENERGY STORAGE↗

Deconvoluting Structures of Component Plant Biopolymers Using Deuterium Labeled Brassica oleracea Stems

Several Brassica species are cultivated globally for the production of seed oils as food, lubricants, and increasingly biofuels. The stem and leaf residues of these herbaceous dicotyledonous crops constitute another feedstock for biofuels and other products. Plant cell walls are complex, multipolymeric structures that consist primarily of polysaccharides and lignin. Cellulose chains coalesce to form crystalline microfibrils while the amorphous biopolymers, hemicellulose, and lignin form a network structure and fill the interstitial space. Neutron scattering has been used for the structural study of the assembly and deconstruction of the plant cell walls. However, similar neutron sensitivity of the different amorphous biopolymers has made structural association to individual component biopolymers nontrivial and ambiguous. To improve the association of structural features to specific biopolymer components, partial deuteration of the plant cell wall can be employed to increase the difference in the neutron scattering length density between amorphous carbohydrate and lignin plant polymers. Vegetative stems from partially deuterated Brassica oleracea acephala (kale) plants were obtained commercially, and the plant cell wall structures were studied by contrast-variation small-angle neutron scattering (CV-SANS) and Fourier-transform infrared spectroscopy (FTIR). FTIR results indicated that deuterium substitution for hydrogen in the carbohydrates was higher than that in lignin. By combining CV-SANS and FTIR results, the neutron scattering length density (nSLD) of the polysaccharides and lignin was determined to match nSLD of 65%:35% and 48%:52% D 2 O/H 2 O solvent mixtures, respectively. These nSLD values were higher than the nSLD values of polysaccharides and lignin for H 2 O grown biopolymers. The nSLD increase correlates to replacing about 42.5% of hydrogens present as both C–H and O–H groups in cellulose with deuterium atoms, while only 21% for lignin. In conclusion, this study lays the foundation to use partially deuterated plants to deconvolute structural features of the different component biopolymers, especially cellulose, hemicellulose, and lignin, of the plant cell wall without introducing unintended structural modifications due to the pretreatment extraction processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Deconvoluting XPS Spectra of La-Containing Perovskites from First-Principles

Perovskite-based oxides are used in electrochemical CO 2 and H 2 O reduction in electrochemical cells due to their compositional versatility, redox properties and stability. However limited knowledge exists on the mechanisms driving these processes. Toward this understanding, herein we probe the core level binding energy shifts of water-derived adspecies (H, O, OH, H 2 O) as well as the adsorption of CO 2 on LaCoO 3 and LaNiO 3 and we correlate the simulated peaks with experimental Temperature Programmed X-ray Photoelectron Spectroscopy (TPXPS) results. We find the strong adsorption of such chemical species can affect the antiferromagnetic ordering of LaNiO 3 . The adsorption of such adspecies is further quantified through Bader and differential charge analyses. We find the higher O 1s core level binding energy peak for both LaCoO 3 and LaNiO 3 corresponds to adsorption of water-related species and CO 2 , while the lower energy peak is due to lattice oxygen. We further correlate these DFT-based core level O 1s binding energies with the TPXPS measurements to quantify the decrease of the O 1s contribution due to desorption of adsorbates and the apparent increase of the lattice oxygen (both bulk and surface) with temperature. Finally, we quantify the influence of adsorbates on the La 4d, Co 2p and the Ni 3p core level binding energy shifts. This work demonstrates how theoretically generated XPS data can be utilized to predict species-specific binding energy shifts to assist in the deconvolution of the experimental results.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Deconvoluting the Photonic and Electronic Response of 2D Materials: The Case of MoS 2

Evaluating and tuning the properties of two-dimensional (2D) materials is a major focus of advancing 2D science and technology. While many claim that the photonic properties of a 2D layer provide evidence that the material is "high quality", this may not be true for electronic performance. In this work, we deconvolute the photonic and electronic response of synthetic monolayer molybdenum disulfide. We demonstrate that enhanced photoluminescence can be robustly engineered via the proper choice of substrate, where growth of MoS 2 on r-plane sapphire can yield > 100x enhancement in PL and carrier lifetime due to increased molybdenum-oxygen bonding compared to that of traditionally grown MoS 2 on c-plane sapphire. These dramatic enhancements in optical properties are similar to those of super-acid treated MoS 2 , and suggest that the electronic properties of the MoS 2 are also superior. However, a direct comparison of the charge transport properties indicates that the enhanced PL due to increased Mo-O bonding leads to p-type compensation doping, and is accompanied by a 2x degradation in transport properties compared to MoS 2 grown on c-plane sapphire. This work provides a foundation for understanding the link between photonic and electronic performance of 2D semiconducting layers, and demonstrates that they are not always correlated.

36 MATERIALS SCIENCE↗

Deconvolution of X-ray natural and magnetic circular dichroism in chiral Dy-ferroborate

Structural chirality and magnetism, when intertwined, can have profound implications on materials properties. Using X-ray imaging and spectroscopic measurements that leverage the natural and magnetic circular dichroic effects present in magnetized chiral crystal structures, we probe the interplay between chirality and magnetism across the field-induced spin-flop transition of Dy ferroborate, DyFe 3 (BO 3 ) 4 . Deconvolution of natural and magnetic circular dichroic signals at the Fe K and Dy L 2,3 absorption edges of the non-centrosymmetric structure was enabled by use of tunable temperature and magnetic field, providing access to element-specific magnetic information across the spin-flop transition. The magnetic response of Fe and Dy sublattices was found to be independent of domain chirality. The chiral domains were robust against both the (chirality preserving) R32 to P3 1 21/P3 2 21 structural phase transition at 280 K, and application of magnetic field up to 4 Tesla. A third flavor of X-ray dichroism, magneto-chiral dichroism, was not detected within the accuracy of our measurements. The absence of significant Fe magnetization along the screw, c-axis for the magnetic field strength used in this study, together with non-linear coupling of magnetic field to electric polarization across the spin-flop transition, may hinder observation of magneto-chiral dichroic effects in this system.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Data-driven deconvolution for large eddy simulations of Kraichnan turbulence

In this article, we demonstrate the use of artificial neural networks as optimal maps which are utilized for convolution and deconvolution of coarse-grained fields to account for sub-grid scale turbulence effects. Here, we demonstrate that an effective eddy-viscosity is predicted by our purely data-driven large eddy simulation framework without explicit utilization of phenomenological arguments. In addition, our data-driven framework precludes the knowledge of true sub-grid stress information during the training phase due to its focus on estimating an effective filter and its inverse so that grid-resolved variables may be related to direct numerical simulation data statistically. The proposed predictive framework is also combined with a statistical truncation mechanism for ensuring numerical realizability in an explicit formulation. Through this, we seek to unite structural and functional modeling strategies for modeling non-linear partial differential equations using reduced degrees of freedom. Both a priori and a posteriori results are shown for a two-dimensional decaying turbulence case in addition to a detailed description of validation and testing. A hyperparameter sensitivity study also shows that the proposed dual network framework simplifies learning complexity and is viable with exceedingly simple network architectures. Our findings indicate that the proposed framework approximates a robust and stable sub-grid closure which compares favorably to the Smagorinsky and Leith hypotheses for capturing the theoretical k -3 scaling in Kraichnan turbulence.

42 ENGINEERING↗

Deconvoluting sources of variability in aerosol jet printing using light scattering measurements

Aerosol jet printing (AJP) is a digital additive manufacturing technique for hybrid and conformal electronics, where its contactless deposition readily enables patterning over 3D surface topography. However, the complexity of aerosol transport physics makes deposition rate sensitive to process variability, hindering widespread industry adoption. Light scattering measurements have recently been demonstrated as a capable tool for measuring deposition rate in real time, enabling closed-loop control and in-situ qualification frameworks. These inline optical measurements present further opportunity as a diagnostic tool to understand the effects of secondary process parameters affecting vapor–liquid equilibrium and heat and mass transport during deposition. Downstream of the optical measurement cell, changing the sheath gas flow rate, increasing temperature via an inline heater, and adding solvent vapor via a sheath gas bubbler were observed to alter drying physics during sheath-collimation, and thereby impaction efficiency. Further upstream, the introduction of solvent vapor via a carrier gas bubbler and liquid build-up in the printhead were seen to affect the quantitative relationship between the light scattering data and the true deposition rate. Using this information, tightened controls of meaningful secondary parameters were implemented to improve the batch-to-batch consistency for printing a dielectric ink. In addition to advancing AJP process reliability for production, this work demonstrates the capability of inline optical measurements to provide insight into process physics and deconvolute competing mechanisms that underly variability.

additive manufacturing↗

Point spread function deconvolution using a convolutional autoencoder

A major issue in optical astronomical image analysis is the combined effect of the instrument’s point spread function (PSF) and the atmospheric seeing that blurs images and changes their shape in a way that is band and time-of-observation dependent. In this work we present a very simple neural network based approach to nonblind image deconvolution that relies on feeding a convolutional autoencoder (CAE) input images that have been preprocessed by convolution with the corresponding PSF and its regularized inverse, a method which is both conceptually simple and computationally less intensive. We also present here, a new approach for dealing with limited input dynamic range of neural networks compared to the dynamic range present in astronomical images.

79 ASTRONOMY AND ASTROPHYSICS↗

Cerebral perfusion computed tomography deconvolution via structure tensor total variation regularization

Purpose: Cerebral perfusion computed tomography (PCT) imaging as an accurate and fast acute ischemic stroke examination has been widely used in clinic. Meanwhile, a major drawback of PCT imaging is the high radiation dose due to its dynamic scan protocol. The purpose of this work is to develop a robust perfusion deconvolution approach via structure tensor total variation (STV) regularization (PD-STV) for estimating an accurate residue function in PCT imaging with the low-milliampere-seconds (low-mAs) data acquisition. Methods: Besides modeling the spatio-temporal structure information of PCT data, the STV regularization of the present PD-STV approach can utilize the higher order derivatives of the residue function to enhance denoising performance. To minimize the objective function, the authors propose an effective iterative algorithm with a shrinkage/thresholding scheme. A simulation study on a digital brain perfusion phantom and a clinical study on an old infarction patient were conducted to validate and evaluate the performance of the present PD-STV approach. Results: In the digital phantom study, visual inspection and quantitative metrics (i.e., the normalized mean square error, the peak signal-to-noise ratio, and the universal quality index) assessments demonstrated that the PD-STV approach outperformed other existing approaches in terms of the performance of noise-induced artifacts reduction and accurate perfusion hemodynamic maps (PHM) estimation. In the patient data study, the present PD-STV approach could yield accurate PHM estimation with several noticeable gains over other existing approaches in terms of visual inspection and correlation analysis. Conclusions: This study demonstrated the feasibility and efficacy of the present PD-STV approach in utilizing STV regularization to improve the accuracy of residue function estimation of cerebral PCT imaging in the case of low-mAs.

60 APPLIED LIFE SCIENCES↗

Multichannel deconvolution of vibrational signals: A state-space inverse filtering approach

Deconvolution of noisy measurements, especially when they are multichannel, has always been a challenging problem. The processing techniques developed range from simple Fourier methods to more sophisticated model-based parametric methodologies based on the underlying acoustics of the problem at hand. Methods relying on multichannel mean-squared error processors (Wiener filters) have evolved over long periods from the seminal efforts in seismic processing. However, when more is known about the acoustics, then model-based state-space techniques incorporating the underlying process physics can improve the processing significantly. The problems of interest are the vibrational response of tightly coupled acoustic test objects excited by an out-of-the-ordinary transient, potentially impairing their operational performance. Further, employing a multiple input/multiple output structural model of the test objects under investigation enables the development of an inverse filter by applying subspace identification techniques during initial calibration measurements. Feasibility applications based on a mass transport experiment and test object calibration test demonstrate the ability of the processor to extract the excitations successfully.

42 ENGINEERING↗

Deconvolution of Composition and Crystallite Size of Silver Hollandite Nanorods: Influence on Electrochemistry

In this paper, silver hollandite (Ag 1.4 Mn 8 O 16 ) has been synthesized by an aqueous, low-temperature co-precipitation technique to afford silver hollandite with distinct crystallite sizes (10 and 15 nm, identified as S-Ag 1.4 Mn 8 O 16 and L-Ag 1.4 Mn 8 O 16 , respectively) and equivalent silver content (x), allowing for the deconvolution of electrochemical effects related to crystallite size and silver content. The as-prepared silver hollandite materials were confirmed to be structurally analogous. Notably, TEM imaging reveals a high degree of bundling of S-Ag 1.4 Mn 8 O 16 nanorods compared to L-Ag 1.4 Mn 8 O 16 which facilitates more intimate connection of the S-Ag 1.4 Mn 8 O 16 material with enhanced interparticle contact. The electrochemical behavior and lithium diffusion properties were investigated by galvanostatic cycling, CV, electrochemical impedance, pulsed-discharge experiments, and ex-situ XAS analysis of cycled cathodes. Lithium based electrochemical cells containing S-Ag 1.4 Mn 8 O 16 delivered a capacity 15X higher than L-Ag 1.4 Mn 8 O 16 on cycle 1. Ex-situ XAS demonstrated structural change for S-Ag 1.4 Mn 8 O 16 and formation of Ag 0 on insertion of 3.8 Li + intercalation. However, the samples of L-Ag 1.4 Mn 8 O 16 were lithiated by a more limited 0.25 molar equivalents, where no significant structural changes were observed. Finally, the findings affirm crystallite size significantly impacts electrochemistry independent of cation occupancy of the α-MnO 2 type structure.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

In-situ FTIR Spectral Deconvolution [SWR-24-60]

In-situ FTIR Spectral Deconvolution contains scripts for the fitting of gaussians to convoluted FTIR spectra. It was specifically developed to handle a time-series of in situ ATR-FTIR spectra, split the spectra into its individual gaussians, and track those peaks as they shift in intensity and energy. Along with the actual fitting script, this repository contains several support scripts for data analysis and recall of prior fit results.

Tremolet de Villers, Bertrand↗