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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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Polaron Mobility and Disordering of the Sodium Sublattice in Triphylite-Na[subscript x]FePO[subscript 4]
Abstract not provided
110th Anniversary: High-Molecular-Weight Chitin and Cellulose Hydrogels from Biomass in Ionic Liquids without Chemical Crosslinking
In this work, cellulose, chitin, and composite 3D hydrogels and membranes were fabricated without any chemical modification from high-molecular-weight chitin and cellulose-rich material (CRM) extracted from shrimp shell or pine wood, respectively, using the ionic liquid (IL) 1-ethyl-3-methylimidazolium acetate ([C 2 mim][OAc]). The hydrogels were prepared by redissolution of the extracted biopolymers in the same IL, or in a one-pot process directly from a solution of the biomass after extraction, followed by molding/gelation (“3D gels”) or casting (membranes), and then washing. For comparison, the preparation of gels was attempted using commercial microcrystalline cellulose or chitin. From all of the sources, the regenerated CRM or chitin required significantly lower load. Hydrogels were also converted to aerogels via transformation to alcogels and then Sc-CO 2 drying, giving materials of low density, high porosity, favorable compressibility, high water uptake, and moderate antioxidant activity. Air-dried membranes were dense, of high tensile strength, and exhibited high water-vapor transmission.
Concentration-Dependent Solvation Structure and Dynamics of Aqueous Sulfuric Acid Using Multinuclear NMR and DFT
Sulfuric acid is a ubiquitous compound for industrial processes and aqueous sulfate solutions also play a critical role in electrolytes for many prominent battery chemistries. While the thermodynamic literature for it is quite well-developed, comprehensive studies of the solvation structure, and particularly molecular-scale dynamical and transport properties, are less available. This study applies a multinuclear NMR approach to the elucidation of the solvation structure and dynamics over a wide temperature (-10 – 50?C) and concentration (0 – 18 M) range, combining 17O shift, linewidth, and T1 relaxation measurements, 33S shift and linewidth measurements, and 1H PFG-NMR measurements of the proton self-diffusivity. In conjunction, these results indicate a crossover between two regimes of solvation structure and dynamics, occurring above the concentration associated with the deep eutectic point (~ 4.5 M), with the high-concentration regime dominated by strong water-sulfate correlation. This description was borne out in detail by the activation energy trends with increasing concentration derived from the relaxation of both the H2O/H3O+ and H2SO4/HSO4-/SO42- 17O resonances and the 1H self-diffusivity. However, the 17O chemical shift difference between the H2O/H3O+ and H2SO4/HSO4-/SO42- resonances across the entire temperature range is nevertheless strikingly linear. A computational approach coupling MD simulations and DFT NMR shift calculations to reproduce this trend is presented, which will be the subject of further development. This combination of multinuclear, dynamical NMR and computational methods, and the results furnished by this study, will provide a platform for future studies on battery electrolytes where aqueous sulfate chemistry plays a central role in the solution structure.
Pathways through equilibrated states with coexisting phases for gas hydrate formation
Under ambient conditions, water freezes to either hexagonal ice or a hexagonal/cubic composite ice. The presence of hydrophobic guest molecules introduces a competing pathway: gas hydrate formation, with the guests in clathrate cages. Here, the pathways of the phase transitions are sought as sequences of states with coexisting phases, using a generalized replica exchange algorithm designed to sample them in equilibrium, avoiding nonequilibrium processes. For a dilute solution of methane in water under 200 atm, initializing the simulation with the full set of replicas leads to methane trapped in hexagonal/cubic ice, while gradually adding replicas with decreasing enthalpy produces the initial steps of hydrate growth. Once a small amount of hydrate is formed, water rearranges to form empty cages, eventually transforming the remainder of the system to metastable β ice, a scaffolding for hydrates. It is suggested that configurations with empty cages are reaction intermediates in hydrate formation when more guest molecules are available. Furthermore, free energy profiles show that methane acts as a catalyst reducing the barrier for β ice versus hexagonal/cubic ice formation.
Effect of Graft Molecular Weight and Density on the Mechanical Properties of Polystyrene-Grafted Cellulose Nanocrystal Films
In this work, polymer-grafted nanoparticle (PGN) films were prepared from polystyrene (PS) grafted to rodlike cellulose nanocrystals (MxG-CNC-g-PS) with a controllable grafting density (0.03–0.25 chains/nm 2 ) and molecular weight (5–60 kg/mol). These nanorod-based PGNs are solution- and melt-processible, permitting access to one-component composite films with high nanofiller loadings (with up to 55 wt %). The impact of both grafted polymer density and molecular weight on the mechanical properties of the films was investigated and related to the polymer brush conformation: concentrated polymer brush (CPB), semidilute polymer brush (SDPB), or CPB core with SDPB corona (CPB/SDPB). The rubbery regime storage modulus (above $T_g$) showed 2 orders of magnitude increase, maximizing at a low degree of polymerization (N) and low grafting density (σ). Fracture toughness was maximized in samples with the grafted polymer in the SDPB or CPD/SDPB (higher N and relatively low σ) regime and showed enhancement relative to PS of molecular weight similar to the graft. In line with prior computation predictions, optimizing for both rubbery modulus and fracture toughness in such nanorod-based PGN films requires the polymers in the SDPB regime and CNC loading levels (ca. 50–60 wt %) that are difficult to attain in more traditional two-component CNC composites.
A universal co-solvent dilution strategy enables facile and cost-effective fabrication of perovskite photovoltaics
Cost management and toxic waste generation are two key issues that must be addressed before the commercialization of perovskite optoelectronic devices. We report a groundbreaking strategy for eco-friendly and cost-effective fabrication of highly efficient perovskite solar cells. This strategy involves the usage of a high volatility co-solvent, which dilutes perovskite precursors to a lower concentration (<0.5 M) while retaining similar film quality and device performance as a high concentration (>1.4 M) solution. More than 70% of toxic waste and material cost can be reduced. Mechanistic insights reveal ultra-rapid evaporation of the co-solvent together with beneficial alteration of the precursor colloidal chemistry upon dilution with co-solvent, which in-situ studies and theoretical simulations confirm. The co-solvent tuned precursor colloidal properties also contribute to the enhancement of the stability of precursor solution, which extends its processing window thus minimizing the waste. This strategy is universally successful across different perovskite compositions, and scales from small devices to large-scale modules using industrial spin-coating, potentially easing the lab-to-fab translation of perovskite technologies.
Tunable angle-dependent electrochemistry at twisted bilayer graphene with moiré flat bands
Tailoring electron transfer dynamics across solid–liquid interfaces is fundamental to the interconversion of electrical and chemical energy. Stacking atomically thin layers with a small azimuthal misorientation to produce moiré superlattices enables the controlled engineering of electronic band structures and the formation of extremely flat electronic bands. Here, we report a strong twist-angle dependence of heterogeneous charge transfer kinetics at twisted bilayer graphene electrodes with the greatest enhancement observed near the ‘magic angle’ (~1.1°). Furthermore, this effect is driven by the angle-dependent tuning of moiré-derived flat bands that modulate electron transfer processes with the solution-phase redox couple. Combined experimental and computational analysis reveals that the variation in electrochemical activity with moiré angle is controlled by a structural relaxation of the moiré superlattice at twist angles of <2°, and ‘topological defect’ AA stacking regions, where flat bands are localized, produce a large anomalous local electrochemical enhancement that cannot be accounted for by the elevated local density of states alone.
Understanding hydrogen electrocatalysis by probing the hydrogen-bond network of water at the electrified Pt–solution interface
Rational construction of the electrode–solution interface where electrochemical processes occur is of paramount importance in electrochemistry. Efforts to gain better control and understanding of the interface have been hindered by lack of probing methods. Here, in this study, we show that the hydrogen evolution and oxidation reactions (HER/HOR) catalysed by platinum in base can be promoted by introduction of N-methylimidazoles at the platinum–water interface. In situ spectroscopic characterization together with simulations indicate that the N-methylimidazoles facilitate diffusion of hydroxides across the interface by holding the second layer of water close to platinum surfaces, thereby promoting the HER/HOR. We thus propose that the HER/HOR kinetics of platinum in acid and base is governed by diffusion of protons and hydroxides, respectively, through the hydrogen-bond network of interfacial water by the Grotthuss mechanism. Moreover, we demonstrate a 40% performance improvement of an anion exchange membrane electrolyser by adding 1,2-dimethylimidazole into the alkali fed into its platinum cathode.
A framework for data-driven solution and parameter estimation of PDEs using conditional generative adversarial networks
We employ and adapt the image-to-image translation concept based on conditional generative adversarial networks (cGAN) for learning a forward and an inverse solution operator of partial differential equations (PDEs). We focus on steady-state solutions of coupled hydromechanical processes in heterogeneous porous media and present the parameterization of the spatially heterogeneous coefficients, which is exceedingly difficult using standard reduced-order modeling techniques. We show that our framework provides a speed-up of at least 2,000 times compared to a finite-element solver and achieves a relative root-mean-square error (r.m.s.e.) of less than 2% for forward modeling. For inverse modeling, the framework estimates the heterogeneous coefficients, given an input of pressure and/or displacement fields, with a relative r.m.s.e. of less than 7%, even for cases where the input data are incomplete and contaminated by noise. The framework also provides a speed-up of 120,000 times compared to a Gaussian prior-based inverse modeling approach while also delivering more accurate results.
Improving the astrometric solution of the Hyper Suprime-Cam with anisotropic Gaussian processes
Context. We study astrometric residuals from a simultaneous fit of Hyper Suprime-Cam images. Aims. We aim to characterize these residuals and study the extent to which they are dominated by atmospheric contributions for bright sources. Methods. We used Gaussian process interpolation with a correlation function (kernel) measured from the data to smooth and correct the observed astrometric residual field. Results. We find that a Gaussian process interpolation with a von Kármán kernel allows us to reduce the covariances of astrometric residuals for nearby sources by about one order of magnitude, from 30 mas 2 to 3 mas 2 at angular scales of ~1 arcmin. This also allows us to halve the rms residuals. Those reductions using Gaussian process interpolation are similar to recent result published with the Dark Energy Survey dataset. We are then able to detect the small static astrometric residuals due to the Hyper Suprime-Cam sensors effects. We discuss how the Gaussian process interpolation of astrometric residuals impacts galaxy shape measurements, particularly in the context of cosmic shear analyses at the Rubin Observatory Legacy Survey of Space and Time.
On orthogonality preserving quadratic stochastic operators
A quadratic stochastic operator (in short QSO) is usually used to present the time evolution of differing species in biology. Some quadratic stochastic operators have been studied by Lotka and Volterra. In the present paper, we first give a simple characterization of Volterra QSO in terms of absolutely continuity of discrete measures. Further, we introduce a notion of orthogonal preserving QSO, and describe such kind of operators defined on two dimensional simplex. It turns out that orthogonal preserving QSOs are permutations of Volterra QSO. The associativity of genetic algebras generated by orthogonal preserving QSO is studied too.
Numerical solution of the stochastic parabolic equation with the dependent operator coefficient
In the present paper, a single step implicit difference scheme for the numerical solution of the stochastic parabolic equation with the dependent operator coefficient is presented. Theorem on convergence estimates for the solution of this difference scheme is established. In applications, this abstract result permits us to obtain the convergence estimates for the solution of difference schemes for the numerical solution of initial boundary value problems for parabolic equations. The theoretical statements for the solution of this difference scheme are supported by the results of numerical experiments.
Pair mobility functions for rigid spheres in concentrated colloidal dispersions: Force, torque, translation, and rotation
The formulation of detailed models for the dynamics of condensed soft matter including colloidal suspensions and other complex fluids requires accurate description of the physical forces between microstructural constituents. In dilute suspensions, pair-level interactions are sufficient to capture hydrodynamic, interparticle, and thermodynamic forces. In dense suspensions, many-body interactions must be considered. Prior analytical approaches to capturing such interactions such as mean-field approaches replace detailed interactions with averaged approximations. However, long-range coupling and effects of concentration on local structure, which may play an important role in, e.g., phase transitions, are smeared out in such approaches. An alternative to such approximations is the detailed modeling of hydrodynamic interactions utilizing precise couplings between moments of the hydrodynamic traction on a suspended particle and the motion of that or other suspended particles. For two isolated spheres, a set of these functions was calculated by Jeffrey and Onishi [J. Fluid Mech. 139, 261–290 (1984)] and Jeffrey [J. Phys. Fluids 4, 16–29 (1992)]. Along with pioneering work by Batchelor, these are the touchstone for low-Reynolds-number hydrodynamic interactions and have been applied directly in the solution of many important problems related to the dynamics of dilute colloidal dispersions [G. K. Batchelor and J. T. Green, J. Fluid Mech. 56, 375–400 (1972) and G. K. Batchelor, J. Fluid Mech. 74, 1–29 (1976)]. Toward extension of these functions to concentrated systems, here we present a new stochastic sampling technique to rapidly calculate an analogous set of mobility functions describing the hydrodynamic interactions between two hard spheres immersed in a suspension of arbitrary concentration, utilizing accelerated Stokesian dynamics simulations. These mobility functions provide precise, radially dependent couplings of hydrodynamic force and torque to particle translation and rotation, for arbitrary colloid volume fraction ϕ. The pair mobilities (describing entrainment of one particle by the disturbance flow created by another) decay slowly with separation distance: as 1/r, for volume fractions 0.05 ≤ ϕ ≤ 0.5. For the relative mobility, we find an initially rapid growth as a pair separates, followed by a slow, 1/r growth. Up to ϕ ≤ 0.4, the relative mobility does not reached the far-field value even beyond separations of many particle sizes. In the case of ϕ = 0.5, the far-field asymptote is reached but only at a separation of eight radii and after a slow 1/r growth. At these higher concentrations, the coefficients also reveal liquid-like structural effects on pair mobility at close separations. These results confirm that long-range many-body hydrodynamic interactions are an essential part of the dynamics of concentrated systems and that care must be taken when applying renormalization schemes.
Degeneracy of energy levels of pseudo-Gaussian oscillators
We study the main features of the isotropic radial pseudo-Gaussian oscillators spectral properties. This study is made upon the energy levels degeneracy with respect to orbital angular momentum quantum number. In a previous work [6] we have shown that the pseudo-Gaussian oscillators belong to the class of quasi-exactly solvable models and an exact solution has been found.
Crank-Nicholson difference scheme for a stochastic parabolic equation with a dependent operator coefficient
In the present paper, the Crank-Nicolson difference scheme for the numerical solution of the stochastic parabolic equation with the dependent operator coefficient is considered. Theorem on convergence estimates for the solution of this difference scheme is established. In applications, convergence estimates for the solution of difference schemes for the numerical solution of three mixed problems for parabolic equations are obtained. The numerical results are given.
Carbon nanotube thermoelectric devices by direct printing: Toward wearable energy converters
Thermoelectric devices convert thermal energy to electrical energy and are particularly well-suited for energy harvesting from waste heat. Even as the number of electronic devices used in daily life proliferates, technical advances diminish the average power such devices require to perform a given function. Here, localized thermal gradients that abound in our living environments, despite having modest energy densities, are therefore becoming increasingly viable and attractive to power such devices. With this motivation, we report the design, fabrication, and characterization of single-wall carbon nanotube thermoelectric devices (CNT-TDs) on flexible polyimide substrates as a basis for wearable energy converters. Our aqueous-solution-based film fabrication process could enable readily scalable, low-cost TDs; here, we demonstrate CNT-hydroxypropyl cellulose (HPC) composite thermoelectric films by aerosol jet printing. The electrical conductivity of the composite films is controlled through the number of CNT/HPC layers printed in combination with control of the annealing conditions.
Flexible machine-learning interatomic potential for simulating structural disordering behavior of Li 7 La 3 Zr 2 O 12 solid electrolytes
Batteries based on solid-state electrolytes, including Li 7 La 3 Zr 2 O 12 (LLZO), promise improved safety and increased energy density; however, atomic disorder at grain boundaries and phase boundaries can severely deteriorate their performance. Machine-learning (ML) interatomic potentials offer a uniquely compelling solution for simulating chemical processes, rare events, and phase transitions associated with these complex interfaces by mixing high scalability with quantum-level accuracy, provided that they can be trained to properly address atomic disorder. To this end, we report the construction and validation of an ML potential that is specifically designed to simulate crystalline, disordered, and amorphous LLZO systems across a wide range of conditions. The ML model is based on a neural network algorithm and is trained using ab initio data. Performance tests prove that the developed ML potential can predict accurate structural and vibrational characteristics, elastic properties, and Li diffusivity of LLZO comparable to ab initio simulations. As a demonstration of its applicability to larger systems, we show that the potential can correctly capture grain boundary effects on diffusivity, as well as the thermal transition behavior of LLZO. Here these examples show that the ML potential enables simulations of transitions between well-defined and disordered structures with quantum-level accuracy at speeds thousands of times faster than ab initio methods.