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NASA NTRS1973

Thermodynamic properties of gases dissolved in electrolyte solutions.

A method based on perturbation theory for mixtures is applied to the prediction of thermodynamic properties of gases dissolved in electrolyte solutions. The theory is compared with experimental data for the dependence of the solute activity coefficient on concentration, temperature, and pressure; calculations are included for partial molal enthalpy and volume of the dissolved gas. The theory is also compared with previous theories for salt effects and found to be superior. The calculations are best for salting-out systems. The qualitative feature of salting-in is predicted by the theory, but quantitative predictions are not satisfactory for such systems; this is attributed to approximations made in evaluating the perturbation terms.

Tiepel, E. W.↗

NASA NTRS1993

Modeling of outgassing and matrix decomposition in carbon-phenolic composites

A new release rate equation to model the phase change of water to steam in composite materials was derived from the theory of molecular diffusion and equilibrium moisture concentration. The new model is dependent on internal pressure, the microstructure of the voids and channels in the composite materials, and the diffusion properties of the matrix material. Hence, it is more fundamental and accurate than the empirical Arrhenius rate equation currently in use. The model was mathematically formalized and integrated into the thermostructural analysis code CHAR. Parametric studies on variation of several parameters have been done. Comparisons to Arrhenius and straight-line models show that the new model produces physically realistic results under all conditions.

Mcmanus, Hugh L.↗

NASA NTRSDate not supplied

Comparison of INP Parameterizations for Dust Minerals in Climatological Simulations With a Global Model

The effect of aerosol particles on ice nucleation and, in turn, the formation of ice and mixed phase clouds is recognized as one of the largest sources of uncertainty in weather and climate prediction. We utilize an improved sectional dust module in NASA GISS Earth System ModelE2.1, which distinguishes eight different mineral species and accretions between iron oxides and the other minerals. Simulations over a period of 20 years have been carried out with this model, and the mineral fields and other model variables (temperature, relative humidity) are used to calculate the ice nucleating particle (INP) number concentration, applying time-independent and time-dependent INP parameterizations, such as active site parameterization and water activity based immersion freezing model (ABIFM). We study how the dependence of the parameterizations on different model variables affects the mean INP number concentration. The sensitivity of the INP number concentration to fundamental dust properties such as emitted mineral size distributions and mixing state between minerals is also investigated. Results show that the sensitivity of the total INP number concentration to the emitted dust size distribution is rather small, but the sensitivity over the whole size range obscures offsetting differences in the magnitude and the sign of the sensitivity between smaller and larger particles.

INP Parameterizations↗

NASA NTRS1994

Composition Dependence of Bulk Alloy Properties

We introduce an approximate expression for the direct calculation of properties of alloys in terms of the pure components. This rule can be obtained as a particular case from the Bozzolo-Ferrante-Smith (BFS) method, a recently developed semiempirical method for alloys. In particular, we examine the application of this rule to several examples of the concentration dependence of the lattice parameter of binary and ternary alloys.

Bozzolo, Guillermo↗

DOE OSTI2023

Barrier-free predictions of short-range ordering/clustering kinetics in binary FCC solid solutions

We present comparisons of kinetic Monte Carlo (kMC) simulations of isothermal short-range ordering (SRO) and clustering (SRC) kinetics in binary FCC alloys with a mean-field concentration wave (CW) model. We find that the CW model is able to give order-of-magnitude agreement with kMC simulations for ordering/clustering relaxation times over a wide range of temperatures and compositions. The advantage of the CW model is that it does not require parameterization of vacancy hopping energy barriers, which, for a concentrated alloy, becomes prohibitive. We assess limits in the accuracy of the model and discuss the effect of cooling rates as well as the extension to multi-component systems. Ultimately, the simplicity and performance of the CW model compared to kMC simulations suggests that it is a useful tool to connect with models of properties dependent on SRO/SRC as well as for designing thermal treatments to control formation of SRO/SRC.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Effect of substrate temperature on sputter-deposited boron carbide films

Sputter deposition of B4C films with tailored physical properties remains a challenge. Here, we systematically study how substrate temperature influences the properties of B4C films deposited by direct current magnetron sputtering onto planar substrates held at temperatures in the range of 100-510°C. Results show that all films are amorphous stoichiometric B4C, with low O content of ~1 at. %. Films deposited onto substrates at 100°C exhibit high compressive residual stress and decreased mechanical properties. Therefore, for elevated substrate temperatures in the range of 180-510°C, film mass density, surface roughness, Young’s modulus, and hardness are weakly dependent on substrate temperature. However, in this temperature range, an increase in substrate temperature leads to larger residual compressive stress accompanied by a corresponding reduction in the concentration of nanoscale inhomogeneities. At least for the landing atom ballistics conditions studied here, a substrate temperature range of ~185-250°C is optimum for growing films with near-zero intrinsic residual stress. The overall weak substrate temperature dependence of film properties revealed in this work is favorable for the development of a robust deposition process, particularly for the case of deposition onto non-planar substrates where temperature control is often challenging.

36 MATERIALS SCIENCE↗

NASA NTRS1994

Micromechanical Modeling of the Thermal Expansion of Graphite/copper Composites with Nonuniform Microstructure

Two micromechanical models were developed to investigate the thermal expansion of graphite/copper (Gr/Cu) composites. The models incorporate the effects of temperature-dependent material properties, matrix inelasticity, initial residual stresses due to processing history, and nonuniform fiber distribution. The first model is based on the multiple concentric cylinder geometry, with each cylinder treated as a two-phase composite with a characteristic fiber volume fractions. By altering the fiber volume fraction of the individual cylinders, unidirectional composites with radially nonuniform fiber distributions can be investigated using this model. The second model is based on the inelastic lamination theory. By varying the fiber content in the individual laminae, composites with nonuniform fiber distribution in the thickness direction can be investigated. In both models, the properties of the individual regions (cylinders or laminae) are calculated using the method of cells micromechanical model. Classical incremental plasticity theory is used to model the inelastic response of the copper matrix at the microlevel. The models were used to characterize the effects of nonuniform fiber distribution on the thermal expansion of Gr/Cu. These effects were compared to the effects of matrix plasticity, choice of stress-free temperature, and slight fiber misalignment. It was found that the radially nonuniform fiber distribution has little effect on the thermal expansion of Gr/Cu but could become significant for composites with large fiber-matrix transverse CTE and Young's modulus mismatch. The effect of nonuniform fiber distribution in the through-thickness direction of a laminate was more significant, but only approached that of the stress-free temperature for the most extreme cases that include large amounts of bending. Subsequent comparison with experimental thermal expansion data indicated the need for more accurate characterization of the graphite fiber thermomechanical properties. Correlation with cyclic data revealed the presence of a mechanism not considered in the developed models. The predicted response did, however, exhibit ratcheting behavior that has been observed experimentally in Gr/Cu. Finally, simulation of the actual fiber distribution of particular specimens had little effect on the predicted thermal expansion.

Bednarcyk, Brett A.↗

DOE OSTI2023

Neural Network Enhanced RKPM for Electrochemical-Mechanical Coupled Damage Modeling of Energy Storage Materials

Energy storage materials undergo significant charge cycling, which makes understanding their reliability and durability fundamental in predicting performance and service life. Strong electrochemical-mechanical coupling and highly anisotropic material properties contribute to the formation and propagation of micro-cracking, largely along material interfaces and grain boundaries. For Li-ion batteries, for example, lithium moving between electrodes during charging and discharging process causes expansion and contraction of grains, and the strongly anisotropic and nonlinearly [Li]-dependent grain material properties can cause grains to expand into and contract away from each other, leading to chemo-mechanical cracking. In the first part of this work, a RKPM based computational framework for solving the coupled solid-phase lithium conservation with Fickian diffusion and the lithium concentration dependent anisotropic mechanical problem subjected to a highly nonlinear Butler-Volmer boundary condition is introduced. The choice of RKPM completeness conditions for lithium concentration and mechanical deformation fields, and the variational consistency condition for the domain integration of the coupled problem is first determined. In the second part of this work, a neural network-enhanced reproducing kernel particle method (NN-RKPM) [1] is leveraged to accurately capture damage and crack propagation throughout the material, by learning the location, orientation, and sharpness of discontinuity while allowing for a coarser nodal distribution than that is necessary for capturing sharp solution transitions using traditional mesh-based methods. NN-RKPM is used to inform how crack opening and closure in turn affect the coupled chemical equations and material microstructure.

damage modeling↗

DOE OSTI2020

Efficient Control of Atom Arrangement in Ternary Metal Chalcogenide Nanoparticles Using Precursor Oxidation State

Controlling both the concentration and the distribution of elements in a given material is often crucial to extracting and optimizing synergistic properties of the various constituents. An interesting class of such multielement materials is metal chalcogenide nanoparticles, which exhibit a wide range of composition-dependent optoelectronic properties including both bandgap-mediated processes and localized surface plasmon resonance properties, each of which is useful in applications ranging from energy conversion to sensing. Because metal chalcogenide nanoparticles can support several different metal elements in a variety of chalcogen lattices, this material class has particularly benefited from the ability to control both atom concentration and atom arrangement to tailor final particle properties. The primary method to access complex, multimetallic chalcogenide particles is via a postsynthetic cation exchange strategy. One-pot syntheses have been less explored to access these complex particles, although this route is desirable for economy and scalability. In this work, we compare the composition and morphology outcomes from cation exchange and one-pot preparation approaches using a Cu/Ag/Se system, which is already known to exhibit both binary and ternary metal chalcogenide phases. We show that at similar concentrations of the two metal cations, initial reaction conditions for the one-pot method yield multicomponent nanoparticles, whereas cation exchange yields homogeneous ternary metal chalcogenide structures. We then show that by tuning the precursor oxidation state for the one-pot method, this approach can be used to access homogeneous ternary metal chalcogenide particles that are similar in atom arrangement to the particles obtained using cation exchange. Taken together, our results demonstrate reliable synthetic methods that yield a variety of controlled compositions and composition morphologies in the Cu/Ag/Se system. Importantly, we demonstrate that this entire collection of architectures can all be accessed via a one-pot method simply by modifying metal precursor chemistry. The mechanistic insights gained and the resulting streamlined syntheses outlined indicate pathways to easily scaled, highly tailorable syntheses for rapid translation into downstream technologies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Multi-modal characterization of the B2 phase in the Ta-Re binary system

The energy and transportation industries demand materials that retain their mechanical property at high temperatures. Refractory complex concentrated alloys (RCCAs) with a BCC + B2 microstructure offer a potential solution, where maintaining the high temperature mechanical properties can be achieved by precipitation strengthening. This depends on the B2 phase in RCCAs being thermodynamically stable with a high solvus temperature. Recently, we predicted the high temperature stability of the B2 structure in the Ta-Re binary system, using density functional theory. Here, in this study, we provide experimental evidence for the existence of this phase for the first time, using a Ta 65 Re 35 alloy. Despite Ta-Re binary phase diagrams predicting a single-phase BCC microstructure for Ta 65 Re 35 , we show that a high Z nanoscale secondary phase appears after heat treatment at 1550 °C and 1100 °C. Scanning transmission electron microscopy (STEM) revealed that this phase has a cubic structure and is equiatomic TaRe though B2 superlattice reflections were absent in fast Fourier transforms (FFT) and diffraction patterns (DPs). DP simulations indicate that the B2 TaRe superlattice reflections are up to two orders of magnitude weaker than their fundamental reflections, making their detection challenging via electron microscopy. Neutron diffraction confirmed the second phase had a B2 structure. This study identified a previously unobserved high temperature stable B2 phase in the Ta-Re system, enabling the development of new high temperature BCC + B2 RCCAs.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Analytical modeling for redox flow battery design

Deeper market penetration of redox flow batteries requires optimization of the cell performance. Though important for optimization, detailed analytical solutions have not been developed for electrolyte flow, mass and charge transport, and reaction kinetics within redox flow batteries. To this end, here we present analytical solutions to active species concentration and over-potential based on advection-diffusion transport for ions and Bulter-Volmer model for interface reaction kinetics. The solutions were validated with results from a finite element model. These solutions were then applied to investigate the relationship between over-potential and state of charge, current density, reaction rate constant, flow velocity, diffusivity, total active species concentration, and electrode structure. Explicit formulas were identified for minimum activation over-potential and limiting current density as well as their dependence on electrolyte properties, operation conditions, and electrode structure. With our new mathematical formulas, this work provides a theoretical framework for flow battery design.

25 ENERGY STORAGE↗

DOE OSTI2021

Observations of Clouds, Aerosols, Precipitation, and Surface Radiation over the Southern Ocean: An Overview of CAPRICORN, MARCUS, MICRE, and SOCRATES

Weather and climate models are challenged by uncertainties and biases in simulating Southern Ocean (SO) radiative fluxes that trace to a poor understanding of cloud, aerosol, precipitation, and radiative processes, and their interactions. Projects between 2016 and 2018 used in situ probes, radar, lidar, and other instruments to make comprehensive measurements of thermodynamics, surface radiation, cloud, precipitation, aerosol, cloud condensation nuclei (CCN), and ice nucleating particles over the SO cold waters, and in ubiquitous liquid and mixed-phase clouds common to this pristine environment. Data including soundings were collected from the NSF–NCAR G-V aircraft flying north–south gradients south of Tasmania, at Macquarie Island, and on the R/V Investigator and RSV Aurora Australis. Synergistically these data characterize boundary layer and free troposphere environmental properties, and represent the most comprehensive data of this type available south of the oceanic polar front, in the cold sector of SO cyclones, and across seasons. Results show largely pristine environments with numerous small and few large aerosols above cloud, suggesting new particle formation and limited long-range transport from continents, high variability in CCN and cloud droplet concentrations, and ubiquitous supercooled water in thin, multilayered clouds, often with small-scale generating cells near cloud top. These observations demonstrate how cloud properties depend on aerosols while highlighting the importance of dynamics and turbulence that likely drive heterogeneity of cloud phase. Satellite retrievals confirmed low clouds were responsible for radiation biases. Furthermore, the combination of models and observations is examining how aerosols and meteorology couple to control SO water and energy budgets.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Microstructurally-Inspired Strategies to Print Tantalum and Tantalum-Tungsten Alloys

The goal of this project is to investigate strategies to print tantalum and tantalumtungsten alloys, which are notoriously difficult to print with consistent results because of the sensitivity of the properties to small concentrations of interstitial impurities (particularly oxygen) and microstructure, and hence to processing conditions. In direct metal laser sintering (DMLS) Ta, a strong dependence of porosity, grain morphology and texture on processing conditions was found.

36 MATERIALS SCIENCE↗

NASA NTRS2013

Effects of Systematic and Random Errors on the Retrieval of Particle Microphysical Properties from Multiwavelength Lidar Measurements Using Inversion with Regularization

In this work we study the effects of systematic and random errors on the inversion of multiwavelength (MW) lidar data using the well-known regularization technique to obtain vertically resolved aerosol microphysical properties. The software implementation used here was developed at the Physics Instrumentation Center (PIC) in Troitsk (Russia) in conjunction with the NASA/Goddard Space Flight Center. Its applicability to Raman lidar systems based on backscattering measurements at three wavelengths (355, 532 and 1064 nm) and extinction measurements at two wavelengths (355 and 532 nm) has been demonstrated widely. The systematic error sensitivity is quantified by first determining the retrieved parameters for a given set of optical input data consistent with three different sets of aerosol physical parameters. Then each optical input is perturbed by varying amounts and the inversion is repeated. Using bimodal aerosol size distributions, we find a generally linear dependence of the retrieved errors in the microphysical properties on the induced systematic errors in the optical data. For the retrievals of effective radius, number/surface/volume concentrations and fine-mode radius and volume, we find that these results are not significantly affected by the range of the constraints used in inversions. But significant sensitivity was found to the allowed range of the imaginary part of the particle refractive index. Our results also indicate that there exists an additive property for the deviations induced by the biases present in the individual optical data. This property permits the results here to be used to predict deviations in retrieved parameters when multiple input optical data are biased simultaneously as well as to study the influence of random errors on the retrievals. The above results are applied to questions regarding lidar design, in particular for the spaceborne multiwavelength lidar under consideration for the upcoming ACE mission.

vertical profiles↗

DOE OSTI2023

n-Propylbenzene Droplet Combustion: Experiments and Numerical Modeling

n-Propylbenzene (PB, C9H12, 432K boiling point) is important as a constituent in surrogates for some transportation fuels but little is understood about its droplet burning characteristics. We present an experimental and numerical study of a fuel droplet burning under conditions where the sole means of gas transport is fuel evaporation at the droplet surface thereby creating a one-dimensional gas transport that is amenable to detailed numerical modeling. The one-dimensional gas transport that results is amenable to detailed numerical modeling. Initial droplet diameters (Do) ranged from 0.3 mm to about 5 mm to better understand the mechanisms that control burning over such a wide range of Do. For Do < 1 mm droplets were burned while anchored to 14 m SiC fibers within a sealed container in free-fall during which time the droplets were ignited by spark discharge and the burning process recorded by video cameras. Larger and free-floating droplets were studied in the spaced-based platform of the orbiting International Space Station for Do > 1.0 mm which provided unlimited times for experimental observation. Measurements of droplet, flame and soot shell diameters were made and are discussed in the presentation. The experimental results showed formation of optically thick soot clouds developing during burning that required a robust image analysis algorithm to enable measurement of droplet diameter. The measured droplet diameters were well predicted by a numerical model that included soot formation, a PB kinetic mechanism comprising 576 species and 27369 reactions, unsteady gas and liquid transport, variable properties and radiative transport. Flame diameters showed more variability compared to the simulations, depending on how the flame was defined (peak gas temperature and OH concentration). Droplets burned slower as Do was increased and the PB sooting propensity increased with Do. Flame extinction was observed for Do > 3.3 mm indicating a strong effect of radiation as Do was increased compared to the smaller droplet diameters examined where extinction was not experimentally observed. For the largest droplets examined the possibility that the observed extinction is indicative of a transition to cool flame burning is still under investigation.

Guo, Songtao↗

DOE OSTI2023

Anion exchange membranes: The effect of reinforcement in water and electrolyte

Alkaline anion-conducting polymer-based CO 2 electrolysis and water electrolysis are among two emerging renewable energy conversion technologies. Their system design and integration offer promise of lower capital cost due to utilization of low-cost catalysts, in contrast to platinum group metal catalysts required for cation-conducting polymer-based devices. However, a critical component, the polymer electrolyte membrane, remains an obstacle hampering system performance and durability. In this study, commercially-available Sustainion® membranes with and without PTFE-reinforcement were investigated to understand previously unreported origins of improved device performance when compared to alternative membrane chemistries. We report critical membrane properties, such as morphology, thermal stability, as well as temperature-, hydration-, and counter-ion dependent ion conductivity. Moveover, the changes in uptake and conductivity of membranes in supporting electrolytes of K 2 CO 3 and KOH investigated as a function of their concentration. Presence of reinforcement and supporting electrolyte type alter the membrane's transport functionality, which could help guide device design for improved performance. In conclusion, the obtained results not only show how Sustainion® properties change with operating environment for CO 2 and water electrolysis applications, but also provide understanding for internal and external factors controlling anion-exhcnage membrane functionality in electrochemical devices.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS2018

A13H-2546: Intercomparison of biomass burning aerosol properties from in-situ and remote-sensing instruments in ORACLES-2016

The magnitude of the cumulative effects of aerosols, both directly and on cloud properties, remains the biggest source of uncertainty in our understanding of anthropogenic radiative forcing on the climate. The magnitude of aerosol effects in any given region will depend on not just the aerosol concentration, but also on the characteristics of the aerosol under consideration. The NASA ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) campaign was conducted in 2016-2018 over three deployments in the Southeast Atlantic Ocean (SEA), with the goal of making observations of seasonal biomass burning (BB) smoke plumes overlying persistent stratocumulus cloud decks. During the first ORACLES deployment (September 2016), two NASA aircraft (a P-3 and an ER-2) were flown with a suite of aerosol, cloud, radiation, and meteorological instruments for remote-sensing and in-situ observations. In ORACLES, data collected by eight different instrument teams are used to derive aerosol properties over this region by independent methods. Here we present a comparison of results from the different instrument retrievals with a focus on the measures of aerosol absorption. We focus on specific cases with near-coincident measurements from in-situ (PSAP or PTI for aerosol absorption combined with a nephelometer for aerosol scattering) and remote sensing (4STAR, AirMSPI, RSP, and SSFR) instruments from coordinated flights between the two aircraft. We use the single scattering albedo (SSA), a measure of the relative absorption versus total extinction by aerosols, as the main comparable property between the various remote sensing and in-situ methods. For the remote sensing instruments, we see general good agreement in the total aerosol loading (aerosol optical depth, AOD), though see some differences in the absorbing component (AAOD). We report values for the retrieved aerosol parameters measured in the ORACLES flights and comment upon the observed variability between different instruments. Finally, we discuss these ORACLES results in the context of previous measurements of BB aerosol over the SEA.

Kristina Pistone↗

DOE OSTI2023

Learning to concentrate: multi-tracer forecasts on local primordial non-Gaussianity with machine-learned bias

Local primordial non-Gaussianity (LPNG) is predicted by many non-minimal models of inflation, and creates a scale-dependent contribution to the power spectrum of large-scale structure (LSS) tracers, whose amplitude is characterized by b Φ . Knowledge of b Φ for the observed tracer population is therefore crucial for learning about inflation from LSS. Recently, it has been shown that the relationship between linear bias b 1 and b Φ for simulated halos exhibits significant secondary dependence on halo concentration. We leverage this fact to forecast multi-tracer constraints on ${f}^{loc}_{NL}$. We train a machine learning model on observable properties of simulated IllustrisTNG galaxies to predict b Φ for samples constructed to approximate DESI emission line galaxies (ELGs) and luminous red galaxies (LRGs). We find σ(${f}^{loc}_{NL}$) = 2.3, and σ(${f}^{loc}_{NL}$) = 3.7, respectively. These forecasted errors are roughly factors of 3, and 35% improvements over the single-tracer case for each sample, respectively. When considering both ELGs and LRGs in their overlap region, we forecast σ(${f}^{loc}_{NL}$) = 1.5 is attainable with our learned model, more than a factor of 3 improvement over the single-tracer case, while the ideal split by b Φ could reach σ(${f}^{loc}_{NL}$) < 1. In conclusion, we also perform multi-tracer forecasts for upcoming spectroscopic surveys targeting LPNG (MegaMapper, SPHEREx) and show that splitting tracer samples by b Φ can lead to an order-of-magnitude reduction in projected σ(${f}^{loc}_{NL}$) for these surveys.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗