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NASA NTRS2014

Pre-Test CFD for the Design and Execution of the Enhanced Injection and Mixing Project at NASA Langley Research Center

With the increasing costs of physics experiments and simultaneous increase in availability and maturity of computational tools it is not surprising that computational fluid dynamics (CFD) is playing an increasingly important role, not only in post-test investigations, but also in the early stages of experimental planning. This paper describes a CFD-based effort executed in close collaboration between computational fluid dynamicists and experimentalists to develop a virtual experiment during the early planning stages of the Enhanced Injection and Mixing project at NASA Langley Research Center. This projects aims to investigate supersonic combustion ramjet (scramjet) fuel injection and mixing physics, improve the understanding of underlying physical processes, and develop enhancement strategies and functional relationships relevant to flight Mach numbers greater than 8. The purpose of the virtual experiment was to provide flow field data to aid in the design of the experimental apparatus and the in-stream rake probes, to verify the nonintrusive measurements based on NO-PLIF, and to perform pre-test analysis of quantities obtainable from the experiment and CFD. The approach also allowed for the joint team to develop common data processing and analysis tools, and to test research ideas. The virtual experiment consisted of a series of Reynolds-averaged simulations (RAS). These simulations included the facility nozzle, the experimental apparatus with a baseline strut injector, and the test cabin. Pure helium and helium-air mixtures were used to determine the efficacy of different inert gases to model hydrogen injection. The results of the simulations were analyzed by computing mixing efficiency, total pressure recovery, and stream thrust potential. As the experimental effort progresses, the simulation results will be compared with the experimental data to calibrate the modeling constants present in the CFD and validate simulation fidelity. CFD will also be used to investigate different injector concepts, improve understanding of the flow structure and flow physics, and develop functional relationships. Both RAS and large eddy simulations (LES) are planned for post-test analysis of the experimental data.

Drozda, Tomasz G.↗

NASA NTRS2016

Calibration of the Fluorine, Chlorine and Hydrogen Content of Apatites With the ChemCam LIBS Instrument

Determining the composition of apatites is important to understand the behavior of volatiles during planetary differentiation. Apatite is an ubiquitous magmatic mineral in the SNC meteorites. It is a significant reservoir of halogens in these meteorites and has been used to estimate the halogen budget of Mars. Apatites have been identified in sandstones and pebbles at Gale crater by ChemCam, a Laser-Induced Breakdown Spectroscometer (LIBS) instrument onboard the Curiosity rover. Their presence was inferred from correlations between calcium, fluorine (using the CaF molecular band centered near 603 nm, whose detection limit is much lower that atomic or ionic lines and, in some cases, phosphorus (whose detection limit is much larger). An initial quantification of fluorine, based on fluorite (CaF2)/basalt mixtures and obtained at the LANL laboratory, indicated that the excess of F/Ca (compared to the stoichiometry of pure fluorapatites) found on Mars in some cases could be explained by the presence of fluorite. Chlorine was not detected in these targets, at least above a detection limit of 0.6 wt% estimated from. Fluorapatite was later also detected by X-ray diffraction (with CheMin) at a level of approx.1wt% in the Windjana drill sample (Kimberley area), and several points analyzed by ChemCam in this area also revealed a correlation between Ca and F. The in situ detection of F-rich, Cl-poor apatites contrasts with the Cl-rich, F-poor compositions of apatites found in basaltic shergottites and in gabbroic clasts from the martian meteorite NWA 7034, which were also found to be more Cl-rich than apatites from basalts on Earth, the Moon, or Vesta. The in situ observations could call into question one of the few possible explanations brought forward to explain the SNC results, namely that Mars may be highly depleted in fluorine. The purpose of the present study is to refine the calibration of the F, Cl, OH and P signals measured by the ChemCam LIBS instrument, initiated for F, for Cl in soils, for P, and estimate their limit of detection. For this purpose, different types of apatites and mixtures of basalt powder and apatites were analyzed using ChemCam Engineering Qualification Model (EQM) at IRAP, Toulouse. The present abstract presents the initial results from the laboratory analyses. Differences between the response function of the EQM and the Flight Model of ChemCam are still to be refined to apply these new results to the Martian dataset.

Meslin, P.-Y.↗

NASA NTRS2016

HST-STIS Spectra of Saturn's Rings and Implications for Their Reddening Agent

We obtained HST-STIS spectra of Saturn's main rings in May 2011, using the G230L (and G430L) gratings, with final averaged radial resolution of 160 (and 330) km/pixel. The dataset filled a previous 200-330nm "spectral gap" between Cassini and ground-based spectra. The data provide radial profiles as a function of wavelength, but our most basic product at this point is a set of very low-noise spectra, radially averaged over broad regions of the rings (A, B, C, and Cassini Division). The raw spectra required special processing to remove artifacts due to extended-source grating scatter. We have modeled the spectra using a new particle surface model, which corrects for on-surface shadowing due to the likely very rough ring particle surfaces, and avoids overestimation of intra-mixed "neutral absorber". We correct for non-classical layer effects and finite ring optical depth, and relate our observed reflectivities to the spherical albedos of individual smooth particles. We model these smooth particle albedos using standard Hapke theory for regolith grain mixtures that are either homogeneous and "intramixed" (nonicy absorbers dispersed in water ice regolith grains) or heterogeneous "intimate" mixtures. As candidates for the nonicy contaminants we have considered amorphous carbon, aromatic-rich and aliphatic-rich organic tholins, silicates, hematite and iron metal. For the A and B rings, we find that iron metal (including a new theoretical estimate of the refractive indices of nanometer-sized grains of iron) is not spectrally steep enough in the 200-300nm range, and that aliphatic-rich tholins are either too steep at short wavelengths or too flat at long wavelengths. However, less than 1% by mass of aromatic-rich tholins provides a very good fit across the entire spectral range with no gratuitous "neutral absorber" needed, and a minimum of additional free parameters. The best fits require forward-scattering regolith grains. For the C Ring and Cassini Division, additional absorbers are needed (updated results will be given).

Saturn's Rings↗

DOE OSTI2025

Demystifying the Resilience of Large Language Models: An End-to-End Perspective

Deep neural networks are known to be resilient to random bit-wise faults in their parameters. However, this resilience has primarily been established through evaluations of classification models. The extent to which this claim holds for large-language models remains underexplored. In this work, we conduct an extensive measurement study on the impact of random bitwise faults in commercial-scale language models. We perform an in-depth analysis of the resulting generation outputs. We first expose that these language models are not truly resilient to random bit-flips. While aggregate metrics such as accuracy may suggest resilience, an in-depth inspection of the generated outputs shows significant degradation in text quality. Our analysis also shows that tasks requiring more complex reasoning suffer more from performance and quality degradation. Moreover, we extend our analysis to models with augmented reasoning capabilities, such as Chain-of-Thought or Mixture of Experts architectures, and characterize their failure scenarios under random bit-flips.

Sun, Yu↗

NASA NTRS2000

Surfactant Facilitated Spreading of Aqueous Drops on Hydrophobic Surfaces

Microgravity technologies often require aqueous phases to spread over nonwetting hydrophobic solid/surfaces. At a hydrophobic surface, the air/hydrophobic solid tension is low, and the solid/aqueous tension is high. A large contact angle forms as the aqueous/air tension acts together with the solid/air tension to balance the large solid/aqueous tension. The aqueous phase, instead of spreading, is held in a meniscus by the large angle. Surfactants facilitate the wetting of water on hydrophobic surfaces by adsorbing on the water/air and hydrophobic solid/water interfaces and lowering the surface tensions of these interfaces. The tension reductions decrease the contact angle, which increases the equilibrium wetted area. Hydrocarbon surfactants (i.e. amphiphiles with a hydrophobic chain of methylene groups attached to a large polar group to give aqueous solubility) do not reduce significantly the contact angles of the very hydrophobic surfaces such as parafilm or polyethylene. Trisiloxane surfactants (amphiphiles with a hydrophobe consisting of methyl groups linked to a trisiloxane backbone in the form of a disk ((CH3)3-Si-O-Si-O-Si(CH3)3)) and an extended ethoxylate (-(OCH2CH2)n-) polar group in the form of a chain with seven or eight units) can significantly reduce the contact angle of water on a very hydrophobic surface and cause rapid and complete (or nearly complete) spreading (lermed superspreading). The overall goal of the research described in this proposal is to establish and verify a theory for how trisiloxanes cause superspreading, and then use this knowledge as a guide to developing more general hydrocarbon based surfactant systems which superspread and can be used in microgravity. We propose that the trisiloxane surfactants superspread when the siloxane adsorbs, the hydrophobic disk parts of the molecule adsorb onto the surface removing the surface water. Since the cross sectional area of the disk is larger than that of the extended ethoxylate chain, the disks can form a space filling mat on the surface which removes a significant amount of the surface water. The water adjacent to the hydrophobic solid surface is of high energy due to incomplete hydrogen bonding; its removal significantly lowers the tension and reduces the contact angle. Hydrocarbon surfactants cannot remove as much surface water because their large polar groups prevent the chains from cohering lengthwise. In our report last year we presented a poster describing the preparation of model very hydrophobic surfaces which are homogeneous and atomically smooth using self assembled monolayers of octadecyl trichlorosilane (OTS). In this poster we will use these surfaces as test substrates in developing hydrocarbon based surfactant systems which superspread. We studied a binary hydrocarbon surfactant systems consisting of a very soluble large polar group polyethylene oxide surfactant (C12E6 (CH3(CH2)11(OCH2CH2)6OH) and a long chain alcohol dodecanol. By mixing the alcohol with this soluble surfactant we have found that the contact angle of the mixed system on our test hydrophobic surfaces is very low. We hypothesize that the alcohol fills in the gaps between adjacent adsorbed chains of the large polar group surfactant. This filling in removes the surface water and effects the decrease in contact angle. We confirm this hypothesis by demonstrating that at the air/water interface the mixed layer forms condensed phases while the soluble large polar group surfactant by itself does not. We present drop impact experiments which demonstrate that the dodecanol/C12E6 mixture is effective in causing impacting drops to spread on the very hydrophobic model OTS surfaces.

Kumar, Nitin↗

DOE OSTI2023

Modeling the co-assembly of binary nanoparticles

Abstract In this work, we present a binary assembly model that can predict the co-assembly structure and spatial frequency spectra of monodispersed nanoparticles with two different particle sizes. The approach relies on an iterative algorithm based on geometric constraints, which can simulate the assembly patterns of particles with two distinct diameters, size distributions, and at various mixture ratios on a planar surface. The two-dimensional spatial-frequency spectra of the modeled assembles can be analyzed using fast Fourier transform analysis to examine their frequency content. The simulated co-assembly structures and spectra are compared with assembled nanoparticles fabricated using transfer coating method are in qualitative agreement with the experimental results. The co-assembly model can also be used to predict the peak spatial frequency and the full-width at half-maximum bandwidth, which can lead to the design of the structure spectra by selection of different monodispersed particles. This work can find applications in fabrication of non-periodic nanostructures for functional surfaces, light extraction structures, and broadband nanophotonics.

Mohanty, Saurav (ORCID:0009000302592855)↗

NASA NTRS2010

Z-Pinch Pulsed Plasma Propulsion Technology Development

Fusion-based propulsion can enable fast interplanetary transportation. Magneto-inertial fusion (MIF) is an approach which has been shown to potentially lead to a low cost, small reactor for fusion break even. The Z-Pinch/dense plasma focus method is an MIF concept in which a column of gas is compressed to thermonuclear conditions by an axial current (I approximates 100 MA). Recent advancements in experiments and the theoretical understanding of this concept suggest favorable scaling of fusion power output yield as I(sup 4). This document presents a conceptual design of a Z-Pinch fusion propulsion system and a vehicle for human exploration. The purpose of this study is to apply Z-Pinch fusion principles to the design of a propulsion system for an interplanetary spacecraft. This study took four steps in service of that objective; these steps are identified below. 1. Z-Pinch Modeling and Analysis: There is a wealth of literature characterizing Z-Pinch physics and existing Z-Pinch physics models. In order to be useful in engineering analysis, simplified Z-Pinch fusion thermodynamic models are required to give propulsion engineers the quantity of plasma, plasma temperature, rate of expansion, etc. The study team developed these models in this study. 2. Propulsion Modeling and Analysis: While the Z-Pinch models characterize the fusion process itself, propulsion models calculate the parameters that characterize the propulsion system (thrust, specific impulse, etc.) The study team developed a Z-Pinch propulsion model and used it to determine the best values for pulse rate, amount of propellant per pulse, and mixture ratio of the D-T and liner materials as well as the resulting thrust and specific impulse of the system. 3. Mission Analysis: Several potential missions were studied. Trajectory analysis using data from the propulsion model was used to determine the duration of the propulsion burns, the amount of propellant expended to complete each mission considered. 4. Vehicle Design: To understand the applicability of Z-Pinch propulsion to interplanetary travel, it is necessary to design a concept vehicle that uses it -- the propulsion system significantly impacts the design of the electrical, thermal control, avionics and structural subsystems of a vehicle. The study team developed a conceptual design of an interplanetary vehicle that transports crew and cargo to Mars and back and can be reused for other missions. Several aspects of this vehicle are based on a previous crewed fusion vehicle study -- the Human Outer Planet Exploration (HOPE) Magnetized Target Fusion (MTF) vehicle. Portions of the vehicle design were used outright and others were modified from the MTF design in order to maintain comparability.

Polsgrove, Tara↗

NASA NTRS1991

Sm-Nd and Rb-Sr isotopic systematics of ureilites

The present evaluation of Sm-Nd and Rb-Sr isotopic data for seven ureilites establishes their divisions into three groups on the bases of Sm-Nd isotopic systematics. The first group of ureilites is made up of whole-rock samples whose highly depleted assemblages indicate Sm-Nd model ages consistent with 4.55 Ga. The second group of whole-rock samples of Kenna, Novo Urei, and ALHA77257 are heterogeneous mixtures of an unidentified light REE-enriched component and a light REE-depleted olivine-pyroxene assemblage. In the third group, LEW85440 neither has a model Sm-Nd age of 4.55 Ga nor plots of the 3.74 Ga isochron of the Kenna group; it might have had an evolution similar to the Kenna group, but involving different times and/or isotopic compositions.

Goodrich, Cyrena Anne↗

DOE OSTI2021

Validation of the HyRAM+ physics models for use with propane

The Hydrogen Risk Assessment Model Plus (HyRAM+) toolkit combines quantitative risk assessment with simulations of unignited dispersion, ignited turbulent diffusion flames, and indoor accumulation with delayed ignition of fuels. HyRAM+ is differentiated from HyRAM in that it includes models and leak data for other alternate fuels. The models of the physical phenomena need to be validated for each of the fuels in the toolkit. This report shows the validation for propane which is being used as a surrogate for autogas, which is a mixture of propane and butane and used in internal combustion engines in vehicles. For flame length comparisons, five previously published experiments from peer reviewed journals were used to validate our models. The validation looked at flame lengths and flame widths with respect to different leak diameters, mass flow rates, and source pressures. Most of the sources included more than one set of experimental data, which were collected using different methods (CCD cameras, IR visualization etc.). In general, HyRAM+ overpredicts the flame lengths by around 65%. For heat and radiation models, we compared the heat flux and radiation data reported from two different sources to the values calculated by HyRAM+. For higher mass flow rates, the HyRAM+ calculated flame length results gave a better estimate of what is found in the experiments (65% error), but a higher error (85%) is observed between the HyRAM+ calculated lengths and the experimental flame lengthsfor lower mass flows. Some differences can be attributed to outdoor environmental effects (i.e. wind speed) and uncertainties in jet flame shapes. The propane flame trajectory is predicted for a high Reynolds number case with Re = 12,500 and a low Reynolds number case where Re = 2,000. The Re=12,500 case which is momentum dominated matches well with the experimental flame trajectory, but the agreement for the bouancy driven low Reynolds number case is not as good. Dispersion modeling for unignited propane was also analyzed. We compared the mole fraction, mixture fraction, mean velocity, concentration half width, and inverse mass concentration over an axial distance from different credible journals to the values calculated by HyRAM+. The results display good agreement but generally, HyRAM+ predicts a wider profile for mole fraction and mixture fraction experiments. Overall, HyRAM+’s results are reasonable for predicting the flame length, heat flux, flame trajectory, and dispersion for propane and can be used in risk analyses

08 HYDROGEN↗

DOE OSTI2020

Benchmark Solutions for Radiation Transport in Stochastic Media with Inhomogeneous Material Statistics

Accurately solving implicit Monte Carlo (IMC) thermal photon transport problems with mixed material cells is important in realistic applications. The production IMC package at LLNL treats mixed material cells arising from ALE remap and hydrodynamics using the same approximate model. The new Imp IMC thermal photon transport package currently under development has both a material interface reconstruction (MIR) algorithm and a Levermore-Pomraning (LP) stochastic medium algorithm for treating mixed material cells. Existing stochastic medium algorithms for treating mixed material cells in IMC lack a complete theoretical basis. The IMC LP algorithm implementation has been demonstrated to reproduce published deterministic LP solutions for the particular case of spatially homogeneous material statistics. Realistic simulations will include spatially inhomogeneous material statistics (material mean chord lengths). In a previous investigation, the LP-model for transport in binary stochastic media in rod geometry was generalized to accommodate spatially varying material chord lengths, i.e., the mixing statistics were allowed to be nonhomogeneous. Analytical solutions were obtained and used to produce a verifi cation suite for the Imp IMC Levermore-Pomraning implementation for different spatial variations of the chord lengths. However, the accuracy of the LP model when the mixing statistics are nonhomogeneous has not been assessed and leaves open the question of whether local accuracy is improved or further degraded when chord lengths are not uniform. This shortcoming is rectifi ed here by developing benchmark analytic solutions for transport in binary Markovian stochastic mixtures in rod geometry with nonhomogeneous mixing statistics, using spatially varying chord lengths considered in the previous investigation based on the LP model. Methods for sampling a nonhomogeneous Poisson process (NHPP) are first described and used to construct individual realizations of the binary mixtures in rod geometry. Analytic solutions are then obtained for the forward and backward directed fluxes on a given realization, now viewed as a deterministic medium with alternating layers of the two materials with known interface locations. Finally, material averaged scalar fluxes are obtained using these sampling schemes with spatially linear and quadratic chord lengths and used to assess the accuracy of the previously obtained LP-model results.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2020

Experimental and DFT Calculated IR Spectra of Guests in Zeolites: Acyclic Olefins and Host-Guest Interactions

We performed experimental and periodic density functional theory (DFT) IR spectroscopy to investigate the adsorption of acyclic olefins over both acidic and non-acidic zeolites. Two conjugated polyenes, 2,4-dimethyl-1,3-pentadiene (I) and 2,6-dimethyl-2,4,6-octatriene (II) were studied to probe organic intermediates that can form during methanol conversion, and that can lead to deactivating species known collectively as “coke.” We computed vibrational spectra using zeolite-adsorbed and gas-phase models for both neutral and protonated forms of I and II, and compared these DFT results to diffuse reflectance IR Fourier transform (DRIFT) spectra of zeolite-guest systems. Our experimental and computational results are precise enough to pinpoint that the gauche s-cis conformation of species I predominates during adsorption over de-aluminated zeolite beta. Computed zeolite-adsorbed spectra of the protonated species I and II best represent the DRIFT spectra obtained after the adsorption of the olefins on HMOR at 20 ?, with computed bands at 1543 and 1562 cm–1 for molecules I+ and II+, respectively, attributed to the allylic stretching mode, ?(C=C–C+). These computed band frequencies are within 6 cm–1 of experimental data and confirm that the interaction between neutral acyclic olefins and acidic zeolites leads to protonation of the olefin. Comparison of computed spectra of the protonated species in the gas phase to those in the zeolite indicates that the electrostatic interaction between alkenyl and alkadienyl cations and negative zeolite framework does not significantly impact the position of the allylic stretching bands. These results highlight that computed spectroscopy and thermodynamics coupled with experimental spectra can be used for elucidating complex mixtures in zeolites, and certain spectral features of adsorbed olefins can be accurately modeled by gas-phase calculations. ACKNOWLEDGMENTS BM and SMA were supported by the National Science Foundation under Award # CBET-1512442. Acknowledgment is made to the Donors of the American Chemical Society Petroleum Research Fund for support (or partial support) of this research (#589978-ND5, EDH and FCJ). MDB was supported by the US Department of Energy (DOE), Office of Science, Office of Basic Energy Sciences (BES), Division of Materials Science and Engineering. CJM was supported by the DOE, Office of Science, BES, Division of Chemical Sciences, Geosciences, and Biosciences. Pacific Northwest National Laboratory (PNNL) is a multiprogram national laboratory operated by Battelle for the U.S. DOE. Computing resources were generously provided through PNNL’s institutional computing (PIC).

Manookian, Babgen↗

DOE OSTI2025

Effect of particle shape on stratification in drying films of binary colloidal mixtures

The role of particle shape in evaporation-induced auto-stratification in polydisperse colloidal suspensions is explored with molecular dynamics simulations of mixtures of spheres and aspherical particles. A unified framework based on the competition between diffusion and diffusiophoresis is proposed to understand the effects of shape and size dispersity. In general, particles diffusing more slowly (e.g., larger particles) tend to accumulate more strongly at the evaporation front. However, larger particles have larger surface areas and therefore greater diffusiophoretic mobility. Hence, they are more likely to be driven away from the evaporation front via diffusiophoresis. For a rapidly dried bidisperse suspension containing small and large spheres, the competition leads to “small-on-top” stratification. Here, we employ a computational model in which the diffusion coefficient is inversely proportional to particle mass. For a mixture of spheres and aspherical particles with similar mass, the diffusion contrast is reduced, and the spheres are always enriched at the evaporation front as they have the smallest surface area for a given mass and, therefore, the lowest diffusiophoretic mobility. Furthermore, for a mixture of solid and hollow spheres that have the same outer radius and thus the same surface area, the diffusiophoretic contrast is suppressed, and the system is dominated by diffusion. Consequently, the solid spheres, which have a larger mass and diffuse more slowly, accumulate on top of the hollow spheres. Finally, for a mixture of thin disks and long rods that differ significantly in shape but have similar mass and surface area, both diffusion and diffusiophoresis contrasts are suppressed, and the mixture does not stratify.

Classical molecular dynamic simulations↗

NASA NTRS2009

Ultimate Temperature of Pulse Tube Cryocoolers

An ideal pulse tube cryocooler using an ideal gas can operate at any temperature. This is not true for real gases. The enthalpy flow resulting from the real gas effects of 3He, 4He, and their mixtures in ideal pulse tube cryocoolers puts limits on the operating temperature of pulse tube cryocoolers. The discussion of these effects follows a previous description of the real gas effects in ideal pulse tube cryocoolers and makes use of models of the thermophysical properties of 3He and 4He. Published data is used to extend the analysis to mixtures of 3He and 4He. The analysis was done for pressures below 2 MPa and temperatures below 2.5 K. Both gases and their mixtures show low temperature limits for pulse tube cryocoolers. These limits are in the 0.5-2.2 K range and depend on pressure and mixture. In some circumstances, even lower temperatures may be possible. Pulse tube cryocoolers using the ha-fluid properties of dilute 3He in superfluid 4He appear to have no limit.

Kittel, Peter↗

DOE OSTI2023

Plasma-parameter dependence of ro-vibrational temperatures for H 2 in LHD divertor

We analyzed a thousand visible spectra of Fulcher-α band measured for divertor plasmas in Large Helical Device. With a coronal model and Bayesian inference, the population distribution of hydrogen molecule in the electronic ground state was estimated. The non-thermal population distribution was recovered with a two-temperature model, which has two sets of rotational and vibrational temperatures, as well as their mixture coefficient. The lower rotational temperature significantly changes according to the plasma parameters. Its nearly linear dependence on the electron density was found, which is consistent with previous works. The lower vibrational temperature also shows a small density dependence, as reported by a previous work. On the other hand, the higher rotational and vibrational temperatures as well as the mixture coefficient only show slight changes over the broad range of plasma parameters. These population parameters show a significant correlation; with higher electron density, all the temperatures and the fraction of the higher-temperature component increase simultaneously. In conclusion, this suggests that the electron impact plays an important role to determine the population distribution.

42 ENGINEERING↗

DOE OSTI2021

Probabilistic Deep Learning Approach to Automate the Interpretation of Multi-phase Diffraction Spectra

Autonomous synthesis and characterization of inorganic materials requires the automatic and accurate analysis of X-ray diffraction spectra. For this task, we designed a probabilistic deep learning algorithm to identify complex multi-phase mixtures. At the core of this algorithm lies an ensemble convolutional neural network trained on simulated diffraction spectra, which are systematically augmented with physics-informed perturbations to account for artifacts that can arise during experimental sample preparation and synthesis. In this work, larger perturbations associated with off-stoichiometry are also captured by supplementing the training set with hypothetical solid solutions. Spectra containing mixtures of materials are analyzed with a newly developed branching algorithm that utilizes the probabilistic nature of the neural network to explore suspected mixtures and identify the set of phases that maximize confidence in the prediction. Our model is benchmarked on simulated and experimentally measured diffraction spectra, showing exceptional performance with accuracies exceeding those given by previously reported methods based on profile matching and deep learning. We envision that the algorithm presented here may be integrated in experimental workflows to facilitate the high-throughput and autonomous discovery of inorganic materials.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Predicting Particle-Size Distributions in Fuel-Cell Inks

Prediction of the catalyst-activated carbon particle sizes of fuel-cell inks remains a critical challenge in enhancing the performance and durability of fuel cells. The performance and structural integrity of the catalyst layers in the cell depend not only on the properties of the ionomer, but also on the carbon supports that host the catalyst. To investigate how these carbon aggregate structures form, we present a model that calculates the cooperative size distributions of ionomer and carbon aggregates in various water/alcohol mixtures and compares those results to available experimental data. Aggregation of both the suspended ionomers and the carbon particles is interwoven as the carbon aggregation depends heavily on the ionic strength of its environment, namely protons dissociating from the ionomer’s sulfonic-acid-group side chains. We demonstrate that the surrounding mixed solvent as well as Nafion TM binder concentration strongly influence the degree of aggregation for carbon particles. The validated model provides a framework for exploring aggregation under a wide range of conditions for various electrochemical-technology inks.

Srivastav, Harsh [University of California, Berkel↗

NASA NTRS1972

Thermodynamic models in cosmochemical systems.

Generalized computer methods are developed for inferring details of the formation of cosmochemical systems. Compositions of ideal gas mixtures existing in equilibrium with multicomponent solid and liquid phases are calculated. A comparison of computed results with experimental data is made for the ternary system MgO-FeO-SiO2. While the ideal-solution approximation is shown to be inaccurate in dealing with the silicate melts, the stable phases and compositions can be accurately calculated in a system where there are only solids and gas. A model system containing the elements H, O, Si, Mg, S, C, Cl, and F is investigated over a range of compositions involving the gas and ten solid phases, to show the power of the technique in dealing with complex gas-solid equilibria. Systems close to cosmic composition are next considered, both with and without iron.

Griffiths, P. R.↗

NASA NTRS1994

Factors and processes governing the C-14 content of carbonate in desert soils

A model is presented describing the factors and processes which determine the measured C-14 ages of soil calcium carbonate. Pedogenic carbonate forms in isotopic equilium with soil CO2. Carbon dioxide in soils is a mixture of CO2 derived from two biological sources: respiration by living plant roots and respiration of microorganisms decomposing soil humus. The relative proportion of these two CO2 sources can greatly affect the initial C-14 content of pedogenic carbonate: the greater the contribution of humus-derived CO2, the greater the initial C-14 age of the carbonate mineral. For any given mixture of CO2 sources, the steady-state (14)CO2 distribution vs. soil depth can be described by a production/diffusion model. As a soil ages, the C-14 age of soil humus increases, as does the steady-state C-14 age of soil CO2 and the initial C-14 age of any pedogenic carbonate which forms. The mean C-14 age of a complete pedogenic carbonate coating or nodule will underestimate the true age of the soil carbonate. This discrepancy increases the older a soil becomes. Partial removal of outer (and younger) carbonate coatings greatly improves the relationship between measured C-14 age and true age. Although the production/diffusion model qualitatively explains the C-14 age of pedogenic carbonate vs. soil depth in many soils, other factors, such as climate change, may contribute to the observed trends, particularily in soils older than the Holocene.

Amundson, Ronald↗