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These codes estimate effective diffusivity for species transport in materials and simultaneously fit multiple temperatures of measured isotherm and effective diffusivities for sorption transport of species through materials. Assumes triple-mode type sorption thermodynamics with mobile and immobile species in quasi-equilibrium.
We use canonical variational theory (CVT) with small-curvature tunneling (SCT) contributions to investigate quantum effects on the H 2 diffusion process in the pure-silica zeolite RHO. At low temperature we find an inverse kinetic isotopic sieving effect in that the heavier isotopic species diffuses faster than the lighter one. Three quantum effects contribute to this kinetic isotope effect (KIE). The first one is quantum mechanical tunneling; this—on its own—would lead to a normal kinetic isotopic sieving effect, in which lighter diprotium diffuses faster than dideuterium. The second factor, which we find to dominate in the present case, is zero-point energy (ZPE). Deuterium has a lower ZPE, which leads to a smaller effective barrier for tunneling because the transition state has a larger ZPE than the precursor stable state; this results in an inverse KIE. The third factor, the thermal vibrational energy (computed from the quantized vibrational partition function), also favors a normal KIE, but it is outweighed by the ZPE effect. The vibrations of the zeolite host framework are found to play an important role at low temperatures, and our calculations consider up to 7296 degrees of freedom at the equilibrium structure and the saddle point and up to 221 degrees of freedom along the reaction path. In conclusion, the importance of quantum considerations on the dynamics is elucidated by comparison to a purely classical treatment.
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A reaction–diffusion shrinking core model describing the decay in diffusivity of supported amine sorbents upon CO 2 sorption under both simulated direct air capture and point source capture conditions is described. The decay in CO 2 diffusivity is associated with crosslinking in the aminopolymer samples and general pore blockage in the amino-silane derived samples, which occurs as CO 2 is adsorbed. The model is used to extract four kinetic parameters that govern the CO 2 uptake kinetics and working capacity: an apparent reaction rate constant, an initial effective diffusivity, and two dimensionless decay parameters. Ideally, an initially reaction limited system would allow for direct determination of the intrinsic reaction rate constant; however, sorption experiments suggest mass transfer resistances related to gas mixing, external boundary layers and intraparticle diffusion are present. Reaction rate constants are determined and agree well with theoretical values predicted with the Eyring equation parameterized using density functional theory energies from literature sources. The kinetic performance is expressed as the average effective diffusivity as a function of average conversion, which can be correlated to the dispersion of sorption sites on the support and the morphology of the active sorbent phase. Four supports are impregnated or grafted with amines, SBA-15, single-walled zeolite nanotubes (ZNT), Syloid SiO 2 , and γ-Al 2 O 3 . Due to its pore structure, γ-Al 2 O 3 supported amines can be modeled at the μm scale or at the nm scale, where the shell balance is on the μm-sized macroporous particle aggregate or on the nm-sized amine film on the surface of the Al 2 O 3 nanoparticles, which comprise the spherical particle aggregates. Faster diffusion rates are maintained under 400 ppm rather than 10% CO 2 due to a slower reaction rate giving a slower decay in diffusivity. In conclusion, this work provides a first principles kinetic analysis of CO 2 sorption where previous models are semi-empirical and use arbitrary kinetic parameters.
Highlights: • Ti{sub 3}Al alloy to Ni-based superalloy was successfully brazed using Ag-21Cu-25Pd filler metal. • Phases TiPd (fcc), Ti{sub 3}Pd{sub 5} (bct) and AlPd (hcp) formed within the Ti{sub 3}Al/Ni-based superalloy joint. • Diffusion behavior of elements and its influence on joint interfacial microstructure were revealed. • A formation model of interfacial microstructure has been established. • The joint tensile strength at room temperature reached 404MPa, and the strength of 212MPa was maintained at 773 K. - Abstract: Dissimilar joining of a Ti{sub 3}Al-based alloy to a Ni-based superalloy has been conducted using Ag-21Cu-25Pd filler metal. The joint microstructures were analyzed using SEM, EPMA, XRD and TEM. The reaction behaviors between different elements were discussed. Due to the strong affinity, element Pd mainly reacted with Ti{sub 3}Al substrate and formed intermetallic compounds of TiPd, Ti{sub 3}Pd{sub 5} and AlPd. Elements Ni and Ti reacted with each other and caused the formation of Ni{sub 3}Ti in the centre of the joint. Owing to the diffusion effect, element Ag was enriched in the joint central area as (Ag,Cu){sub ss}. With the prolonging of the brazing time varying from 3 min to 15 min at 1253 K, the tensile strength of the joint firstly increased and then decreased. The joints brazed at 1253 K for 10 min presented the maximum strength of 404 MPa at room temperature, and the joint strength of 212 MPa was maintained at 773 K. The total fracture surface covered the most of the reaction zones from the (Ag,Cu){sub ss} to the diffusion effect zone at the Ti{sub 3}Al side.
Families of recurring low-frequency earthquakes (LFEs) within nonvolcanic tremor on the San Andreas Fault in central California are sensitive to tidal stresses. LFEs occur at all levels of the tides, are strongly correlated and in phase with the ~200 Pa shear stresses, and weakly and not systematically correlated with the ~2 kPa tidal normal stresses. Here, we assume that LFEs are small sources that repeatedly fail during shear within a much larger scale, aseismically slipping fault zone and consider two different models of the fault slip: (1) modulation of the fault slip rate by the tidal stresses or (2) episodic slip, triggered by the tides. LFEs are strongly clustered with duration much shorter than the semidiurnal tide; they cannot be significantly modulated on that time scale. The recurrence times of clusters, however, are many times longer than the semidiurnal, leading to an appearance of tidal triggering. In this context we examine the predictions of laboratory-observed triggered frictional (dilatant) fault slip. The undrained end-member model produces no sensitivity to the tidal normal stress, and slip onsets are in phase with the tidal shear stress. The tidal correlation constrains the diffusivity to be less than ~1 × 10 -6 /s and the product of the friction and dilatancy coefficients to be at most 5 × 10 -7 , orders of magnitude smaller than observed at room temperature. In the absence of dilatancy the effective normal stress at failure would be about ~55 kPa. Finally, for this model the observations require intrinsic weakness, low dilatancy, and lithostatic pore fluid.
Block ionomers cast from solution exhibit solvent-templated morphologies that can be altered by solvent-vapor annealing. When cast from a mixed solvent, a midblock-sulfonated pentablock ionomer self-assembles into spherical ionic microdomains that are loosely connected. Upon exposure to liquid water, nanoscale channels irreversibly develop between the microdomains due to swelling and form a continuous mesoscale network. In this work, we use electron tomography and real-time X-ray scattering to follow this transformation and show that the resultant morphology provides a highly effective diffusive pathway.
The reactive transport code CrunchClay was used to derive effective diffusion coefficients (D e ), clay porosities (ε), and adsorption distribution coefficients (K D ) from through-diffusion data while considering accurately the influence of unavoidable experimental biases on the estimation of these diffusion parameters. These effects include the presence of filters holding the solid sample in place, the variations in concentration gradients across the diffusion cell due to sampling events, the impact of tubing/dead volumes on the estimation of diffusive fluxes and sample porosity, and the effects of O-ring-filter setups on the delivery of solutions to the clay packing. Doing so, the direct modeling of the measurements of (radio)tracer concentrations in reservoirs is more accurate than that of data converted directly into diffusive fluxes. While the above-mentioned effects have already been described individually in the literature, a consistent modeling approach addressing all these issues at the same time has never been described nor made easily available to the community. A graphical user interface, CrunchEase, was created, which supports the user by automating the creation of input files, the running of simulations, and the extraction and comparison of data and simulation results. While a classical model considering an effective diffusion coefficient, a porosity and a solid/solution distribution coefficient (D e –ε–K D ) may be implemented in any reactive transport code, the development of CrunchEase makes it easy to apply by experimentalists without a background in reactive transport modeling. CrunchEase makes it also possible to transition more easily from a D e –ε–K D modeling approach to a state-of-the-art process-based understanding modeling approach using the full capabilities of CrunchClay, which include surface complexation modeling and a multi-porosity description of the clay packing with charged diffuse layers.
Multifunctional porous materials are increasingly needed across various fields, but their complex microstructures create significant challenges due to the intricate microstructure-property relationships. This complexity, combined with limitations of traditional analysis methods, hinders efforts to understand and optimize microstructure–property relationships. Here, to address this, we integrate physics-based mesoscale modeling with interpretable machine learning (ML) to uncover how microstructural features govern effective diffusivity and elastic modulus. At constant porosity, we show diffusivity varies by over 150 × and modulus by ∼50 ×, highlighting the power of microstructure engineering. Statistical analysis reveals bimodal behavior in diffusivity and unimodal in modulus. ML identifies connectivity as the dominant factor, while modulus is also sensitive to domain size and feature interactions. Controlled simulations further highlight domain shape as a critical feature for modulus. This framework enables efficient exploration of microstructure-property correlations, offering new insights to guide the design of advanced porous materials.
Core Ideas A significant fraction of CO 2 fluxes from a semiarid floodplain originates from below the root zone. Measured and calculated field CO 2 fluxes are consistent. Laboratory‐measured respiration rates are consistent with field results. Although CO 2 fluxes from soils are often assumed to originate within shallow soil horizons (<1‐m depth), relatively little is known about respiration rates at greater depths. We compared measured and calculated CO 2 fluxes at the Rifle floodplain along the Colorado River and measured CO 2 production rates of floodplain sediments to determine the relative importance of deeper vadose zone respiration. Calculations based on measured CO 2 gradients and estimated effective diffusion coefficients yielded fluxes that are generally consistent with measurements obtained at the soil surface (326 g C m −2 yr −1 ). Carbon dioxide production from the 2.0‐ to 3.5‐m depth interval was calculated to contribute 17% of the total floodplain respiration, with rates that were larger than some parts of the shallower vadose zone and underlying aquifer. Microbial respiration rates determined from laboratory incubation tests of the sediments support this conclusion. The deeper unsaturated zone typically maintains intermediate water and air saturations, lacks extreme temperatures and salinities, and is annually resupplied with organic carbon from snowmelt‐driven recharge and by water table decline. This combination of favorable conditions supports deeper unsaturated zone microbial respiration throughout the year.
Flames in practical combustors and engines are inevitably subject to the effects of upstream chemical reaction progress and stretch, induced by elevated thermodynamic conditions and flow non-uniformities, respectively. Recent shock tube experiments and simulation studies on flame propagation have shown that flame speed under engine-relevant conditions can be enhanced with non-negligible upstream chemical reaction progress, especially when low-temperature heat release is involved in the unburnt mixture. On the other hand, depending on the mixture equivalence ratio and diluents, nonequidiffusion (including the non-unity Lewis number effect and the preferential diffusion effect) can couple with the flame stretch to fundamentally affect the flame propagation, which can manifest as either facilitation or suppression. Depending on the transport property of a reacting mixture, there hence can be either inhibition or promotion from unburnt reaction progress and stretch effects on flame propagation. In the current work, through one-dimensional numerical simulations of transient planar and spherical flames of n-heptane/air under elevated thermodynamic conditions, the combined effects of upstream chemical reaction progress and stretch on flame propagation are investigated. Results show that for both lean and rich n-heptane/air mixtures, flame speed can be substantially promoted with reaction progress, while the rich mixtures can exhibit opposite stretch dependence after first-stage ignition. Different definitions of effective Lewis number are adopted to explain the change in Markstein length for spherical flame in lean and rich mixtures reformed by the low temperature chemistry. Further, this work fills an important gap in laminar premixed flame research relevant to practical combustion systems and can provide useful insight into local turbulent flame behaviors and phi-sensitivity in engine combustion.
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Solute diffusion in compacted clays depends on ionic strength through its control on the thickness of the electrical double layer (EDL) on the charged clay surfaces. In the DR-A field experiment (Mont Terri, Switzerland), synthetic porewater was circulated through a borehole for 189 days, leading to the out-diffusion of a variety of tracers into the Opalinus Clay. The borehole solution was then replaced with a higher-salinity solution for an additional 540 days, leading to the diffusion of Cs + , Ca 2+ , Mg 2+ , and Sr 2+ back into the borehole and to an increase in the out-diffusion of anions (I - , Br - ) and 3 H. The experimental results were interpreted using the CrunchClay code, which includes a mean electrostatic potential model for the EDL. The EDL corresponds to a second continuum in addition to bulk electrically neutral porewater. Species-specific diffusion (Nernst-Planck equation) occurs through both domains. A 1D radial model considered a single pore diffusion coefficient (Dp = 10-9 m2/s) for cations and 3H in the bulk porosity, and a smaller D p (3 × 10 -10 m 2 /s) for anions. Dp values in the EDL were smaller (10 -11 m 2 /s), except for Cs + and K + (5 × 10 -10 and 2 × 10 -10 m 2 /s, respectively). The model reproduced well the experimental results and showed the capability to consider temporal changes in geochemical conditions affecting the transport and retention of potentially important radionuclide contaminants (e.g., 137 Cs + , 90 Sr 2+ , 129 I - ) in underground geological nuclear waste repositories. Finally, coupled multicomponent diffusion together with the electrostatic properties of the charged surfaces are essential in the development of predictive models for ion transport in clays.
In this project, we have analyzed data collected by the U.S. Department of Energy (DOE), National Energy Technology Laboratory (NETL) in a high pressure water tunnel (HPWT) and data from two research cruises to natural seeps in the Gulf of Mexico to adapt and validate a numerical model to predict the dynamics of natural seeps in the deep oceans. The HPWT data include video observations of the shrinkage rate of individual methane and natural gas bubbles under simulated deep-water conditions. Field data were collected during two cruises by the Gulf Integrated Spill Research (GISR) Consortium led by Texas A&M University and funded by the Gulf of Mexico Research Initiative (GoMRI). These data included in situ observations from a remotely operated vehicle (ROV) of gas bubbles at two natural seep sites in the Gulf and acoustic observations of the natural seep bubble flares in the ocean water column. The acoustic data were from multibeam echosounders, one mounted in a forward-looking orientation on the ROV and another mounted down-looking in the haul of the ship. All of these laboratory and field data were focused on the dynamics of natural gas bubbles at temperatures and pressures favorable for clathrate hydrate formation between the gas and water. Our analyses of this data focused on understanding the mechanisms responsible for gas bubble dissolution within the hydrate stability zone (HSZ) of the oceans. Ice-like hydrate shells may form on the bubble-water interface under these conditions, and it was unknown how this might affect the mass transfer of gas into the ocean. We were able to extract bubble shrinkage rates from the HPWT datasets. Using this data we determined that mass transfer coefficients with and without a hydrate shell match empirical values for bubbles in contaminated systems (so-called dirty bubbles contaminated by naturally occurring surfactants). We also showed that free gas, and not gas hydrate, is the dominant dissolving phase when the hydrate sub-cooling is below 11 degree Celsius (temperature difference between hydrate the hydrate formation temperature and ambient temperator) or the pressure is reducing as bubbles rise through the ocean water column. Using this mass transfer model, our numerical model of bubble dissolution matched the over 200 HPWT experiments with an average error of 10% for predicting the bubble size at the end of an experiment. From field data in the literature, we also observed that gas bubbles dissolve faster when they are initially released, following mass transfer coefficients for so-called clean-bubbles (those not yet contaminated by surfactants). Shortly after release within the HSZ, a hydrate shell forms on the bubble-water interface, and the mass transfer reduces to rates matching those of dirty bubbles. We correlated this transition time from clean to dirty bubble behavior with the initial bubble surface area and the hydrate sub-cooling. With this model for hydrate formation time and using the mass transfer coefficients deduced from the HPWT data, we validated our numerical model for predicting the rise heights of natural seep flares in the oceans. Flare heights are commonly observed in haul-mounted acoustic multibeam data. The numerical model predicts bubbles to rise high in the ocean water column owing to the slower mass transfer rates for dirty bubbles that accompany the majority of their rise time. We found that the numerical model predictions matched the observed flare heights within 5% to 10% accuracy when we compared the rise heights of the largest bubbles released from the seafloor with the bubbles acoustically visible in the multibeam data. Bubbles become acoustically transparent as they shrink to sizes of order 1 mm in diameter for the multibeam frequencies used in the field. The forward-looking multibeam on the ROV also provided data on the lateral spreading of bubbles in natural seep flares. Our analysis of this data showed that spreading follows a diffusion process, with the effective diffusivity correlating with the wobbling length scale of these ellipsoidal bubbles. When we apply this diffusivity in a random displacement model of bubble spreading, our numerical simulations match closely the lateral spread observed by the M3 in the ocean water column. Finally, we compared the seep model predictions for the acoustic properties of these natural seep plumes with that observed by the acoustic instruments in the field. The M3 and EM 302 observations were converted to relative values of target strength using a calibration we obtained in the laboratory for the M3 and using an algorithm from the manufacturer for the EM 302. Comparing the numerical seep model to these data, we obtain good agreement over the whole height of rise of these bubble flares. This further validates the numerical model. Overall, our validated seep model captures the key dynamics of gas bubbles released from natural seeps in the oceans and helps to predict the fate of methane in the water column.
Reducing mass-transport losses in polymer-electrolyte fuel cells (PEFCs) is essential to increase their power density and reduce overall stack cost. At the same time, cost also motivates the reduction in expensive precious-metal catalysts, which results in higher local transport losses in the catalyst layers. Here, we use a hydrogen-pump limiting-current setup to explore the gas-phase transport losses through PEFC catalyst layers and various gas-diffusion and microporous layers. It is shown that the effective diffusivity in the gas-diffusion layers is a strong function of liquid saturation. Additionally, it is shown how the catalyst layer unexpectedly contributes significantly to the overall measured transport resistance. This is especially true for low catalyst loadings. It is also shown how the various losses can be separated into different mechanisms including diffusional processes and mass-dependent and independent ones, where the data suggests that a large part of the transport resistance in catalyst layers cannot be attributed to a gas-phase diffusional process. The technique is promising for deconvoluting transport losses in PEFCs.
The effects of neutron irradiation temperature and dose on thermal diffusivity are compared between non-irradiated and in-pile irradiated MgO samples. MgO pellets were irradiated in-pile of the Advanced Test Reactor at Idaho National Laboratory. Samples were irradiated at 623 and 973 K to fast neutron fluences of 1 x 1025 (1.5 dpa) and 2 x 1025 n/m2 (3 dpa). Post irradiation examination included X-ray diffraction, scanning electron microscopy, laser flash thermal diffusivity, and transmission electron microscopy. The radiation induced thermophysical and structural evolution of MgO is reported
Gross primary productivity (GPP) has been reported to increase with the fraction of diffuse solar radiation, for a given total irradiance. The correlation between GPP and diffuse radiation suggests effects of diffuse radiation on canopy light-use efficiency, but potentially confounding effects of vegetation phenology have not been fully explored. We applied several approaches to control for phenology, using 8 years of eddy-covariance measurements of winter wheat in the U.S. Southern Great Plains. The apparent enhancement of daily GPP due to diffuse radiation was reduced from 260% to 75%, after subsampling over the peak growing season or by subtracting a 15 day moving average of GPP, suggesting a role of phenology. The diffuse radiation effect was further reduced to 22% after normalizing GPP by a spectral reflectance index to account for phenological variations in leaf area index LAI and canopy photosynthetic capacity. Canopy photosynthetic capacity covaries with diffuse fraction at a given solar irradiance at this site because both factors are dependent on day of year or solar zenith angle. Using a two-leaf Sun-shaded canopy radiative transfer model, we confirmed that the effects of phenological variations in photosynthetic capacity can appear qualitatively similar to the effects of diffuse radiation on GPP and therefore can be difficult to distinguish using observations. The importance of controlling for phenology when inferring diffuse radiation effects on GPP raises new challenges and opportunities for using radiation measurements to improve carbon cycle models.