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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 253 records · Page 14

Pressure effects on reactivity and extinction of n -dodecane diffusion cool flame

Low-temperature combustion at high pressure has gained increasing interest owing to the growing demand for clean and efficient propulsion and energy systems. In particular, cool flame structure, extinction limits, and fuel reactivities at high pressure are critical in affecting the engine performance at near-limit conditions. Here, this paper investigates the effects of pressure on the cool flame extinction limit, structure, radical index, reactivity, and oxygen concentration dependence by experiments, analysis, and modeling. A large n-alkane, namely n-dodecane (n C 12 H 26 ), is selected to study its diffusion cool flame dynamics and reactivity in a high-pressure counterflow burner up to 10 atm. The experimental results show that higher pressure increases the cool flame extinction strain rates, and that the pressure-weighted extinction strain rate (aP) is proportional to the square of pressure, P 2 . A scaling analysis explains the relationship between the dependence of flame structure, heat release rate, and pressure-weighted cool flame strain rate on pressure. Furthermore, radical indexes at different pressures are measured by isolating the thermal and transport effects from the chemical contribution to diffusion cool flame extinction. The radical index clearly shows that the low-temperature reactivity increases with pressure. In addition, due to the critical role of multiple oxygen addition reactions in low-temperature chemistry, the relationship between the cool flame extinction limit and the oxygen concentration is explored. It is found that the cool flame extinction limits are proportional to the n th power of the oxygen concentration, [O 2 ] n , and increasing pressure leads to stronger extinction limit dependence (larger n) on the oxygen concentration. The present experiment and detailed kinetic analysis show clearly that increasing pressure promotes the low-temperature chemistry including the oxygen addition reactions, while the scaling analysis explains well the experimental results.

33 ADVANCED PROPULSION SYSTEMS↗

Evidence for the 3D Radiative Effects of Boundary-Layer Clouds From Observations of Direct and Diffuse Surface Solar Fluxes

Numerical experiments have revealed the importance of horizontal transport of light in the presence of clouds (“3D effects”), with consequences for climate, weather, and solar resource availability predictions. Yet, analysis of 3D effects from observations remain sparse because of the difficulty to isolate the effect of horizontal transport in radiation measurements. In this study, we provide observational evidence for 3D effects based on the direct-diffuse partition of surface solar fluxes. It is compared to outputs from the ecRad radiative transfer scheme run on retrieved cloud profiles. Furthermore, the direct-beam calculation takes careful account of the field-of-view of the pyrheliometer to ensure consistency between observed and modeled direct fluxes. Only the solver that accounts for 3D effects is able to reproduce the observed mean direct-diffuse partition as a function of solar zenith angle and cloud cover, in particular at large solar zenith angles where cloud sides intercept most of the direct beam.

54 ENVIRONMENTAL SCIENCES↗

Larger than uncorrelated vacancy diffusion contributions in chemically disordered crystalline materials

Arising from a variational approach to compute diffusion coefficients, we introduce “superkinetic kinosons”, which are contributions to the diffusion flux of mobile defects and atomic species by single jump mechanisms that can exceed their uncorrelated values. In vacancy-mediated diffusion in crystalline random and high entropy materials, these contributions primarily arise from intermittent jumps of slow moving atoms that remove the vacancy out of correlation traps and enable a quantification of such effects on the diffusion coefficients. They can be significant contributors to diffusion, even when faster moving atoms have infinite percolation networks. Furthermore, their existence and importance provide fundamental insights about underlying aspects of vacancy diffusion such as formation of localized correlation traps and deviation of vacancy diffusion from percolation behavior.

36 MATERIALS SCIENCE↗

HTO and selenate diffusion through compacted Na-, Na–Ca-, and Ca-montmorillonite

Radionuclide transport in smectite clay barrier systems used for nuclear waste disposal is controlled by diffusion, with adsorption significantly retarding transport rates. While a relatively minor component of spent nuclear fuel, 79 Se is a major driver of the safety case for spent fuel disposal due to its long half-life (3.3×10 5 yr) and its low adsorption to clay (K D < 10 L/kg), thus a thorough understanding of Se diffusion through clay is critical for understanding the long-term safety of spent fuel disposal systems. Through-diffusion experiments with tritiated water (HTO, conservative tracer) and Se(VI) were conducted with a well-characterized, purified montmorillonite source clay (SWy-2) under a constant ionic strength (0.1 M) and three different electrolyte compositions: Na + , Ca 2+ , and a Na + -Ca 2+ mixture at pH 6.5 in order to probe the effects of electrolyte composition and interlayer cation composition on clay microstructure, Se(VI) aqueous speciation, and ultimately diffusion. Further, the results were modeled using a reactive transport modeling approach to determine values of porosity (ε), D e (effective diffusion coefficient), and K D (distribution coefficient for adsorption). HTO diffusive flux was higher in Ca-montmorillonite (D e =1.68×10 -10 m 2 s -1 ) compared to Na-montmorillonite (De=7.83×10 -11 m 2 s -1 ). This increase in flux is likely due to a greater degree of clay layer stacking in the presence of Ca 2+ compared to Na + , which leads to larger inter-particle pores. Overall, the Se(VI) flux was much lower than the HTO flux due to anion exclusion, with Se(VI) flux following the order Ca (D e = 1.03×10 -11 m 2 s -1 ) > Na–Ca (D e = 2.12×10 -12 m 2 s -1 ) > Na (D e = 1.28×10 -12 m 2 s -1 ). These differences in Se(VI) flux are due to a combination of factors, including (1) larger accessible porosity in Ca-montmorillonite due to clay layer stacking and smaller electrostatic effects compared to Na-montmorillonite, (2) larger accessible porosity for neutral-charge CaSeO4 species which makes up 32% of aqueous Se(VI) in the pure Ca system, and (3) possibly higher Se(VI) adsorption for Ca-montmorillonite. Through a combination of experimental and modeling work, this study highlights the compounding effects that electrolyte and counterion compositions can have on radionuclide transport through clay. Diffusion models that neglect these effects are not transferable from laboratory experimental conditions to in situ repository conditions.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

A diffusion–deformation model with damage for polymer undergoing rapid decompression failure

Green hydrogen is emerging as one of the most promising alternatives to replace fossil fuels. While hydrogen gas has a good energy density by weight, its poor energy density by volume requires it to be stored under high pressure for commercial use. The hydrogen infrastructure developed to handle this high pressure hydrogen contains multiple components made of polymers as sealing agents. Although polymers do not react chemically with hydrogen gas, they undergo a mechanical failure when high pressure hydrogen gas is suddenly depressurized. This phenomenon known as 'rapid decompression failure' occurs due to the diffusion of hydrogen through polymer and getting trapped inside pre-existing cavities or voids. Here, in this paper, a continuum mechanics-based coupled diffusion-deformation-damage model was developed to predict the hydrogen distribution, stress distribution, and damage propagation inside the polymer while it undergoes rapid decompression failure. The polymer was modeled as a hyperelastic material because it represents the nonlinear material response observed in uniaxial tensile tests perfectly. The effects of hydrogen diffusivity, pre-existing cavity size, cavity location, applied hydrogen pressure, and depressurization rate on damage initiation were studied. It was found that the coefficient of diffusion plays an important role in damage initiation and damage was mostly concentrated in the inside areas rather than near the surface. Experiments were conducted with EPDM polymer which agreed well with the predicted trends using the given model. The effect of adding carbon black and silica filler particles and plasticizer to the pure EPDM polymer was also studied. It was found that damage during RDF decreases with the addition of fillers, but increases with the addition of the plasticizer. Finally, the damage evolution in the presence of two cavities was also studied, and was found that the interaction of stress fields around the cavities alters the damage occurring during RDF.

36 MATERIALS SCIENCE↗

Multiscale, mechanistic modeling of cesium transport in silicon carbide for TRISO fuel performance prediction

Understanding cesium (Cs) transport in TRistructural ISOtropic (TRISO) particle fuel is crucial for predicting fission product release in high-temperature reactors. However, current challenges include significant scatter in diffusivity data and unexplained temperature-dependent diffusion regimes in the silicon carbide layer. This study addresses these challenges by developing a multiscale, mechanistic Cs transport model integrating atomistic simulations and phase field modeling. Our model quantifies temperature and grain size effects on Cs diffusivity, attributing experimentally observed regimes to a transition from bulk-dominated diffusivity at high temperatures to grain boundary-dominated diffusivity at lower temperatures. The model, validated against diffusion measurements and advanced gas reactor (AGR)-1 and AGR-2 post-irradiation fission product release data, enhances the predictive capability of the BISON fuel performance code. This study advances our understanding of Cs release from TRISO particles and its dependence on temperature and silicon carbide grain size, with implications for the safety and efficiency of high-temperature nuclear reactors.

BISON↗

Path integral molecular dynamics: A high-fidelity approach to quantum dynamics of electrons

We investigate electron transport in the uniform electron gas using ring-polymer molecular dynamics (RPMD). Working in the weakly coupled, non-degenerate regime, we use RPMD to probe how the onset of quantum diffraction effects at high temperature reshapes electron–electron collisions and leads to a classical-to-quantum crossover in macroscopic transport properties. Static thermodynamics obtained with RPMD are consistent with the weak-coupling equation of state, confirming correct quantum Boltzmann sampling. Real-time transport extracted from mean square displacements exhibits the expected ballistic-to-diffusive transition and a systematic reduction of the electronic self-diffusivity as quantum effects strengthen, due to quantum diffraction modifying electron–electron collisions. Direct ring-polymer scattering simulations reveal diffractive “softening” of binary deflections, providing a micro-to-macro link between collision physics and diffusion. The present study establishes RPMD as a quantitative, trajectory-based tool for electron transport across the classical–quantum crossover and furnishes benchmarks for improving Coulomb-log interpolation models. We outline extensions to multi-component plasmas and a path to incorporate Fermi–Dirac statistics within path-integral dynamics.

Electronic transport↗

Dynamics of Glyceline and Interactions of Constituents: A Multitechnique NMR Study

In this work, the dynamics of the organic components of the deep eutectic solvent (DES) glyceline are analyzed using an array of complementary nuclear magnetic resonance (NMR) methods. Fast-Field Cycling 1 H relaxometry, Pulsed Field Gradient diffusion, Nuclear Overhauser Effect Spectroscopy (NOESY), 13 C NMR relaxation and pressure dependent NMR experiments are deployed to sample a range of frequencies and modes of motion of the glycerol and choline components of the DES. Generally, translational and rotational diffusion of glycerol are more rapid than those of choline while short range rotational motions observed from 13 C relaxation indicate slow local motion of glycerol at low choline chloride (ChCl) content. The rates of glycerol and choline local motions become more similar at higher ChCl. This result taken together with pressure dependent NMR studies show that the addition of ChCl makes it easier to disrupt glycerol packing. Finally, a relatively slow hydroxyl H-exchange process between glycerol and choline protons is deduced from the data. Consistent with this, NOESY results indicate relatively little direct H-bonding between glycerol and choline. These results suggest that the glycerol H-bonding network is disrupted as choline is added, but primarily in regions where there is intimate mixing of the two components. Thus, the local dynamics of most of the glycerol, resembles that of pure glycerol until substantial choline chloride is present.

13C NMR relaxation↗

Co-ion specific effect on sodium halides sorption and transport in a cross-linked poly(p-styrene sulfonate-co-divinylbenzene) for membrane applications

Here, sodium halide sorption and transport in a cation exchange membrane based on cross-linked poly(p-styrene sulfonate-co-divinylbenzene) (CR61) were investigated experimentally and theoretically. At fixed co-ion valence, sodium halide partitioning between aqueous electrolyte solutions and ion exchange polymers is only minimally sensitive to co-ion chemical identity. NaCl, NaF and NaI exhibit similar solubility coefficients in CR61, which agrees reasonably well with predictions of the Donnan-Manning model, especially at high external salt concentrations. Ion activity coefficients in the membrane were evaluated and ion sorption thermodynamics were investigated. Ion diffusion coefficients in CR61 were predicted using a recently developed framework based on the Manning diffusion model, which accounts for electrostatic effects on ion diffusion, and the Mackie-Meares model, which accounts for tortuosity/area effects on ion diffusion in swollen polymers. Model predictions agree reasonably well with the experimental data, especially at high external salt concentrations. The observed decrease in salt diffusion coefficients in CR61 relative to values in aqueous solutions is due primarily to tortuosity/area effects. Salt diffusion coefficients correlate with co-ion hydrated radius and membrane water content. Finally, salt permeability coefficients predicted using the solution-diffusion model exhibit good agreement with experimental data, especially at external salt concentration greater than 0.1 mol/L.

42 ENGINEERING↗

High Accuracy Transition Metal Effective Cores for the Many-Body Diffusion Monte Carlo Method

Practical applications of the real-space diffusion Monte Carlo (DMC) method require the removal of core electrons, where currently localization approximations of semilocal potentials are generally used in the projector. Accurate calculations of complex solids and large molecules demand minimizing the impact of approximated atomic cores. Prior works have shown that the errors from such approximations can be sizable in both finite and periodic systems. In this work, we show that a class of differential pseudopotentials, known as pseudo-Hamiltonians, can be constructed for the 3d transition metal atoms, entirely removing the need for any localization scheme in the DMC projector. As a proof of principle, we demonstrate the approach for the case of Co. In order to minimize errors in the pseudo-Hamiltonian at the many-body level, we generalize the recently proposed correlation-consistent pseudopotential generation scheme to successively close semilocal representations of the differential potentials. Our generation scheme successfully produces potentials tailored specifically for real space projector quantum Monte Carlo methods with low error at the many-body level, i.e., with many-body scattering properties very close to relativistic all-electron results. In particular, we show that the agreement with respect to atomic and molecular quantities reach chemical accuracy in many cases-on par with the most accurate semilocal pseudopotentials available. Further, our pseudo-Hamiltonian generation scheme utilizes standard quantum chemistry codes designed only to work with semilocal pseudopotentials, enabling straightforward generation of pseudo-Hamiltonians for additional elements in future works.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Effect of Confinement on the Density and Diffusivity of Organic Molecules in Single-Digit Nanopores Relative to Bulk Fluid Behavior

Prediction of fluid properties in microporous and mesoporous confinement is non-trivial due to distinct influences from pore surface functionality and shape and fluid molecular characteristics. The vast majority of literature focuses nearly exclusively on a small number of components that are generally low molecular weight gases and vapors. Missing are studies that utilize a relatively large number of compounds that are liquid at ambient conditions to probe the impact of molecular shape and size on confined fluid properties. Such materials are of great interest in the extraction of oil and gas from shale reservoirs or for the design of selective adsorbents for chemical separation. In this work, we reveal non-intuitive relationships that emerge when comparing bulk fluid properties to those when confined in amorphous silica single-digit nanopores (approx. 5 nm SBA-15), specifically the confined density and self-diffusivity. A counterintuitive result was obtained where larger molecules had relatively faster self-diffusivities; however, this behavior was revealed to be caused by these larger compounds exhibiting a relatively low density when confined. As the prediction of confined fluid properties impacts a diversity of disciplines, the results highlight the need for additional investigations where consistent and large-scale experimental procedures are employed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Electric Field Effects on Water and Ion Structure and Diffusion at the Orthoclase (001)–Water Interface

Understanding the electrochemical properties of mineral–water interfaces tends to rely upon electrical double layer (EDL) models, but these models are based on the assumption that electrostatic equilibrium is constantly maintained. In reality, interfacial reactions, ion diffusion, and their electrochemical signatures are based in nonequilibrium conditions of locally or globally imbalanced electrical fields where current EDL models have limited purview. In this work, we performed molecular dynamics (MD) simulations of the orthoclase (001) surface in contact with a 1 M NaCl aqueous solution under various electric fields, to explore the interplay between EDL structure and dynamics when perturbed by electric fields of different direction and strength, by confinement, and by different distributions of structural surface charge. The simulations showed that confinement between two opposing (001) surfaces led to the development of an induced field when the applied field was perpendicular to the surfaces and, as a result, to ionic diffusion coefficients that were independent of electric field strength. In contrast, when the applied field was parallel to the surfaces, confinement resulted in ionic diffusion coefficients that were more strongly dependent on the magnitude of the electric field than in bulk water. Differences in the density and distribution of aluminol groups on the two surfaces had a significant impact on how the interfacial structure and dynamics varied in the presence of an electric field. Notably, these differences resulted in an electro-osmotic flow with opposite directions at the two surfaces under parallel applied electric field. Overall, the MD simulations highlighted the importance of considering atomic-level structure and heterogeneities when developing models of the electrochemical properties of mineral–water interfaces.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The Effect of Acetylation on Iron Uptake and Diffusion in Water Saturated Wood Cell Walls and Implications for Decay

Acetylation is widely used as a wood modification process that protects wood from fungal decay. The mechanisms by which acetylation protects wood are not fully understood. With these experiments, we expand upon the literature and test whether previously observed differences in iron uptake by wood were a result of decreased iron binding capacity or slower diffusion. We measured the concentration of iron in 2 mm thick wood sections at 0, 10, and 20% acetylation as a function of time after exposure to iron solutions. The iron was introduced either strongly chelated with oxalate or weakly chelated with acetate. The concentrations of iron and oxalate in solution were chosen to be similar to those found during brown rot decay, while the concentration of iron and acetate matched previous work. The iron content of oxalate-exposed wood increased only slightly and was complete within an hour, suggesting little absorption and fast diffusion, or only slight surface adsorption. The increase in iron concentration from acetate solutions with time was consistent with Fickian diffusion, with a diffusion coefficient on the order of 10 -16 m 2 s -1 . The rather slow diffusion rate was likely due to significant binding of iron within the wood cell wall. The diffusion coefficient did not depend on the acetylation level; however, the capacity for iron absorption from acetate solution was greatly reduced in the acetylated wood, likely due to the loss of OH groups. We explored several hypotheses that might explain why the diffusion rate appears to be independent of the acetylation level and found none of them convincing. Implications for brown rot decay mechanisms and future research are discussed.

54 ENVIRONMENTAL SCIENCES↗

Discrete generative diffusion models without stochastic differential equations: A tensor network approach

Diffusion models (DMs) are a class of generative machine learning methods that sample a target distribution by transforming samples of a trivial (often Gaussian) distribution using a learned stochastic differential equation. In standard DMs, this is done by learning a “score function” that reverses the effect of adding diffusive noise to the distribution of interest. Here we consider the generalisation of DMs to lattice systems with discrete degrees of freedom, and where noise is added via Markov chain jump dynamics. We show how to use tensor networks (TNs) to efficiently define and sample such “discrete diffusion models” (DDMs) without explicitly having to solve a stochastic differential equation. We show the following: (i) by parametrising the data and evolution operators as TNs, the denoising dynamics can be represented exactly; (ii) the auto-regressive nature of TNs allows to generate samples efficiently and without bias; (iii) for sampling Boltzmann-like distributions, TNs allow to construct an efficient learning scheme that integrates well with Monte Carlo. We illustrate this approach to study the equilibrium of two models with non-trivial thermodynamics, the d = 1 constrained Fredkin chain and the d = 2 Ising model. Published by the American Physical Society 2025

Causer, Luke (ORCID:0000000194243473)↗