Search NASA⌕ Search

SEARCH · Search NASA

Results for “diffusion models”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Nanoscopic dynamics of bicontinous microemulsions: effect of membrane associated protein

Bicontinous microemulsions (BμE) generally consist of nanodomains formed by surfactant in a mixture of water and oil at nearly equal proportions and are potential candidates for the solubilization and purification of membrane proteins. In this paper, we present the first time report of nanoscopic dynamics of surfactant monolayers within BμEs formed by the anionic surfactant sodium dodecyl sulfate (SDS) measured on the nanosecond to picosecond time scale using quasielastic neutron scattering (QENS). BμEs investigated herein consisted of middle phases isolated from Winsor-III microemulsion systems that were formed by mixing aqueous and oil solutions under optimal conditions. QENS data indicates that surfactants undergo two distinct motions, namely (i) lateral motion along the surface of the oil nanodomains and (ii) localized internal motion. Lateral motion can be described using a continuous diffusion model, from which the lateral diffusion coefficient is obtained. Internal motion of surfactant is described using a model which assumes that a fraction of the surfactants’ hydrogens undergoes localized translational diffusion that could be considered confined within a spherical volume. The effect of cytochrome c, an archetypal membrane-associated protein known to strongly partition near the surfactant head groups in BμEs (a trend supported by small-angle X-ray scattering [SAXS] analysis), on the dynamics of BμE has also been investigated. QENS results demonstrated that cytochrome c significantly hindered both the lateral and the internal motions of surfactant. The lateral motion was more strongly affected: a reduction of the lateral diffusion coefficient by 33% was measured. This change is mainly attributable to the strong association of cytochrome c with oppositely charged SDS. In contrast, analysis of SAXS data suggested that thermal fluctuations (for a longer length and slower time scale compared to QENS) were increased upon incorporation of cytochrome c. Finally, this study demonstrates the utility of QENS for evaluating dynamics of BμEs in nanoscopic region, and that proteins directly affect the microscopic dynamics, which is of relevance for evaluating release kinetics of encapsulated drugs from BμE delivery systems and the use of BμEs as biomembrane mimetic systems for investigating membrane protein–biomembrane interactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Modeling fission product diffusion in TRISO fuel particles with BISON

Diffusion of fission products in intact TRISO particles depends on particle geometry, fission product source rates, time, temperature, and temperature-dependent diffusion coefficients. Simulating this diffusion process requires models for source rates and diffusion coefficients, plus computation of the temperature field if not prescribed. In addition, simulation quality depends on discretization of the geometry, appropriate time stepping, and the accuracy of the solution method. In this paper, we explore the simulation of fission product diffusion in TRISO fuel particles using the finite element method via the fuel performance code Bison. Recent material model development has occurred in Bison for each material present in tri-structural isotropic (TRISO) fuel particles: the buffer, inner pyrolytic carbon, silicon carbide, and outer pyrolytic carbon layers, as well as the fuel kernel. Also, new mesh generation and fission product release fraction capabilities have been added. Diffusion capabilities are shown to converge to the correct solution via formal verification tests. A large number of code benchmarking problems are also given, with good results, showing that Bison’s computed release fractions closely match those of other software tools. Finally, a significant validation effort is detailed in which fission product release, measured as part of the AGR-1 capsule experiments, is compared to Bison outputs. Bison outputs compare very well to the experimental data and to PARFUME results.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2018

Comparison of experimental methods for estimating matrix diffusion coefficients for contaminant transport modeling

Here, diffusion cell and diffusion wafer experiments were conducted to compare methods for estimating effective matrix diffusion coefficients in rock core samples from Pahute Mesa at the Nevada Nuclear Security Site (NNSS). A diffusion wafer method, in which a solute diffuses out of a rock matrix that is pre-saturated with water containing the solute, is presented as a simpler alternative to the traditional through-diffusion (diffusion cell) method. Both methods yielded estimates of effective matrix diffusion coefficients that were within the range of values previously reported for NNSS volcanic rocks. The difference between the estimates of the two methods ranged from 14 to 30%, and there was no systematic high or low bias of one method relative to the other. From a transport modeling perspective, these differences are relatively minor when one considers that other variables (e.g., fracture apertures, fracture spacings) influence matrix diffusion to a greater degree and tend to have greater uncertainty than effective matrix diffusion coefficients. For the same relative random errors in concentration measurements, the diffusion cell method yields effective matrix diffusion coefficient estimates that have less uncertainty than the wafer method. However, the wafer method is easier and less costly to implement and yields estimates more quickly, thus allowing a greater number of samples to be analyzed for the same cost and time. Given the relatively good agreement between the methods, and the lack of any apparent bias between the methods, the diffusion wafer method appears to offer advantages over the diffusion cell method if better statistical representation of a given set of rock samples is desired.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

Predictive modeling of CO2 sequestration in deep saline sandstone reservoirs: Impacts of geochemical kinetics

One idea for mitigating the increase in fossil-fuel generated CO{sub 2} in the atmosphere is to inject CO{sub 2} into subsurface saline sandstone reservoirs. To decide whether to try such sequestration at a globally significant scale will require the ability to predict the fate of injected CO{sub 2}. Thus, models are needed to predict the rates and extents of subsurface rock-water-gas interactions. Several reactive transport models for CO{sub 2} sequestration created in the last decade predicted sequestration in sandstone reservoirs of ~17 to ~90 kg CO{sub 2} m{sup -3|. To build confidence in such models, a baseline problem including rock + water chemistry is proposed as the basis for future modeling so that both the models and the parameterizations can be compared systematically. In addition, a reactive diffusion model is used to investigate the fate of injected supercritical CO{sub 2} fluid in the proposed baseline reservoir + brine system. In the baseline problem, injected CO{sub 2} is redistributed from the supercritical (SC) free phase by dissolution into pore brine and by formation of carbonates in the sandstone. The numerical transport model incorporates a full kinetic description of mineral-water reactions under the assumption that transport is by diffusion only. Sensitivity tests were also run to understand which mineral kinetics reactions are important for CO{sub 2} trapping. The diffusion transport model shows that for the first ~20 years after CO{sub 2} diffusion initiates, CO{sub 2} is mostly consumed by dissolution into the brine to form CO{sub 2,aq} (solubility trapping). From 20-200 years, both solubility and mineral trapping are important as calcite precipitation is driven by dissolution of oligoclase. From 200 to 1000 years, mineral trapping is the most important sequestration mechanism, as smectite dissolves and calcite precipitates. Beyond 2000 years, most trapping is due to formation of aqueous HCO{sub 3}{sup -}. Ninety-seven percent of the maximum CO{sub 2} sequestration, 34.5 kg CO{sub 2} per m{sup 3} of sandstone, is attained by 4000 years even though the system does not achieve chemical equilibrium until ~25,000 years. This maximum represents about 20% CO{sub 2} dissolved as CO{sub 2},aq, 50% dissolved as HCO{sub 3}{sup -}{sub ,aq}, and 30% precipitated as calcite. The extent of sequestration as HCO{sub 3}{sup -} at equilibrium can be calculated from equilibrium thermodynamics and is roughly equivalent to the amount of Na+ in the initial sandstone in a soluble mineral (here, oligoclase). Similarly, the extent of trapping in calcite is determined by the amount of Ca2+ in the initial oligoclase and smectite. Sensitivity analyses show that the rate of CO{sub 2} sequestration is sensitive to the mineral-water reaction kinetic constants between approximately 10 and 4000 years. The sensitivity of CO{sub 2} sequestration to the rate constants decreases in magnitude respectively from oligoclase to albite to smectite.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

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↗
DOE OSTI2013

Using High-Fidelity Radiation Transport Methods to Supplement the Diffusion Approximation at Material Interfaces

Today, many radiation-hydrodynamics simulations use methods that combine hydrodynamics and radiation diffusion algorithms. The diffusion model has been used because it provides faster calculations for the radiation scalar flux than the full radiation transport model. However, it is well-known that diffusion cannot resolve “transport effects” at material interfaces. This could cause erroneous predictions when coupling the radiation results with a material hydrodynamics calculation. In this work, the “transport effects” are thoroughly characterized using IMC and SN transport methods. Based on the information obtained from this study, new models based on diffusion that can capture these effects are developed. These models are subsequently compared with the full radiation transport model. It is hoped that the new models can be used to provide improved predictions in rad-hydro simulations, such as in ICF capsule implosions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Sequential Infiltration Synthesis of Multinary Metal Oxides: The Role of Precursor Diffusion and Reactivity

Understanding volatile metal–organic precursor transport in polymer matrices during sequential infiltration synthesis (SIS) is critical to the design of hybrid materials of tailored composition and uniform structure. Here, we investigate the diffusion and reaction behavior of diethylzinc (DEZ) in poly(methyl methacrylate) (PMMA) matrices with variable indium and zinc incorporation. Unlike conventional SIS where precursors adduct or react directly with the polymer backbone, DEZ shows minimal interaction with PMMA. However, DEZ may interact strongly with In–OH or Zn–OH moieties that are previously incorporated into a PMMA thick film. Using spectroscopic ellipsometry, X-ray photoelectron spectroscopy depth profiling, and EDX line scans, we quantify Zn incorporation as a function of exposure time, polymer thickness, and previous infiltration steps. The Zn distribution evolves from surface-localized to deep within the ∼1 μm thick film with increasing DEZ exposures up to 30 min. A reaction-diffusion model incorporating a hindering factor to capture diffusivity decay due to product accumulation reproduces the Zn depth profile and yields physically meaningful parameters to guide future growth. Furthermore, this study provides a framework for interpreting metal–organic precursor infiltration behavior and highlights the utility of model-guided SIS process design.

diethylzinc↗
NASA NTRS2002

Deep Throttle Turbopump Technology Design Concepts

The objective of this project is to increase the throttling range of turbopumps from 30 to 120% of the design value, while maintaining high performance levels. Details are given on wide flow range issues, H-Q characteristics, stall characteristics, energy levels, pressure fluctuations at impeller exit, WFR impeller characteristics, commercial diffuser pumps, slotted or tandem vanes, leading edge characteristics, leading edge models, throat models, diffusion passage models, computational fluid dynamics (CFD) methodologies, and CFD flow cases.

Guinzburg, Adiel↗
DOE OSTI2022

Salt and ion transport in a series of crosslinked AMPS/PEGDA hydrogel membranes

Salt permeability and ionic conductivity are critical properties for membranes in water purification and energy applications. Both properties depend on individual ion sorption and diffusion coefficients, which are significantly influenced by polymer chemical and physical parameters such as fixed charge concentration and membrane water content. However, systematic studies connecting polymer structure to ion transport properties are still lacking. In this study, a series of uncharged and charged membranes were synthesized using poly(ethylene glycol) diacrylate (PEGDA) as a cross-linker and 2-acrylamido-2-methyl-1-propanesulfonic acid (AMPS) as a charged monomer. Membrane fixed charge concentration and water uptake were systematically varied by adjusting AMPS content in the pre-polymerization mixture. Salt sorption and permeability coefficients and ionic conductivity of these membranes were measured as a function of NaCl solution concentration (0.01–1 M). Combining the solution-diffusion model and Nernst-Planck equation, individual ion diffusion coefficients were calculated. Experimental Na + diffusion coefficients for all materials were well described by the Mackie and Meares tortuosity model, highlighting the strong influence of water content on ion diffusivity in both uncharged and charged polymers. Model predictions for Cl – diffusion coefficients agree reasonably well with experimental values, with some deviations occurring in more highly charged membranes. Finally, this discrepancy might result from interactions not captured by the Mackie and Meares model (e.g., fixed charge-ion interactions).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Flow matching meets biology and life science: a survey

Over the past decade, advances in generative modeling, such as generative adversarial networks, masked autoencoders, and diffusion models, have significantly transformed biological research and discovery, enabling breakthroughs in molecule design, protein generation, catalysis discovery, drug discovery, and beyond. At the same time, biological applications have served as valuable testbeds for evaluating the capabilities of generative models. Recently, flow matching has emerged as a powerful and efficient alternative to diffusion-based generative modeling, with growing interest in its application to problems in biology and life sciences. This paper presents the first comprehensive survey of recent developments in flow matching and its applications in biological domains. We begin by systematically reviewing the foundations and variants of flow matching, and then categorize its applications into three major areas: biological sequence modeling, molecule generation and design, and peptide and protein generation. For each, we provide an in-depth review of recent progress. We also summarize commonly used datasets and software tools, and conclude with a discussion of potential future directions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Ge auto-doping and out-diffusion in InGaP grown on Ge substrate and their effects on the ordering of InGaP

We report on the Ge auto-doping and out-diffusion in InGaP epilayer with Cu-Pt ordering grown on 4-in. Ge substrate. Ge profiles determined from secondary ion mass spectrometry indicate that the Ge out-diffusion depth is within 100 nm. However, the edge of the wafer suffers from stronger Ge gas-phase auto-doping than the center, leading to ordering deterioration in the InGaP epilayer. In the edge, we observed a residual Cu-Pt ordering layer left beneath the surface, suggesting that the ordering deterioration takes place after the deposition rather than during the deposition and In/Ga inter-diffusion enhanced by Ge vapor-phase auto-doping is responsible for the deterioration. We thus propose a di-vacancy diffusion model, in which the amphoteric Ge increases the di-vacancy density, resulting in a Ge density dependent diffusion. In the model, the In/Ga inter-diffusion and Ge out-diffusion are realized by the random hopping of In/Ga host atoms and Ge atoms to di-vacancies, respectively. Simulation based on this model well fits the Ge out-diffusion profiles, suggesting its validity. By comparing the Ge diffusion coefficient obtained from the fitting and the characteristic time constant of ordering deterioration estimated from the residual ordering layer, we found that the hopping rates of Ge and the host atoms are in the same order of magnitude, indicating that di-vacancies are bound in the vicinity of Ge atoms.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS1995

Kinematic models of supergranular diffusion on the Sun

We develop kinematic models of diffusion generated by supergranulation at the solar surface. These models use current observations for the size, horizontal velocity, and lifetime of supergranules. Because there is no observational description of the appearance and disappearance of supergranules, we investigate models using several plausible evolution processes, including the effect of different lifetime distribution functions for the cells. The results are quite insensitive to the methods chosen to replace old supergranules, the distribution of cell lifetimes, and even the cell lifetime itself, for mean lifetimes between 15 to 30 hr. Calculated diffusion coefficients range between 500 and 700 sq km/s, in agreement with the best fit diffusion coefficients used by Sheeley and his collaborators to model the large-scale distribution of magnetic fields over the solar surface. However, our models do not explain the field distribution in plage, and they predict that virtually all the strong field in quiet Sun exists in relatively isolated clumps. We suggest possible mechanisms for the creation of plage and the bright network seen in quiet Sun.

Simon, G. W.↗