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Results for “Effective diffusivity”

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 1,063 records · Page 59
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Hydrodynamic and frictional modulation of deformations in switchable colloidal crystallites

Displacive transformations in colloidal crystals may offer a pathway for increasing the diversity of accessible configurations without the need to engineer particle shape or interaction complexity. To date, binary crystals composed of spherically symmetric particles at specific size ratios have been formed that exhibit floppiness and facile routes for transformation into more rigid structures that are otherwise not accessible by direct nucleation and growth. There is evidence that such transformations, at least at the micrometer scale, are kinetically influenced by concomitant solvent motion that effectively induces hydrodynamic correlations between particles. Here, we study quantitatively the impact of such interactions on the transformation of binary bcc-CsCl analog crystals into close-packed configurations. We first employ principal-component analysis to stratify the explorations of a bcc-CsCl crystallite into orthogonal directions according to displacement. We then compute diffusion coefficients along the different directions using several dynamical models and find that hydrodynamic correlations, depending on their range, can either enhance or dampen collective particle motions. These two distinct effects work synergistically to bias crystallite deformations toward a subset of the available outcomes.

42 ENGINEERING↗
DOE OSTI2024

Cost‐Effective Layered Oxide – Olivine Blend Cathodes for High‐Rate Pulse Power Lithium‐Ion Batteries

Abstract Sustainability and supply‐chain concerns require lithium‐ion batteries (LIBs) free from critical minerals, such as nickel and cobalt. While recent advances provide encouraging signs that cobalt can be removed, the question remains how much Ni can be removed from Co‐free layered oxide cathodes before sacrificing critical performance metrics. This study highlights the effect of reducing Ni by benchmarking several Co‐free cathodes with decreasing Ni content. Keeping the energy density the same by increasing the charge voltage, cathodes below 80% Ni content exhibit worsened capacity fade due to increasing oxygen release and electrolyte decomposition. Charge transfer and diffusion kinetics are also hindered with increasing Mn content and exacerbated by resistive surface phases formed at high voltages, rendering lower‐Ni, Co‐free cathodes less competitive than high‐Ni cathodes for high energy and power applications. It is demonstrated blending layered oxide with olivine as an effective alternative to deliver energy density and cycling stability comparable to lower‐Ni cathodes with moderate charging voltages. Blending with 30 wt% olivine LiMn 0.5 Fe 0.5 PO 4 (LMFP) virtually eliminates the diffusion limitation of layered oxides at low state‐of‐charge, with enhanced pulse power characteristics rivaling the high‐Ni counterparts. Cathode blending can further reduce the overall Ni content and cost without the performance limitations of lower‐Ni, Co‐free cathodes.

Lee, Steven↗
DOE OSTI2020

Ion Conductivity and Correlations in Model Salt-Doped Polymers: Effects of Interaction Strength and Concentration

Correlated anion and cation motion can greatly reduce the overall ion conductivity in electrolytes versus the ideal conductivity calculated based on the diffusion constants alone. Using coarse-grained molecular dynamics simulations, we calculate conductivity and the degree of uncorrelated ion motion in salt-doped homopolymers and block copolymers as a function of concentration and interaction strengths. Calculating conductivity from ion mobility under an applied electric field increases accuracy versus the typical use of fluctuation dissipation relationships in equilibrium simulations. In typical electrolytes, correlation in cation-anion motion is often expected to be reduced at low ion concentrations. Yet, for these polymer electrolytes with strong ion-polymer and ion-ion interactions, we find cation-anion motion is more correlated at lower concentrations when other variables are held constant. We show this phenomenon is related to the slower ion cluster relaxation rate at low concentrations rather than the static spatial state of ion aggregation or the fraction of free ions.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Activated penetrant dynamics in glass forming liquids: size effects, decoupling, slaving, collective elasticity and correlation with matrix compressibility

In this work, we employ the microscopic self-consistent cooperative hopping theory of penetrant activated dynamics in glass forming viscous liquids and colloidal suspensions to address new questions over a wide range of high matrix packing fractions and penetrant-to-matrix particle size ratios. The focus is on the mean activated relaxation time of smaller tracers in a hard sphere fluid of larger particle matrices. This quantity also determines the penetrant diffusion constant and connects directly with the structural relaxation time probed in an incoherent dynamic structure factor measurement. The timescale of the non-activated fast dissipative process is also studied and is predicted to follow power laws with the contact value of the penetrant–matrix pair correlation function and the penetrant–matrix size ratio. For long time penetrant relaxation, in the relatively lower packing fraction metastable regime the local cage barriers are dominant and matrix collective elasticity effects unimportant. As packing fraction and/or penetrant size grows, much higher barriers emerge and the collective elasticity associated with the correlated matrix dynamic displacement that facilitates penetrant hopping becomes important. This results in a non-monotonic variation with packing fraction of the degree of decoupling between the matrix and penetrant alpha relaxation times. The conditions required for penetrant hopping to become slaved to the matrix alpha process are determined, which depend mainly on the penetrant to matrix particle size ratio. By analyzing the absolute and relative importance of the cage and elastic barriers we establish a mechanistic understanding of the origin of the predicted exponential growth of the penetrant hopping time with size ratio predicted at very high packing fractions. A dynamics-thermodynamics power law connection between the penetrant activation barrier and the matrix dimensionless compressibility is established as a prediction of theory, with different scaling exponents depending on whether matrix collective elasticity effects are important. Quantitative comparisons with simulations of the penetrant relaxation time, diffusion constant, and transient localization length of tracers in dense colloidal suspensions and cold viscous liquids reveal good agreements. Multiple new predictions are made that are testable via future experiments and simulations. Extension of the theoretical approach to more complex systems of high experimental interest (nonspherical molecules, semiflexible polymers, crosslinked networks) interacting via variable hard or soft repulsions and/or short range attractions is possible, including under external deformation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Selective One-Dimensional 13 C– 13 C Spin-Diffusion Solid-State Nuclear Magnetic Resonance Methods to Probe Spatial Arrangements in Biopolymers Including Plant Cell Walls, Peptides, and Spider Silk

Two-dimensional (2D) and 3D through-space 13 C– 13 C homonuclear spin-diffusion techniques are powerful solid-state nuclear magnetic resonance (NMR) tools for extracting structural information from 13 C-enriched biomolecules, but necessarily long acquisition times restrict their applications. In this work, we explore the broad utility and underutilized power of a chemical shift-selective one-dimensional (1D) version of a 2D 13 C– 13 C spin-diffusion solid-state NMR technique. The method, which is called 1D dipolar-assisted rotational resonance (DARR) difference, is applied to a variety of biomaterials including lignocellulosic plant cell walls, microcrystalline peptide fMLF, and black widow dragline spider silk. 1D 13 C– 13 C spin-diffusion methods described here apply in select cases in which the 1D 13 C solid-state NMR spectrum displays chemical shift-resolved moieties. Furthermore, this is analogous to the selective 1D nuclear Overhauser effect spectroscopy (NOESY) experiment utilized in liquid-state NMR as a faster (1D instead of 2D) and often less ambiguous (direct sampling of the time domain data, coupled with increased signal averaging) alternative to 2D NOESY. Selective 1D 13 C– 13 C spin-diffusion methods are more time-efficient than their 2D counterparts such as proton-driven spin diffusion (PDSD) and dipolar-assisted rotational resonance. The additional time gained enables measurements of 13 C– 13 C spin-diffusion buildup curves and extraction of spin-diffusion time constants TSD, yielding detailed structural information. Specifically, selective 1D DARR difference buildup curves applied to 13 C-enriched hybrid poplar woody stems confirm strong spatial interaction between lignin and acetylated xylan polymers within poplar plant secondary cell walls, and an interpolymer distance of ~0.45–0.5 nm was estimated. Additionally, Tyr/Gly long-range correlations were observed on isotopically enriched black widow spider dragline silks.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Understanding the impact of the gas diffusion layer structure on catalyst utilization in the PEM water electrolyzer

A multiphysics half-cell model of a polymer electrolyte membrane water electrolyzer (PEMWE) was developed to probe impacts of the detailed 3-dimensional pore structure of the gas diffusion layer (GDL) on performance characteristics. We show that pores in the titanium GDL mesh led to significant underutilization of the catalyst layer (CL), with only 45% of the catalyst effectively utilized. This contradicts the assumption of uniform electron flow across the CL, as shown in graphical abstract (a), as near-zero current was observed near GDL pore regions and the current distribution in CL was influenced by GDL structure, as shown in graphical abstract (b). Instead, oxygen generation was primarily concentrated under the solid titanium regions, diffusing out around the pore walls. High current density peaks were also noted at the GDL-catalyst contact, correlating with degradation hotspots that were directly observed in companion experiments, as shown in graphical abstract (c). Collectively, these findings point to the critical importance of the heterogeneous GDL porous architecture not only for PEMWE efficiency but also for uneven degradation of the CL.

COMSOL↗
DOE OSTI2025

Co‐Doping Approach for Enhanced Electron Extraction to TiO 2 for Stable Inorganic Perovskite Solar Cells

Inorganic perovskite CsPbI 3 solar cells hold great potential for improving the operational stability of perovskite photovoltaics. However, electron extraction is limited by the low conductivity of TiO 2 , representing a bottleneck for achieving stable performance. In this study, a co‐doping strategy for TiO 2 using Nb(V) and Sn(IV), which reduces the material's work function by 80 meV compared to Nb(V) mono‐doped TiO 2 , is introduced. To gain fundamental understanding of the processes at the interfaces between the perovskite and charge‐selective layer, transient surface photovoltage measurements are applied, revealing the beneficial effect of the energetic and structural modification on electron extraction across the CsPbI 3 /TiO 2 interface. Using 2D drift‐diffusion simulations, it is found that co‐doping reduces the interface hole recombination velocity by two orders of magnitude, increasing the concentration of extracted electrons by 20%. When integrated into n–i–p solar cells, co‐doped TiO 2 enhances the projected T S80 lifetimes under continuous AM1.5G illumination by a factor of 25 compared to mono‐doped TiO 2 . This study provides fundamental insights into interfacial charge extraction and its correlation with operational stability of perovskite solar cells, offering potential applications for other charge‐selective contacts.

14 SOLAR ENERGY↗
DOE OSTI2021

Simulation of hardened cement degradation and estimation of uncertainty in predicted failure times with peridynamics

Modeling the degradation of cement-based infrastructure due to aqueous environmental conditions continues to be a challenge. In order to develop a capability to predict concrete infrastructure failure due to chemical degradation, here we created a chemomechanical model of the effects of long-term water exposure on cement paste. The model couples the mechanical static equilibrium balance with reactive–diffusive transport and incorporates fracture and failure via peridynamics (a meshless simulation method). The model includes fundamental aspects of degradation of ordinary Portland cement (OPC) paste, including the observed softening, reduced toughness, and shrinkage of the cement paste, and increased reactivity and transport with water induced degradation. This version of the model focuses on the first stage of cement paste decalcification, the dissolution of portlandite. Given unknowns in the cement paste degradation process and the cost of uncertainty quantification (UQ), we adopt a minimally complex model in two dimensions (2D) in order to perform sensitivity analysis and UQ. We calibrate the model to existing experimental data using simulations of common tests such as flexure, compression and diffusion. Then we calculate the global sensitivity and uncertainty of predicted failure times based on variation of eleven unique and fundamental material properties. We observed particularly strong sensitivities to the diffusion coefficient, the reaction rate, and the shrinkage with degradation. Also, the predicted time of first fracture is highly correlated with the time to total failure in compression, which implies fracture can indicate impending degradation induced failure; however, the distributions of the two events overlap so the lead time may be minimal. Extension of the model to include the multiple reactions that describe complete degradation, viscous relaxation, post-peak load mechanisms, and to three dimensions to explore the interactions of complex fracture patterns evoked by more realistic geometry is straightforward and ongoing.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Neutron irradiation-enhanced grain growth in tungsten and tungsten alloys

Herein, to understand the microstructural stability of candidate plasma-facing materials under fusion-relevant environments, neutron irradiation of W and W-3%Re alloys with and without K and La dopants was performed in the mixed-spectrum High Flux Isotope Reactor at nominal temperatures of ~850 °C and ~1100 °C to calculated doses between 0.42 and 0.47 dpa. To the best of our knowledge, this study presents the first experimental evidence of radiation-enhanced recrystallization in W and undoped W–Re alloys at ~850 °C, conditions where thermal annealing does not cause any grain growth in a similar timescale. Potassium- or lanthanum-doped tungsten alloys showed more resistance to radiation-enhanced grain growth. We explain the acceleration of grain growth by analyzing the self-diffusion constant under atomic displacement environments. The microstructural observations of the studied W variants suggest that La doping is more effective than K doping for mitigating recrystallization. This study also found that radiation-enhanced recrystallization is an important consideration when designing and applying W to plasma-facing components in future nuclear fusion reactors.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Mapping of fracture and ionic conductivity changes in ion implanted solid electrolytes: Insights from molecular dynamics

Ion implantation emerges as a promising technique to address the persistent challenge of lithium (Li) filament growth in solid-state electrolytes as it can induce compressive stresses inhibiting crack growth and deflect dendrites, de facto mitigating early electrolyte failure. In this study, we examine the potential paradox of ion implantation: while aiming to enhance electrolyte performance, the radiation damage associated with implantation might inadvertently compromise both the ionic conductivity and the intrinsic fracture toughness of the material, rendering the material unsuitable for battery applications. Specifically, we employed molecular dynamics simulations to examine the scope of the downsides of ion implantation, specifically: (i) reduced ionic conductivity (due to radiation-induced amorphization) and (ii) mechanical stability (due to radiation-induced embrittlement) in ion-implanted Li 7 La 3 Zr 2 O 12 (LLZO) solid-state electrolytes. We explore how radiation damage impacts LLZO’s crystalline structure, Li-ion diffusion, and fracture properties at various temperatures and radiation damage levels. The study aims to provide insights into the competing effects of ion implantation and suggest potential engineering strategies for developing more robust solid-state electrolytes with improved conductivity and dendrite resistance.

Conductivity↗
DOE OSTI2022

Role of side-chain length on gas transport of CO 2 /CH 4 mixtures in polymers with side-chain porosity

Polymers of intrinsic microporosity (PIMs) are traditionally formed from ladder backbones, but recent synthetic advances have allowed for the formation of non-traditional PIMs using a poly(ladder) motif, whereby rigid PIM-like sidechains are appended onto more flexible backbones. The effect of side-chain length on free volume and gas transport properties was recently evaluated for a methoxy-functionalized poly(ladder) (OMe-ROMP). In this study, we elaborate on the role of side-chain length and its influence on mixed-gas performance and plasticization stability for OMe-ROMP. Pure-gas sorption results are also reported, including hysteresis effects from CO 2 conditioning. Taken together, this study reveals the role of side-chain length on gas sorption, diffusion, and plasticization for CO 2 /CH 4 separations. Finally, we conclude that the length of a rigid side chain in the poly(ladder) motif is a valuable structural parameter to control sorption, diffusion, and stability towards plasticization for gas separation membrane materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Bayesian learning with Gaussian processes for low-dimensional representations of time-dependent nonlinear systems

This work presents a data-driven method for learning low-dimensional time-dependent physics-based surrogate models whose predictions are endowed with uncertainty estimates. We use the operator inference approach to model reduction that poses the problem of learning low-dimensional model terms as a regression of state space data and corresponding time derivatives by minimizing the residual of reduced system equations. Standard operator inference models perform well with accurate training data that are dense in time, but producing stable and accurate models when the state data are noisy and/or sparse in time remains a challenge. Another challenge is the lack of uncertainty estimation for the predictions from the operator inference models. Our approach addresses these challenges by incorporating Gaussian process surrogates into the operator inference framework to (1) probabilistically describe uncertainties in the state predictions and (2) procure analytical time derivative estimates with quantified uncertainties. The formulation leads to a generalized least-squares regression and, ultimately, reduced-order models that are described probabilistically with a closed-form expression for the posterior distribution of the operators. The resulting probabilistic surrogate model propagates uncertainties from the observed state data to reduced-order predictions. Furthermore, we demonstrate the method is effective for constructing low-dimensional models of two nonlinear partial differential equations representing a compressible flow and a nonlinear diffusion–reaction process, as well as for estimating the parameters of a low-dimensional system of nonlinear ordinary differential equations representing compartmental models in epidemiology.

Data-driven model reduction↗
DOE OSTI2023

Optimal white-noise stochastic forcing for linear models of turbulent channel flow

In the present study an optimisation problem is formulated to determine the forcing of an eddy-viscosity-based linearised Navier–Stokes model in channel flow at $Re_\tau \approx 5200$ ( $Re_\tau$ is the friction Reynolds number), where the forcing is white-in-time and spatially decorrelated. The objective functional is prescribed such that the forcing drives a response to best match a set of velocity spectra from direct numerical simulation (DNS), as well as remaining sufficiently smooth. Strong quantitative agreement is obtained between the velocity spectra from the linear model with optimal forcing and from DNS, but only qualitative agreement between the Reynolds shear stress co-spectra from the model and DNS. The forcing spectra exhibit a level of self-similarity, associated with the primary peak in the velocity spectra, but they also reveal a non-negligible amount of energy spent in phenomenologically mimicking the non-self-similar part of the velocity spectra associated with energy cascade. By exploiting linearity, the effect of the individual forcing components is assessed and the contributions from the Orr mechanism and the lift-up effect are also identified. Finally, the effect of the strength of the eddy viscosity on the optimisation performance is investigated. The inclusion of the eddy viscosity diffusion operator is shown to be essential in modelling of the near-wall features, while still allowing the forcing of the self-similar primary peak. In particular, reducing the strength of the eddy viscosity results in a considerable increase in the near-wall forcing of wall-parallel components.

Mechanics↗
DOE OSTI2023

Role of Intra-Domain Heterogeneity on Ion and Polymer Dynamics in Block Polymer Electrolytes: An Approach for Spatially Resolving Dynamics and Ion Transport

The design of safe and high-performance, nanostructured, block polymer (BP) electrolytes for lithium-ion batteries requires a thorough understanding of the key parameters that govern local structure and dynamics. Yet, the interfaces between microphase separated domains can introduce complexities in this local behavior that can be challenging to quantify. Herein, the local polymer, cation (Li + ), and anion dynamics were described in salt-doped polystyrene block poly(oligo-oxyethylene methyl ether methacrylate) (PS-b-POEM) through a quantitative framework that considered the effects of polymer architecture, segmental mixing, chain stretching, and confinement on polymer mobility and ion transport. This framework was validated through nuclear magnetic resonance (NMR) spectroscopy measurements on solid (dry) polymer electrolyte samples. Notably, a mobility transition temperature (T mobility ) was identified through NMR spectroscopy that captured the local dynamics more accurately than the thermal glass transition temperature. Additionally, the approach quantitatively described the mobility gradient across a domain when segmental mixing effects were combined with chain stretching and confinement information, especially at higher segregation strengths – facilitating the assessment of local ion diffusion and conductivity. As a result, spatially averaged local ion diffusion predictions quantitatively matched NMR-measured ion diffusivities in the BP samples, while spatially summed ionic conductivity predictions across a domain qualitatively captured trends in the measured ionic conductivities.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Simulating Long–Term Dynamics of Radiation Belt Electrons Using DREAM3D Model

Here, we compared the performance of DREAM3D simulations in reproducing the long-term radiation belt dynamics observed by Van Allen Probes over the entire year of 2017 with various boundary conditions (BCs) and model inputs. Specifically, we investigated the effects of three different outer boundary conditions, two different low-energy boundary conditions for seed electrons, four different radial diffusion (RD) coefficients (DLL), four hiss wave models, and two chorus wave models from the literature. Using the outer boundary condition driven by GOES data, our benchmark simulation generally well reproduces the observed radiation belt dynamics inside L* = 6, with a better model performance at lower μ than higher μ, where μ is the first adiabatic invariant. By varying the boundary conditions and inputs, we find that: (a) The data-driven outer boundary condition is critical to the model performance, while adding in the data-driven seed population doesn't further improve the performance. (b) The model shows comparable performance with DLL from Brautigam and Albert (2000, https://doi.org/10.1029/1999ja900344), Ozeke et al. (2014, https://doi.org/10.1002/2013ja019204), and Liu et al. (2016, https://doi.org/10.1002/2015gl067398), while with DLL from Ali et al. (2016, https://doi.org/10.1002/2016ja023002) the model shows less RD compared to data. (c) The model performance is similar with data-based hiss models, but the results show faster loss is still needed inside the plasmasphere. (d) The model performs similarly with the two different chorus models, but better capturing the electron enhancement at higher μ using the Wang et al. (2019, https://doi.org/10.1029/2018ja026183) model due to its stronger wave power, since local heating for higher energy electrons is under-reproduced in the current model.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Thermal Conductivity of Graphene Coated Copper Under Uniaxial Tensile Mechanical Strain

Graphene continues to demonstrate promise as a highly effective barrier coating, even at only one atom thick. The thermal properties of this coating are also promising to allow diffusion of heat across the surface, as the isolated graphene is an intrinsically good thermal conductor, yet this and its behavior under mechanical deformation has been less extensively studied. This report demonstrates that the in-plane thermal conductivity and interfacial thermal conductance of graphene coatings on copper are affected by mechanical strain. By inducing a strain in the copper substrate, the Raman-active 2D peak exhibits a change in position as well as a change in laser power dependence as the copper substrate is uniaxially elongated to a maximum of 0.5%. Non-linear trends in thermal conductivity are observed with tensile strain in samples with differing strain transfer rates from the substrate, indicating the close correlation between intrinsic thermal conduction and interfacial properties in atomically thin coatings transferred onto metals.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Universality in diffusion-controlled nucleation and growth

Nucleation and growth are studied in a system that undergoes diffusion-controlled condensation under gradual changes in parameters, such as cooling. Here, it is demonstrated that when the Gibbs–Thompson effect becomes negligible, the system falls into a universal regime. i.e., the final droplet size distribution remains invariant under certain rescaling of system parameters. An approximate yet very accurate analytic form is obtained for the final droplet size distribution in this regime.

36 MATERIALS SCIENCE↗