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DOE OSTI2022

Method for fabricating embedded nanostructures with arbitrary shape

A layered heterostructure, comprising alternating layers of different semiconductors, wherein one of the atom species of one of the semiconductors has a faster diffusion rate along an oxidizing interface than an atom species of the other semiconductor at an oxidizing temperature, can be used to fabricate embedded nanostructures with arbitrary shape. The result of the oxidation will be an embedded nanostructure comprising the semiconductor having slower diffusing atom species surrounded by the semiconductor having the higher diffusing atom species. The method enables the fabrication of low- and multi-dimensional quantum-scale embedded nanostructures, such as quantum dots (QDs), toroids, and ellipsoids.

Wang, George T.↗

DOE OSTI2022

The effects of turbulence on the flame structure and NO formation of ammonia turbulent premixed combustion at various equivalence ratios

Ammonia is carbon-free and is regarded as a potential fuel to address global warming issues. Here, in this work, three-dimensional direct numerical simulations (DNS) of ammonia/air turbulent premixed flames were performed to explore the influence of turbulence and equivalence ratio on the flame structure and NO formation characteristics. Two equivalence ratios were considered, i.e. Φ=0.9 and Φ=1.1. The general flame structures were presented and species distributions were examined. The NO mass fraction was found to be the highest in the product for the lean case and in the reaction zone for the rich case. The conditional mean values of species mass fractions and reaction rates were compared with those of the unstrained and strained laminar premixed flames to explore how well the laminar flame structures can approach those of the turbulent flame. The budget analysis of the species transport equations showed that turbulent diffusion plays an important role in species transport. The turbulent diffusivity D T was estimated using the gradient hypothesis based on the DNS data. Various laminar flame simulations with different diffusivities were carried out. It was shown that the conditional means of the DNS agree well with those of the laminar flames including D T in the transport property calculation. The global and local NO formation characteristics were investigated. It was found that the mean NO production conditioned on the progress variable is lower compared with the corresponding laminar flame in the rich case. However, the relative contributions from various NO pathways are rarely affected by turbulence. The NO mass fraction is higher in negative curvature regions compared with positive curvature regions of the flame surface for the rich case, which is due to the preferential diffusion of H 2 and other radicals and the enhanced NO pathways in negatively curved regions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Machine-learning-assisted deciphering of microstructural effects on ionic transport in composite materials: A case study of Li 7 La 3 Zr 2 O 12 -LiCoO 2

The effective diffusivity of ionic species in multiphase materials is critical for the design and function of composite materials for electrochemical energy storage. In practice, effective diffusivity depends sensitively not only on the intrinsic diffusivities of constituting materials but also on their topological arrangement; nevertheless, these coupled contributions are oversimplified in most analytical models. Here, we combine atomistically informed mesoscale modeling and machine learning (ML) analysis to unravel how such features affect effective diffusivity in two-phase composites. Using the Li 7 La 3 Zr 2 O 12 -LiCoO 2 composite solid-state battery cathode as a model system, we compute effective diffusivity for 600 distinct dense polycrystalline microstructures with different topological configurations of grains, grain boundaries, and heterointerfaces. We verify that in addition to atomic-scale variabilities, microstructural feature diversity can significantly impact effective transport properties. Across the ensemble of test microstructures, this often results in bimodal distributions of effective diffusivity that encompass two qualitatively distinct operating mechanisms, which we identify via flux analysis. An ML approach reveals that the most critical determining factors for effective diffusivity are the connectivity of bulk phases and their heterointerfaces. The role of ionic mobility at the heterointerfaces is also discussed. These insights highlight the combined importance of microstructure and interface engineering in tuning the transport properties of ionic species in composite materials. In conclusion, our framework can also be extended for understanding generic microstructure-property relationships in other complex multiphase materials.

25 ENERGY STORAGE↗

DOE OSTI2021

Large-eddy simulation of a multi-injection flame in a diesel engine environment using an unsteady flamelet/progress variable approach

In this work, large-eddy simulations (LESs) are conducted for a multiple-injection flame in a diesel engine environment using an unsteady flamelet/progress variable (UFPV) approach in which differential diffusion is considered. The suitability of the UFPV tabulation approach is first evaluated through a priori analyses using the state-of-the-art direct numerical simulation (DNS) dataset. Both the instantaneous data and the conditional values for the major and minor species' mass fractions are compared between the UFPV and the DNS. The comparisons show that the proposed UFPV tabulation approach can give good predictions for the multiple-injection flame at different injection phases. While the gas temperature and major species mass fractions can be accurately predicted with or without differential diffusion being considered in the UFPV flamelet library, the prediction accuracy for the highly diffusive species (e.g., hydrogen) in the main injection phase can be noticeably improved when differential diffusion is taken into account. The fully coupled LES/UFPV simulations show that the overall structure of the multiple-injection flame can be predicted, and the conditional thermo-chemical values are close to the filtered DNS dataset. The reasons for the remaining discrepancies found in the a priori analyses and the a posteriori simulations using the UFPV approach are analyzed.

Wen, Xu (ORCID:0000000331334292)↗

DOE OSTI2019

Kinetic Monte Carlo Simulations of Electrochemical Oxidation and Reduction of Pt(111)

Kinetic Monte Carlo simulations of electrochemical oxidation and reduction are presented that match many features of the experimentally observed electrochemical and morphological response of Pt(111). Included in the simulation are all relevant microscopic transitions, including the formation of Pt-OH and Pt-O from Pt, surface diffusion of all three species, as well as an effective place exchange diffusion at high potential. A detailed description of this approach to modeling such a complex surface is also presented. Overall, it is found that many features of the Pt(111) CV, including hydroxylation, hysteresis, and surface roughening, can be correlated to events associated with n -coordinated surface species, such as the hydroxylation wave corresponding to a one-electron oxidation of 9-coordinated terrace sites. Oxidation to Pt-O species at potentials above 1.0 V are shown to correlate to the presence of growing surface roughness, and the simulations suggest the onset of Pt-O formation in steady-state cyclic voltammetry is dominated by the oxidation of 8-coordinated step edges rather than terrace sites. Implications for the stability of Pt(111) catalysts after thousands of voltammetric cycles are discussed.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Cation–Ligand Interactions Dictate Salt Partitioning and Diffusivity in Ligand-Functionalized Polymer Membranes

Membranes are an attractive alternative to current thermal separations due to their scalability and energy efficiency in desalinating water. Unfortunately, many of the conventional membrane materials available today are unable to differentiate between ionic solutes, especially alkali cations, compromising their use in ion–ion separations. Inspired by the ion-specific interactions exhibited by biological ion channels, recent research efforts have focused on synthesizing and characterizing new polymeric materials that incorporate ligands into polymer networks to bias solubility and/or diffusivity of one cationic species over another. Despite these efforts, little is known about the influence of incorporating ligands into polymer membranes on solubility and diffusivity of the complexing species. In this study, we first build a qualitative model of salt partitioning, diffusivity, and permeability in generic cation-complexing ligand-functionalized polymer membranes. Next, to validate our model and hypotheses, we perform atomistic molecular dynamics simulations of a 12-crown-4-functionalized membrane in the presence of alkali halide salts at low concentration. Generally, cation complexation enhances cation solubility but decreases diffusivity. Interestingly, the reduction in diffusivity is predicted to be larger than the enhancement in solubility for materials which operate by the mechanisms proposed in our physical picture, ultimately resulting in a reduction in the permeability of the selectively complexing ion.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Selective atomic sieving across metal/oxide interface for super-oxidation resistance

Abstract Surface passivation, a desirable natural consequence during initial oxidation of alloys, is the foundation for functioning of corrosion and oxidation resistant alloys ranging from industrial stainless steel to kitchen utensils. This initial oxidation has been long perceived to vary with crystal facet, however, the underlying mechanism remains elusive. Here, using in situ environmental transmission electron microscopy, we gain atomic details on crystal facet dependent initial oxidation behavior in a model Ni-5Cr alloy. We find the (001) surface shows higher initial oxidation resistance as compared to the (111) surface. We reveal the crystal facet dependent oxidation is related to an interfacial atomic sieving effect, wherein the oxide/metal interface selectively promotes diffusion of certain atomic species. Density functional theory calculations rationalize the oxygen diffusion across Ni(111)/NiO(111) interface, as contrasted with Ni(001)/NiO(111), is enhanced. We unveil that crystal facet with initial fast oxidation rate could conversely switch to a slow steady state oxidation.

(S)TEM, oxidizing metals↗

DOE OSTI2025

Quantum Sieving for Isotopic Separations of Gases Using Porous Materials─30 Years of Progress

Here, this paper reviews theoretical and experimental efforts to establish microporous materials that can be used to separate isotopologues of molecular gases such as H 2 and D 2 . Emphasis is placed on use of simplified models to highlight the quantum phenomena that make these separations possible. In equilibrium adsorption, differences in zero point energy in the adsorbed states of molecules favor binding of heaver isotopologues (e.g. D 2 relative to H 2 ). Experimental data showing this effect was reported as early as 1933, but the theoretical work of Beenakkers et al. in 1995 [Chem. Phys. Lett. 232 (1995) 379-382] spurred modern efforts to develop materials with strong so-called quantum sieving. In porous materials where the transition state for molecular diffusion is more strongly confined than the energy minima associated with equilibrium adsorption, differences in zero point energies between these two sites can lead to isotopic differences in molecular diffusivities. This effect favors diffusion of heavier species (e.g. D 2 ) relative to lighter species (e.g. H 2 ). This so-called kinetic quantum sieving has been observed experimentally in porous carbons and in porous organic cage materials. We show that quantum tunneling, which favors hopping of lighter species across energy barriers, diminishes the strength of kinetic quantum sieving but that it appears to make only a small contribution to the net molecular diffusivities in many porous materials of practical interest.

Sholl, David S. [Oak Ridge National Laboratory (OR↗

DOE OSTI2024

Complete quasilinear model for the acceleration-driven lower hybrid drift instability and a computational assessment of its validity

A complete quasilinear model is derived for the electrostatic acceleration-driven lower hybrid drift instability in a uniform two-species low-beta plasma in which current is perpendicular to the background magnetic field. The model consists of coupled nonlinear velocity space diffusion equations for the volume-averaged ion and electron distribution functions. Each species' diffusion coefficient depends on a time-evolving spectral density of the electric-field energy per unit volume and a time-evolving dispersion relation. The dispersion relation is expressed analytically in integral form without the use of asymptotic limits and applies to arbitrary distribution functions, so long as they can be expressed as a function of one velocity coordinate, e.g., f⁡(vy) or f⁡(v⊥). The quasilinear model conserves energy and is complete in that it fully describes the evolution of the distribution functions, including resonant and nonresonant particle-wave interactions, while accounting for distribution-function-dependent mixed-complex frequencies. Further, the quasilinear diffusion model is solved numerically and self-consistently using a Crank-Nicolson temporal discretization and a second-order finite-volume velocity-space discretization. Numerical solutions are compared to nonlinear fourth-order accurate continuum kinetic Vlasov-Poisson simulations. Evolution of electric-field energy, growth rates, distribution functions, and diffusion coefficients are shown to be in agreement with Vlasov simulations. The quasilinear model is shown to predict anomalous transport terms, like resistivity and heating, to within a factor of order unity. Discrepancies between the quasilinear model and Vlasov simulations are assessed and attributed primarily to lack of damping in the quasilinear description and to the use of unperturbed-orbit susceptibilities in the linear theory dispersion relation. The results illuminate the predictive accuracy of the quasilinear model, place approximate bounds on its validity, and provide much needed vetting of quasilinear theory's ability to predict the nonlinear state of a microturbulent plasma.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2025

Trapping and imaging dynamic battery nanointerfaces via electrified cryo-EM

The electrified interface between a liquid and a solid underpins diverse phenomena, from ion-transfer during battery operation to action potentials enabling biological communication. However, conventional tools are blind to the nanoscale dynamics of this metastable interface. Here, we leverage electrified cryo–electron microscopy (eCryo-EM), a technique that rapidly freezes and kinetically traps these dynamic, nonequilibrium states during battery operation for nanoscale characterization. Collective snapshots of the electrified interface at controlled time intervals quantifies early-stage growth kinetics of the solid electrolyte interphase (SEI), a passivation film that governs electron and ion transport. Unexpectedly, the diffusivity of charged species of the two SEI films with differing chemistry and performance are estimated to be within 10% of the other, indicated by the slope of their diffusion-limited SEI growth regimes. Instead, the slope of the reaction-limited SEI growth regimes differs by a factor of 3, suggesting that lowered reactivity of the high-performance electrolyte is largely responsible for its high coulombic efficiency.

Science & Technology - Other Topics↗

DOE OSTI2025

Developing the Science Basis for Understanding Polymer Encapsulant Degradation Mechanisms: DuraMAT 2.0 Final Project Report

Polymeric encapsulants are essential materials in photovoltaic modules, protecting sensitive electronics from the environment while providing mechanical integrity to the multilayered assembly. However, these polymeric materials are susceptible to degradation processes driven by the ingress of environmental species, ultraviolet radiation, thermal stresses, and mechanical loading. In this study, we employ a combined atomistic simulation and accelerated aging experimental approach to study the molecular-scale mechanisms of encapsulant degradation. Classical molecular dynamics simulations quantify the diffusion of environmental and degradation species through the polymer matrix, producing composition-specific diffusion coefficients. Reactive simulations characterize activation energy barriers and reaction rate constants for key chemical pathways. In parallel, thermal-desorption analyses coupled with mass spectrometry monitor the emergence and concentration profiles of degradation products under controlled stressor conditions. By integrating simulation and experiment, we establish quantitative correlations between polymer composition, species diffusivity, and chemical reactivity. We anticipate that these relations and quantitative values could serve as high-fidelity inputs to reaction-diffusion models, enabling physics-informed lifetime predictions and guiding the design of more durable encapsulant materials for solar energy applications.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Shapeshifting Nanocatalyst for CO2 Conversion

The conversion of CO2 into high-value chemicals through a photoreduction reaction in water is a promising route to reduce the dependence on fossil fuels. Enhancing selectivity toward hydrocarbons or alcohols can be achieved by Ag-Cu alloys. However, the stabilized surface state created by Ag-Cu interactions is still poorly understood. In this work, multi-modal in situ X-ray experiments reveals underlying mechanisms and the evolution of Ag-Cu nanoparticles under CO2 reduction reaction (CO2RR) conditions. Both morphological and chemical changes of Ag and Cu species induced by diffusion mechanics are tracked during nanocatalyst operation. The initial spheroid Ag-Cu nanoparticles are composed of a Cu-rich shell and Ag-rich core. The reduction treatment promotes Ag migration toward the surface. During photocatalytic CO2 reduction reaction, Cu atoms migrate back to the surface, forming Ag-Cu-O species. The study observes the surface oxidation of Cu(0) to Cu+ and the presence of Ag at the sub-surface region. Furthermore, nanoparticles change their shape, decreasing their specific surface area, driven by Cu diffusion during the CO2 photoreduction reaction. The results provide invaluable insights into the dynamic restructuring of the catalyst under reaction conditions and into the active species responsible for CO2 conversion.

CO2 reduction reaction↗

DOE OSTI2024

Interactions Between Climate and Species Drive Future Forest Carbon and Water Balances

Global change is altering forest carbon and water balances; however, the extent to which tree species shape ecosystem‐scale responses to climate, particularly in biodiverse forests, remains unclear. To address this, we simulated the effects of an envelope of future climate conditions on watershed carbon and water balances and quantified the contributions of tree species based on their xylem anatomy. We accomplished this by incorporating species‐level transpiration calculations into a landscape‐scale ecosystem process model. Our revised model linked the effects of forest succession, species composition, and climate change on water and carbon. Calibration of forest water fluxes using sap flux measurements and catchment water balances captured variability in species transpiration and interannual ET in biodiverse, humid temperate forest catchments in the southern Blue Ridge Mountains, USA. Across wet and dry future climate projections, ET increased, and streamflow and net carbon uptake decreased, particularly under a scenario of increasing drought. Despite accounting for just 30% of current biomass, diffuse‐porous tree species were the main driver of carbon and water flux responses now and in the future, thus intensifying the increase in ET and decline in streamflow. As diffuse‐porous biomass continues to increase, these forests will be increasingly sensitive to drought, amplifying losses of carbon sequestration and freshwater delivery.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Cation–polymer interactions and local heterogeneity determine the relative order of alkali cation diffusion coefficients in PEGDA hydrogels

Current research efforts are focused on endowing polymer membranes with ion–ion selectivity by incorporating ion–polymer interactions into materials to bias the selective partitioning and or diffusivity of one species over another. However, little is known about the impact of such interactions on the mechanisms of ion transport. In this study, we probe the influence of cation–polymer interactions on cation, anion, and salt diffusivity in a model membrane material, poly(ethylene glycol) diacrylate (PEGDA) by modeling concentrated polyethylene oxide solutions via molecular dynamics simulations. These results are compared to published experimental data for LiCl, NaCl, and KCl diffusion in PEGDA. Experimentally, the order of salt and cation diffusion coefficients for LiCl, NaCl, and KCl deviate from the order in aqueous solutions. Here, simulations identify these deviations to arise from cation–polymer coordination in the membrane. Both the fraction of bound cations and the average binding lifetime increases with decreasing cation hydration free energy (moving down the alkali series), leading to different diffusivity trends in the membrane compared to solution. However, to recover the experimentally observed order of diffusivities cations and salt in our simulations, we needed to incorporate membrane heterogeneity explicitly via a polymer charge scaling procedure. Together, our results indicate that cation–polymer interactions, as well as spatial heterogeneity within the membrane, play a critical role in dictating the observed order of alkali cation and salt diffusion coefficients in membranes.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Immobilization of active ammonia-oxidizing archaea in hydrogel beads

Abstract Ammonia-oxidizing archaea (AOA) are major players in the nitrogen cycle but their cultivation represents a major challenge due to their slow growth rate and limited tendency to form biofilms. In this study, AOA was embedded in small (~2.5 mm) and large (~4.7 mm) poly(vinyl alcohol) (PVA)—sodium alginate (SA) hydrogel beads cross-linked with four agents (calcium, barium, light, or sulfate) to compare the differences in activity, the diffusivity of nitrogen species (NH 4 + , NO 2 − , and NO 3 − ), and polymer leakage in batch systems over time. Sulfate-bound PVA-SA beads were the most stable, releasing the lowest amount of polymer without shrinking. Diffusion coefficients were found to be 2 to 3 times higher in hydrogels than in granules, with ammonium diffusivity being ca . 35% greater than nitrite and nitrate. Despite a longer lag phase in small beads, embedded AOA sustained a high per volume rate of ammonia oxidation compatible with applications in research and wastewater treatment.

42 ENGINEERING↗

DOE OSTI2022

Verification of Bison fission product species conservation under TRISO reactor conditions

When assessing the reliability and predictive capabilities of a simulation tool, code verification is used to ensure that the implemented numerical algorithm is a faithful representation of its underlying mathematical model, including partial differential or integral equations, initial and boundary conditions, and auxiliary relationships. During this process, numerical results in a discrete solution are compared to the analytical solution of the mathematical model. Here, in this paper, the code verification process is applied to one-dimensional spatiotemporal problems that exercise partial differential equation governing the conservation of fission product species (or mass diffusion). Numerical experiments were performed in the Bison fuel performance code to evaluate its predictive capability under various TRISO reactor conditions such as base irradiation and safety heating test conditions for either short- or long-lived fission product species, as well as a case concerning evaporation from the outer surface of a particle. The code predictions were compared with the expected exact results obtained from the analytical expressions, and the fact that they demonstrate the correct analytical behavior provides strong evidence of proper numerical algorithm implementation.

07 ISOTOPE AND RADIATION SOURCES↗

DOE OSTI2023

Extraction Kinetics of Rare Earth Elements from Ion-Adsorbed Underclays

Citric acid has been identified as an environmentally sustainable organic acid capable of leaching up to ~30% of easily accessible REEs from underclay material. An analysis of the leaching profiles was performed to discern the reaction rates, extraction efficiencies, and potential leaching mechanisms of REEs and cations of interest from ion-adsorbed underclays. The initial leaching stage follows a slow intraparticle diffusion mechanism followed by a second stage controlled by a mixed diffusion regime. The leaching profiles of Ca and P were similar to those of REEs, suggesting that REEs are most likely derived from mineral surfaces such as hydroxyapatite or crandallite rather than predominately from underclays. Fitting to a modified diffusion control model found diffusion-controlled leaching to be the primary mechanism whereas non-diffusive mechanisms made up about 22% of the extracted REEs. Gangue cations associated with underclays had less non-diffusive leaching than REE species, indicating that their leaching kinetics may be dominated by diffusion from within the material or potentially from product layer formation. Fitting to Boyd plots further indicated that REEs were leached following intraparticle diffusion control. These results have important implications for the development of more efficient and sustainable methods for extracting REEs or critical minerals from alternative feedstocks.

Prem, Priscilla↗

DOE OSTI2020

Pattern formation in a coupled membrane-bulk reaction-diffusion model for intracellular polarization and oscillations

Reaction-diffusion systems have been widely used to study spatio-temporal phenomena in cell biology, such as cell polarization. Coupled bulk-surface models naturally include compartmentalization of cytosolic and membrane-bound polarity molecules. Here we study the distribution of the polarity protein Cdc42 in a mass-conserved membrane-bulk model, and explore the effects of diffusion and spatial dimensionality on spatio-temporal pattern formation. We first analyze a one-dimensional (1-D) model for Cdc42 oscillations in fission yeast, consisting of two diffusion equations in the bulk domain coupled to nonlinear ODEs for binding kinetics at each end of the cell. In 1-D, our analysis reveals the existence of symmetric and asymmetric steady states, as well as anti-phase relaxation oscillations typical of slow-fast systems. We then extend our analysis to a two-dimensional (2-D) model with circular bulk geometry, for which species can either diffuse inside the cell or become bound to the membrane and undergo a nonlinear reaction-diffusion process. We also consider a nonlocal system of PDEs approximating the dynamics of the 2-D membrane-bulk model in the limit of fast bulk diffusion. In all three model variants we find that mass conservation selects perturbations of spatial modes that simply redistribute mass. In 1-D, only anti-phase oscillations between the two ends of the cell can occur, and in-phase oscillations are excluded. In higher dimensions, no radially symmetric oscillations are observed. Instead, the only instabilities are symmetry-breaking, either corresponding to stationary Turing instabilities, leading to the formation of stationary patterns, or to oscillatory Turing instabilities, leading to traveling and standing waves. Codimension-two Bogdanov—Takens bifurcations occur when the two distinct instabilities coincide, causing traveling waves to slow down and to eventually become stationary patterns. Our work clarifies the effect of geometry and dimensionality on behaviors observed in ma.ss-conserved cell polarity models.

97 MATHEMATICS AND COMPUTING↗