Continuum Scale Research Articles

A Multiscale Method for Two-Component, Two-Phase Flow with a Neural Network Surrogate

Understanding the dynamics of phase boundaries in fluids requires quantitative knowledge about the microscale processes at the interface. We consider the sharp-interface motion of the compressible two-component flow and propose a heterogeneous multiscale method (HMM) to describe the flow fields accurately. The multiscale approach combines a hyperbolic system of balance laws on the continuum scale with molecular-dynamics (MD) simulations on the microscale level. Notably, the multiscale approach is necessary to compute the interface dynamics because there is—at present—no closed continuum-scale model. The basic HMM relies on a moving-mesh finite-volume method and has been introduced recently for the compressible one-component flow with phase transitions by Magiera and Rohde in (J Comput Phys 469: 111551, 2022). To overcome the numerical complexity of the MD microscale model, a deep neural network is employed as an efficient surrogate model. The entire approach is finally applied to simulate droplet dynamics for argon-methane mixtures in several space dimensions. To our knowledge, such compressible two-phase dynamics accounting for microscale phase-change transfer rates have not yet been computed.

Physical insights into uranyl diffusion and sorption in bentonite: Theoretical and molecular dynamics study

Mechanistic understanding of diffusion and sorption of radionuclides and metals in clay-based engineered barriers is essential to develop models and define parameters for transport calculations for the safety analysis of disposal systems. Here we studied diffusion of uranyl (UO22+) species in the clay interparticle pore or macropores of bentonite clay by means of molecular dynamics simulation (MDS) for pore sizes ranging from 8.37 to 33.5 nm. The conceptual model of the clay pore system considered diffusion as a combination of pore diffusion (Dp) and surface diffusion DS (i.e. diffusion of adsorbed cations within the electrical double layer of the clay surfaces), from which the apparent diffusion Da was calculated as the weighted sum of Dp and DS, using a weighing factor f calculated as the ratio of adsorbed to total UO22+ in the system. Diffusivities at equilibrium for the largest pore size of 33.5 nm were: Da=7.37×10−10 m2 s−1, Dp=1.14×10−9 m2 s−1, and Ds=1.97×10−13 m2 s−1. The Ds was several orders of magnitude smaller than Dp. This was evident from the much smaller gradient of the mean-square displacement vs time lag curve for the adsorbed species than that of the species in the pore space. We found a remarkable consistency between our theoretical derivation and independent MDS evidence. For the slit-shaped interparticle pore, the retardation factor Rf was found to be the reciprocal of the unabsorbed fraction (Rf=1/1−f) and the capacity factor α was a ratio of the porosity to the unadsorbed fraction (α=ε1−f) or the ratio of the diffusant density in the bulk sample to the corresponding density in the pore solution. MD simulations of diffusion and sorption processes can be applied to other transport related problems at continuum scale, pore scale and molecular scale, such as for improved modelling of global elemental cycles, CO2 geosequestration, or the performance of desalination membranes.

A modified local thermal non-equilibrium model of transient phase-change transpiration cooling for hypersonic thermal protection

Aiming to efficiently simulate the transient process of transpiration cooling with phase change and reveal the convection mechanism between fluid and porous media particles in a continuum scale, a new two-phase mixture model is developed by incorporating the local thermal non-equilibrium effect. Considering the low-pressure and high overload working conditions of hypersonic flying, the heat and mass transfer induced by capillary and inertial body forces are analyzed for sub-cooled, saturated and super-heated states of water coolant under varying saturation pressures. After the validation of the model, transient simulations for different external factors, including spatially-varied heat flux, coolant mass flux, time-dependent external pressure and aircraft acceleration are conducted. The results show that the vapor blockage patterns at the outlet are highly dependent on the injection mass flux value and the external pressure, and the reduced saturation temperature at low external pressure leads to early boiling off and vapor blockage. The motion of flying has a large influence on the cooling effect, as the inertial force could change the flow pattern of the fluid inside significantly. The comparison of the results from 2-D and 3-D simulations suggests that 3-D simulation shall be conducted for practical application of transpiration cooling, as the thermal protection efficiency may be overestimated by the 2-D results due to the assumption of an infinite width length of the porous plate.

The discrete and continuum behaviour of railway ballast

The mechanics of coarse-grained geomaterials have traditionally been examined from a continuum mechanics standpoint, but this has led to ever more complex constitutive models as an increasing number of novel aspects of behaviour are investigated. For this reason, there is a tendency to move towards discrete approaches. Such approaches require accurate definition and modelling of the particle shapes, for which considerable progress has been made, and also the contact mechanics between particles, about which little is known. For very coarse materials such as railway ballast, our understanding at the continuum scale has been hampered further by the technical difficulties in the laboratory testing so that the very small strain behaviour has been difficult to define with accuracy. New apparatus and techniques will be described to test ballast at both the continuum and particulate scales. These allow the small strain stiffness to be defined with accuracy in triaxial tests and to carry out precise particle-to-particle contact tests. At the particle contact scale, the behaviour is dominated by the roughness of the particles and their relatively sharp contacts, so that plasticity and particle wear predominate, which both change the contact properties significantly. It is the contact plasticity that then controls the decay in continuum stiffness with strain. The work emphasises the inadequacy of using simple linear and/or elastic DEM models calibrated from macro-scale tests rather than deriving the correct contact behaviour directly.

Advancing environmental monitoring across the water continuum combining biomarker analysis in multiple sentinel species: A case study in the Seine-Normandie Basin (France)

Nowadays, biomarkers are recognized as valuable tools to complement chemical and ecological assessments in biomonitoring programs. They provide insights into the effects of contaminant exposures on individuals and establish connections between environmental pressure and biological response at higher levels. In the last decade, strong improvements in the design of experimental protocols and the result interpretation facilitated the use of biomarker across wide geographical areas, including aquatic continua. Notably, the statistical establishment of reference values and thresholds enabled the discrimination of contamination effects in environmental conditions, allowed interspecies comparisons, and eliminated the need of a reference site.The aim of this work was to study freshwater-estuarine-coastal water continua by applying biomarker measurements in multi-species caged organisms. During two campaigns, eight sentinel species, encompassing fish, mollusks, and crustaceans, were deployed to cover 25 sites from rivers to the sea. As much as possible, a common methodology was employed for biomarker measurements (DNA damage and phagocytosis efficiency) and data interpretation based on guidelines established using reference values and induction/inhibition thresholds (establishment of three effect levels).The methodology was successfully implemented and allowed us to assess the environmental quality. Employing multiple species per site enhances confidence in observed trends. The results highlight the feasibility of integrating biomarker-based environmental monitoring programs across a continuum scale. Biomarker results align with Water Framework Directive indicators in cases of poor site quality. Additionally, when discrepancies arise between chemical and ecological statuses, biomarker findings offer a comprehensive perspective to elucidate the disparities. Presented as a pilot project, this work contributes to gain insights into current biomonitoring needs, providing new questions and perspectives.

Comparison of the Prediction of the Temperature Profile in an Ohmic Reactor on Different Modeling Scales

AbstractTo predict the temperature profile in an ohmic reactor, it is essential to know the thermal and electrical conductivity of the reactor geometry. Those properties can be considered on different modeling scales: On the detailed (resolved) scale, the reactor consists of a packed bed structure, where the properties of each substance are considered. On the effective (continuum) scale, the packed bed is considered as effective medium with composite properties. In this contribution, we consider both scales and compare the results. Based on the detailed description with a resolved microstructure, the bed's effective thermal and electrical conductivity are computed. These properties are compared with analytical formulas. The electrical conductivity is the basis for the electrical field and the current density. Finally, these properties are used to evaluate the ohmic heating of the packed bed exposed to flow and to compute the temperature distribution within the reactor.

A data-driven multiscale model for reactive wetting simulations

We describe a data-driven, multiscale technique to model reactive wetting of a silver–aluminum alloy on a Kovar™ (Fe-Ni-Co alloy) surface. We employ molecular dynamics simulations to elucidate the dependence of surface tension and wetting angle on the drop’s composition and temperature. A design of computational experiments is used to efficiently generate training data of surface tension and wetting angle from a limited number of molecular dynamics simulations. The simulation results are used to parameterize models of the material’s wetting properties and compute the uncertainty in the models due to limited data. The data-driven models are incorporated into an engineering-scale (continuum) model of a silver–aluminum sessile drop on a Kovar™ substrate. Model predictions of the wetting angle are compared with experiments of pure silver spreading on Kovar™ to quantify the model-form errors introduced by the limited training data versus the simplifications inherent in the molecular dynamics simulations. The paper presents innovations in the determination of “convergence” of noisy MD simulations before they are used to extract the wetting angle and surface tension, and the construction of their models which approximate physio-chemical processes that are left unresolved by the engineering-scale model. Together, these constitute a multiscale approach that integrates molecular-scale information into continuum scale models.

Analysis of shear shock waves in soft materials: From periodic elastic laminates and fibre-reinforced composites to molecular chain networks

We investigate the effect of microstructure and molecular length-scale structures on the formation of shear shock waves in soft materials. We consider (i) soft materials with layered microstructures, (ii) transversely isotropic fibre-reinforced composites (FC), as well as (iii) molecular chain networks, using homogenised energy density functions at the continuum scale. Critical conditions for the formation of shear shocks are found analytically for laminates and FCs, and are shown to depend only on the angle between the initial orientation direction and the applied load. We elucidate the effects of the microstructural material parameters on the shock formation distance. Our results show that increased stiffness ratio and volume fraction of fibres decreases the shock formation distance. The analysis of molecular chain networks indicates that an increase in the entanglement increases the critical shock formation distance. We also highlight that by an appropriate choice of loading and material parameters, shock formation can be avoided, providing guidance for design of protective materials and structures.

From clusters of moving molecules to continua: Material elements as open systems

We discuss the discrete-to-continuum transition in the description of matter, starting from a cluster of flowing molecules with equal mass and ending up with a non-simple fluid. We account for the fluctuations beyond a local affine approximation of the velocity distribution of molecules within a space window adopted to compute some prominent statistics. The resulting continuum picture accounts for local mass variation in each space window corresponding to a point in the continuum scale. From a statistical viewpoint, every material element is thus considered as a grand-canonical ensemble. So-called C-derivatives account for macroscopic-to-mesoscopic relative motion. When considered for second-rank tensors, they extend Truesdell’s derivative and reduce to Oldroyd’s one when the macroscopic-to-mesoscopic relative motion vanishes. Fluctuations beyond an affine component best approximating the kinetic energy are summarized into a second-rank symmetric tensor whose time variation enters a balance equation governing transfer from velocity fluctuations to heat. Eventually, we discuss essential elements of thermodynamics in the present setting. What emerges is the possibility of a non-Fourier type heat transfer. The results address computational schemes for field representations of sparse phase dynamics, such as granular materials, and the one of bodies with transport of scattered molecules, such as pollutants in fluids or proteins in biological tissues.

The Mental Health Toll: Medical Trainees Living with Disabilities during the COVID-19 Pandemic

Objectives. Throughout the world, medical trainees have experienced psychological distress during the COVID-19 pandemic due to substantial changes in their educational programs and COVID-19 patient care. When medical trainees live with a disability, their psychological distress may be exacerbated. This study aimed to explore how having a disability may be associated with an additional emotional toll for medical trainees during the COVID-19 pandemic. Methods. Participants in the study were 201 medical trainees (62 interns and 138 residents) and 147 medical attending physicians in various fields of medicine. Participants completed an online survey including the Fear of COVID-19 scale, the Depression Anxiety and Stress Scale, and the Mental Health Continuum Scale measuring aspects of wellbeing, including emotional wellbeing, belonging, and sense of psychological meaning. Results. Disabled participants experienced higher levels of fear of COVID-19, depression, anxiety, stress, and lower levels of emotional wellbeing, sense of belonging, and psychological meaning compared to participants with no disabilities. Residents generally experienced higher stress levels and lower wellbeing levels than attendings. Residents living with disabilities were more prone to experience stress and fear of COVID-19, and residents and interns living with disabilities experienced higher levels of depression, anxiety, and stress compared to their peers who live without disabilities and compared to attendings living with disabilities. Conclusions. Medical trainees living with disabilities were more prone to experience high levels of psychological distress and lower levels of wellbeing during the COVID-19 pandemic compared to their peers without disabilities. Therefore, there is a need to address this emotional toll and provide support in medical education programs promoting trainees’ wellbeing, sense of belonging, and psychological meaning.

Temporal Evolution of Solute Dispersion in Three‐Dimensional Porous Rocks

AbstractWe study the temporal evolution of solute dispersion in three‐dimensional porous rocks of different heterogeneity and pore structure. To this end, we perform direct numerical simulations of pore‐scale flow and transport in a sand pack, which exhibits mild heterogeneity, and a Berea sandstone, which is characterized by strong heterogeneity as measured by the variance of the logarithm of the flow velocity. The impact of medium structure and pore‐scale mass transfer mechanisms is probed by effective and ensemble dispersion coefficients. The former is a measure for the typical width of a plume, while the latter for the deformation, that is, the spread of a mixing front. Both dispersion coefficients evolve from the molecular diffusion coefficients toward a common finite asymptotic value. Their behavior is governed by the interplay between diffusion, pore‐scale velocity fluctuations and medium structure, which determine the characteristic mass transfer time scales. We find distinctly different dispersion behaviors in the two media, which can be traced back to how particles sample pore‐scale velocity variability and how this depends on the medium structure. These are key elements for the upscaling of transport, mixing and reaction from the pore to the continuum scale.

Investigation of REV scale and anisotropy for 2D permeable fracture Networks: The role of geological entropy

To investigate the intrinsic association between geometrical properties and permeability of anisotropic fractured media, a methodology of geological entropy is applied to anisotropic fracture networks for the evaluation of seepage fields. By integrating the synthetic effect of fracture geometrical parameters (e.g., trace length, spacing, dip angle, and aperture), the global connectivity of fracture networks is quantified by the entropy scale (Hs), while the directional entropy scale (Hs,α) is used to characterize the local geometrical anisotropy in arbitrary orientations. A series of hydraulic representative elementary volumes (REVs) of fracture patterns with various geometrical properties are acquired based on continuum analysis. The permeability in the continuum scale is obtained from steady-state flow simulations. Sensitivity analyses are performed to understand the geometrical dependence of permeability parameters regarding entropy indices. It is found that a systematic increase in trace length, spacing, and dip angle is correlated with an increase, decrease, and equilibrium in entropy, respectively, which corresponds to a change in hydraulic REV sizes that can be expressed as a power-law function related to the Hs. Moreover, Hs,α can well explain the permeability anisotropy resulting from the spatial order of fracture networks, and a unified mathematical relationship for the effective permeability coefficients in arbitrary orientations versus the Hs,α is proposed, independent of variations in fracture patterns and scales. The results indicate that geological entropy, related to the geometrical properties and spatial distribution of fractures, is appropriate to characterize the permeability of anisotropic systems.

Exascale Computational Fluid Dynamics in Heterogeneous Systems

Abstract Exascale computing has extended the reach of resolved flow simulations in complex, heterogeneous systems far beyond conventional computational fluid dynamics capabilities. As a result, unprecedented pore and microscale resolution have been achieved in domains that have been traditionally modeled by, and limited to, continuum, effective medium approaches. By making use of computational resources on the new exascale supercomputer, Frontier, at the Oak Ridge Leadership Computing Facility, we performed flow simulations that have pushed the limits of domain-to-resolution ratios by several orders of magnitude for heterogeneous media. Our approach is an incompressible, Navier–Stokes CFD solver based on adaptive, embedded boundary (EB) methods supported by the Chombo software framework for applied partial differential equations (PDEs). The computational workhorse in the CFD application code is an elliptic solver framework in Chombo for pressure-Poisson and viscous, Helmholtz terms that leverages a PETSc-hypre software interface tuned for accelerator-based platforms. We demonstrate scalability of the approach by replicating a unit cylinder packed with microspheres to achieve over 400 × 109 degrees-of-freedom simulated. These simulations model domain lengths of over 20 meters with channel volumes of over 400 cm3 and containing millions of packed spheres with 20 micron grid resolution, challenging current understanding of what it means to be a representative elementary volume (REV) of the continuum scale in heterogeneous media. We also simulate a range of Reynolds numbers to demonstrate wide applicability and robustness of the approach.

Simulations of CO2 Dissolution in Porous Media Using the Volume-of-Fluid Method

Traditional investigations of fluid flow in porous media often rely on a continuum approach, but this method has limitations as it does not account for microscale details. However, recent progress in imaging technology allows us to visualize structures within the porous medium directly. This capability provides a means to confirm and validate continuum relationships. In this study, we present a detailed analysis of the dissolution trapping dynamics that take place when supercritical CO2 (scCO2) is injected into a heterogeneous porous medium saturated with brine. We present simulations based on the volume-of-fluid (VOF) method to model the combined behavior of two-phase fluid flow and mass transfer at the pore scale. These simulations are designed to capture the dynamic dissolution of scCO2 in a brine solution. Based on our simulation results, we have revised the Sherwood correlations: We expanded the correlation between Sherwood and Peclet numbers, revealing how the mobility ratio affects the equation. The expanded correlation gave improved correlations built on the underlying displacement patterns at different mobility ratios. Further, we analyzed the relationship between the Sherwood number, which is based on the Reynolds number, and the Schmidt number. Our regression on free parameters yielded constants similar to those previously reported. Our mass transfer model was compared to experimental models in the literature, showing good agreement for interfacial mass transfer of CO2 into water. The results of this study provide new perspectives on the application of non-dimensional numbers in large-scale (field-scale) applications, with implications for continuum scale modeling, e.g., in the field of geological storage of CO2 in saline aquifers.

A continuum scale chemo-mechanical model for multi-trap hydrogen transport in deformed polycrystalline metals

This study presents a coupled multi-trap hydrogen diffusion and crystal plasticity model within a thermodynamically consistent framework. The developed modeling scheme incorporates the hydrogen-enhanced localized plasticity (HELP) and hydrogen-enhanced strain-induced plasticity (HESIV) based on thermodynamic considerations. The theoretical formulations are implemented in the finite element method, which considers the concentration- and chemical potential-based balance equations. The validity of the coupled model is established through preliminary single element simulations under isothermal conditions, showcasing the predictability of evolution of hydrogen concentration and occupancies in the deformed microstructure of polycrystalline metal. Then, the developed computational approach is applied to two materials exhibiting hydrogen-induced hardening and softening behaviors in accordance with the HELP mechanism and vacancy-hydrogen complex (VaH) formation under isothermal condition. The model successfully reproduces the change of mechanical behavior induced by hydrogen in both materials. The effects of hydrogen diffusivity and the binding energy of defects on hydrogen transport are also investigated. Furthermore, the sensitivity of hydrogen diffusion to different trapping mechanisms, local equilibrium trapping and kinetics trapping, is examined. The proposed modeling framework can be applied to new material design strategies for developing metals resistant to hydrogen embrittlement.

A multiscale FEM-MD coupling method for investigation into atomistic-scale deformation mechanisms of nanocrystalline metals under continuum-scale deformation

This study aims to develop a multiscale bridging method for investigating nanocrystalline metals based on macro-scale deformation. For this purpose, we propose a hierarchical multiscale computational method that can focus on some of the elements in a finite element model for scale bridging to atomistic-scale models. This method assumes that atomistic-scale nanocrystalline models are related to the integration points in a finite element and deform based on the macro-scale deformation. Nanocrystalline aluminum was chosen for the validation of the multiscale method. The finite element method (FEM) and the molecular dynamics (MD) method were used for continuum-scale and atomistic-scale simulations, respectively. We utilized the notion of the CauchyBorn rule (CBR) for communicating deformation information from the continuum scale to the atomistic scale. We studied three different cases with two nanocrystalline models and two loading cases to compare differences resulting from crystal structures and loading. Based on the crystal structure change during relaxation, nonequilibrium grain boundaries (NEGBs) were shown to play a role as deformation mechanisms in the plastic regime and induce the onset and migration of crystal defects, including deformation twins, as reported in the experiment. Furthermore, the crystal orientation dependence of the onset of crystal defects was confirmed by the comparison of the results from the two different nanocrystalline models. The qualitative agreement of the results with experimental observations is also confirmed. The proposed ‘FEM-MD’ method can bridge a large-scale gap, for example, from a nano-scale to a continuum-scale such that an MD model can be coupled to a millimeter or centimeter scale compared to other embedding methods. The present method is ideal for investigating the dislocation behavior of nanocrystalline materials, which contain multi-grained nanostructure at finite temperature, undergoing various loading scenarios at the macro-scale.

High-throughput single-cell assay for precise measurement of the intrinsic mechanical properties and shape characteristics of red blood cells.

The intrinsic physical and mechanical properties of red blood cells (RBCs), including their geometric and rheological characteristics, can undergo changes in various circulatory and metabolic diseases. However, clinical diagnosis using RBC biophysical phenotypes remains impractical due to the unique biconcave shape, remarkable deformability, and high heterogeneity within different subpopulations. Here, we combine the hydrodynamic mechanisms of fluid-cell interactions in micro circular tubes with a machine learning method to develop a relatively high-throughput microfluidic technology that can accurately measure the shear modulus of the membrane, viscosity, surface area, and volume of individual RBCs. The present method can detect the subtle changes of mechanical properties in various RBC components at continuum scales in response to different doses of cytoskeletal drugs. We also investigate the correlation between glycosylated hemoglobin and RBC mechanical properties. Our study develops a methodology that combines microfluidic technology and machine learning to explore the material properties of cells based on fluid-cell interactions. This approach holds promise in offering novel label-free single-cell-assay-based biophysical markers for RBCs, thereby enhancing the potential for more robust disease diagnosis.

Satisfaction of basic needs mediates relationships between incremental mindsets and well-being.

Research on the extent to which people believe that people can change (incremental beliefs) suggests that incrementalist beliefs are positively related to well-being, whereas entity beliefs (people cannot change) are not. One explanation for this relationship is that incremental beliefs are associated with a mastery orientation, whereas entity beliefs are not. If this is the case, then autonomous and competence motives should mediate relationships between incrementalism and well-being because these motives reflect different aspects of mastery. The present study examined the possibility that autonomous and competence motives mediate relationships between self-theories and well-being. Participants were adult community members (n = 428) who completed the Life Engagement Test (eudaimonic well-being), the Satisfaction with life Scale (hedonic well-being), the Mental Health Continuum Scale (eudaimonic, subjective, and psychological well-being), the Basic Needs Satisfaction scale (autonomy, competence, relatedness), and a measure of implicit theories of the self (incremental and entity beliefs). Regression analyses found that incremental beliefs were significantly related (positively) to all three measures of well-being, whereas entity beliefs were not significantly related to well-being. Regression analyses also found that incremental beliefs were positively related to satisfaction of autonomy and competence needs but were not related to satisfaction of relatedness needs. Entity beliefs were not related to the satisfaction of any of the three basic needs. A series of mediational analyses found that competence and autonomy motives mediated relationships between incremental beliefs and all three measures of well-being. In all but one case, satisfaction with life, the direct effects of incremental beliefs on well-being were rendered non-significant when satisfaction of autonomy and competence needs were included as mediators. The present results confirm and extend to the general domain the supposition that a mastery orientation is responsible for relationships between well-being and incremental theories of the self. They also conform the importance of the tenants of Self-Determination Theory in understanding self-theories.

(Invited) Multiscale Simulations of Materials Degradation in Hydrogen Production and Storage Applications

Most hydrogen production and storage technologies rely on controlled chemical or electrochemical reactions occurring at complex interfaces. However, under actual operating conditions, competing mechanisms of chemistry, transport, and phase evolution can activate other processes that compete with or deactivate the desired processes. In certain cases, such mechanisms can lead to critical degradation of materials and their performance. In this talk, I will discuss how multiscale, multiphysics materials modeling from atomistic to continuum scales is being applied to understand fundamentals of degradation in materials relevant to hydrogen technology. Topics will include modeling of competing reaction pathways for hydrogen-rich chemicals, secondary phase formation in high-temperature hydrogen environments, impeded transport pathways in metals for hydrogen storage, and corrosion and oxidation of secondary components and contacts. In each case, I will show how HPC-accelerated models are being integrated across scales and interfaced with microscopy and spectroscopy, as well as modern data science approaches, to gain new physicochemical understanding and guide efforts towards improvement. Examples will be drawn from current efforts within the DOE HydroGEN, HyMARC, and H2NEW hydrogen production and storage multi-laboratory consortia, as well as closely related activities within the Corrosion Science Strategic Initiative at Lawrence Livermore National Laboratory. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.

Modelling Interfaces for Solid Electrolytes

All-solid-state batteries (ASSBs) are candidates for the next-generation of battery electric vehicles. They potentially enable the use of lithium metal as an anode material thereby highly improving the energy density of the battery. Among the most promising candidates for solid electrolytes are polycrystalline materials such as LLZO, due to their high ionic conductivity and chemical stability. Lithium dendrites form above a critical current density (CDC) of as low as 0.6 mA/cm² [1], however. While some explanations where suggested, the underlying mechanisms are not yet understood. In a recent paper a more viable CDC of 5 mA/cm² was reported, which was achieved by protonating the interfaces and grain boundaries [2], this shows that understanding both external and internal interfaces is crucial for the successful development of ASSBs.One often used tool in battery analysis is Electrochemical Impedance Spectroscopy (EIS). We developed a continuum scale model [3] in order to compare experimental impedance data with simulated impedances for a range of possible interface configurations. Space charge layers and their effects are resolved in the model and material properties are informed by atomistic simulations.In our contribution we simulate impedances at ASSB internal and external interfaces. The comparison to experiment helps us validate the model while better understanding the effect that different interface configurations have on resistance and capacitance. The gained understanding can inform the development and manufacturing of future ASSBs. Acknowledgements This work contributes to the research performed at CELEST (Center for Electrochemical Energy Storage Ulm-Karlsruhe). The authors thank the German Ministry of Education and Research (BMBF) for funding of the project CatSE II under grant number 03XP0223E. Han, F., Westover, A. S. et al. Nature Energy 2019, 4(3), 187-196. DOI: 1038/s41560-018-0312-zKim, S., Kim, J. S. et al. Nature Commun 2022, 13(1), 1-12. DOI: 10.1038/s41467-022-29531-xBecker-Steinberger, K., Schardt, S. et al. arXiv 2021 DOI: 10.48550/arXiv.2101.10294