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Multilayer polymer films are extensively used in multiphase separation. Electrospray deposition (ESD) is an important technique for fabricating such films with tunable morphology. Viscoelastic properties of polystyrene (PS) nanoshell coatings produced by ESD on gold and spin‐coated PS surfaces are evaluated using Quartz Crystal Microbalance with Dissipation (QCM‐D). The thickness of PS films on gold increases with flow rate from ∼200 nm at 0.5 to ∼400 nm at 1.5 mL h^−1, accompanied by an order‐of‐magnitude increase in dissipation due to larger particle sizes from shorter droplet flight times. This effect is absent on spin–coated PS films, suggesting the onset of the self‐limiting effect of charges. Although the shear moduli for ESD films calculated from Voigt models is only 0.08%–0.20% of the bulk PS modulus, the stiffness ratio of spray‐coated PS to a single shell is (5.00–13.3) × 10^3  m^−1, due to shell–shell and shell–substrate interactions. These are novel results related to the interparticle friction obtained using QCM‐D for the first time. This work demonstrates  that mechanical properties of particulate viscoelastic films with potential applications in high surface area sensors, such as size‐selective membranes for protein or electrolyte adsorption, can be evaluated by QCM‐D with nanograms of material. 

Abstract A novel finite element method (FEM) is developed to study mechanical response of axons embedded in extra cellular matrix (ECM) when subjected to harmonic uniaxial stretch under purely non-affine kinematic boundary conditions. The proposed modeling approach combines hyper-elastic (such as Ogden model) and time/frequency domain viscoelastic constitutive models to evaluate the effect of parametrically varying oligodendrocyte-axon tethering under harmonic stretch at 50Hz. A hybrid hyper-viscoelastic material (HVE) model enabled the analysis of repeated uniaxial load on stress propagation and damage accumulation in white matter. In the proposed FEM, oligodendrocyte connections to axons are depicted via a spring-dashpot model. This tethering technique facilitates contact definition at various locations, parameterizes connection points and varies stiffness of connection hubs. Results from a home-grown FE submodel configuration of a single oligodendrocyte tethered to axons at various locations are presented. Root mean square deviation (RMSD) are computed between stress-strain plots to depict trends in mechanical response. Steady-state dynamic (SSD) simulations show stress relaxation in axons. Gradual axonal softening under repetitive loads is illustrated employing Prony series - HVE models. Representative von-Mises stress plots indicate that undulated axons experience bending stresses along their tortuous path, suggesting greater susceptibility to damage accumulation and fatigue failure due to repeated strains. 

Abstract White matter (WM) characterization is challenging due to its anisotropic and inhomogeneous microstructure that necessitates multiscale and multi-modality measurements. Shear elastography is one such modality that requires the accurate interpretation of 3D shear strain measurements, which hinge on developing appropriate constitutive tissue models. Finite element methods enable the development of such models by simulating the shear response of representative elemental volumes (REV). We have developed triphasic (axon, myelin, glia), 2D REVs to simulate the influence of the intrinsic viscoelastic property and volume fraction of each phase. This work constitutes the extension of 2D- to 3D-REVs, focusing on the effect of the intrinsic material properties and their 3D representation on the viscoelastic response of the tissue. By lumping the axon and myelin phases, a flexible 3D REV generation and analysis routine is then developed to allow for shear homogenization in both the axial and transverse directions. The 2D and 3D models agree on stress distribution and total deformation when 2D cross-sectional snapshots are compared. We also conclude that the ratio of transverse to axial transverse modulus is larger than one when axon fibers are stiffer than the glial phase. 

Abstract Numerical simulations using non-linear hyper-elastic material models to describe interactions between brain white matter (axons and extra cellular matrix (ECM)) have enabled high-fidelity characterization of stress-strain response. In this paper, a novel finite element model (FEM) has been developed to study mechanical response of axons embedded in ECM when subjected to tensile loads under purely non-affine kinematic boundary conditions. FEM leveraging Ogden hyper-elastic material model is deployed to understand impact of parametrically varying oligodendrocyte-axon tethering and analyze influence of aging material characteristics on stress propagation. In proposed FEM, oligodendrocyte connections to axons are represented via spring-dashpot model, such tethering technique facilitates contact definition at various locations, parameterize connection points and vary stiffness of connection hubs. Two FE submodels are discussed: 1) multiple oligodendrocytes arbitrarily tethered to the nearest axons, and 2) single oligodendrocyte tethered to all axons at various locations. Root mean square deviation (RMSD) were computed between stress-strain plots to depict trends in mechanical response. Axonal stiffness was found to rise with increasing tethering, indicating role of oligodendrocytes in stress redistribution. Finally, stress state results for aging axon material, with varying stiffnesses and number of connections in FEM ensemble have also been discussed to demonstrate gradual softening of tissues. 

Material properties of brain white matter (BWM) show high anisotropy due to the complicated internal three-dimensional microstructure and variant interaction between heterogeneous brain-tissue (axon, myelin, and glia). From our previous study, finite element methods were used to merge micro-scale Representative Volume Elements (RVE) with orthotropic frequency domain viscoelasticity to an integral macro-scale BWM. Quantification of the micro-scale RVE with anisotropic frequency domain viscoelasticity is the core challenge in this study. The RVE behavior is expressed by a viscoelastic constitutive material model, in which the frequency-related viscoelastic properties are imparted as storage modulus and loss modulus for the composite comprised of axonal fibers and extracellular glia. Using finite elements to build RVEs with anisotropic frequency domain viscoelastic material properties is computationally very consuming and resource-draining. Additionally, it is very challenging to build every single RVE using finite elements since the architecture of each RVE is arbitrary in an infinite data set. The architecture information encoded in the voxelized location is employed as input data and is consequently incorporated into a deep 3D convolution neural network (CNN) model that cross-references the RVEs’ material properties (output data). The output data (RVEs’ material properties) is calculated in parallel using an in-house developed finite element method, which models RVE samples of axon-myelin-glia composites. This novel combination of the CNN-RVE method achieved a dramatic reduction in the computation time compared with directly using finite element methods currently present in the literature.