Accurate characterization of the mechanical properties of the human brain at both microscopic and macroscopic length scales is a critical requirement for modeling of traumatic brain injury and brain folding. To date, most experimental studies that employ classical tension/compression/shear tests report the mechanical properties of the brain averaged over both the gray and white matter within the macroscopic regions of interest. As a result, there is a missing correlation between the independent mechanical properties of the microscopic constituent elements and the composite bulk macroscopic mechanical properties of the tissue. This microstructural computational study aims to inversely predict the hyperelastic mechanical properties of the axonal fibers and their surrounding extracellular matrix (ECM) from the bulk tissue's mechanical properties. We develop a representative volume element (RVE) model of the bulk tissue consisting of axonal fibers and ECM with the embedded element technique. A multiobjective optimization technique is implemented to calibrate the model and establish the independent mechanical properties of axonal fibers and ECM based on seven previously reported experimental mechanical tests for bulk white matter tissue from the corpus callosum. The result of the study shows that the discrepancy between the reported values for the elastic behavior of white matter in literature stems from the anisotropy of the tissue at the microscale. The shear modulus of the axonal fiber is seven times larger than the ECM, with axonal fibers that also show greater nonlinearity, contrary to the common assumption that both components exhibit identical nonlinear characteristics.
Statement of significance
The reported mechanical properties of white matter microstructure used in traumatic brain injury or brain mechanics studies vary widely, in some cases by up to two orders of magnitude. Currently, the material parameters of the white matter microstructure are identified by a single loading mode or ultimately two modes of the bulk tissue. The presented material models only define the response of the bulk and homogenized white matter at a macroscopic scale and cannot explicitly capture the connection between the material properties of microstructure and bulk structure. To fill this knowledge gap, our study characterizes the hyperelastic material properties of axonal fibers and ECM using microscale computational modeling and multiobjective optimization. The hyperelastic material properties for axonal fibers and ECM presented in this study are more accurate than previously proposed because they have been optimized using seven or six loading modes of the bulk tissue, which were previously limited to only two of the seven possible loading modes. As such, the predicted values with high accuracy could be used in various computational modeling studies. The systematic characterization of the material properties of the human brain tissue at both macro- and microscales will lead to more accurate computational predictions, which will enable a better understanding of injury criteria, and has a positive impact on the improved development of smart protection systems, and more accurate prediction of brain development and disease progression.
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Multiscale geometry and mechanics of lipid monolayer collapse
Langmuir monolayers at gas/liquid interfaces provide a rich framework to investigate the interplay between multiscale geometry and mechanics. Monolayer collapse is investigated at a topological and geometric level by building a scale spaceM from experimental imaging data. We present a general lipid monolayer collapse phase diagram, which shows that wrinkling, folding, crumpling, shear banding, and vesiculation are a continuous set of mechanical states that can be approached by either tuning monolayer composition or temperature. The origin of the different mechanical states can be understood by investigating the monolayer geometry at two scales: fluorescent vs atomic force microscopy imaging. We show that an interesting switch in continuity occurs in passing between the two scales, CAFM MAFM 6¼ CFM M. Studying the difference between monolayers that fold vs shear band, we show that shear banding is correlated to the persistence of a multi-length scale microstructure within the monolayer at all surface pressures. A detailed analytical geometric formalism to describe this microstructure is developed using the theory of structured deformations. Lastly, we provide the first ever finite element simulation of lipid monolayer collapse utilizing a direct mapping from the experimental image spaceM into a simulation domain P. We show that elastic dissipation in the form of bielasticity is a necessary and sufficient condition to
capture loss of in-plane stability and shear banding.
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- Award ID(s):
- 1950525
- NSF-PAR ID:
- 10333223
- Date Published:
- Journal Name:
- Current topics in membranes
- Volume:
- 87
- ISSN:
- 1063-5823
- Page Range / eLocation ID:
- 1-45
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1016/bs.ctm.2021.08.003
