Multiscale computational modelling
Most materials systems, including soft biological tissues, owe their macroscopic properties to their organization at smaller length scales. In order to understand the origin of these properties on the one hand, but also towards tailoring them for desired applications, multi-scale mechanical analyses and models are therefore indispensable. Based on microscopy and image analysis, we generate computational models that reproduce key features of the "micro"-structures of these materials as a starting point for such analyses, and use computational homogenization methods to determine their macroscopic response through numerical simulation.
In soft biological tissues, the cross-linked network of collagen fibrils, fibers and bundles is one of the dominating microstructures that furnishes these tissues with extraordinary characteristics. Special kinematic features such as large Poisson's ratios [1,2] and negative compressibility [3] exemplify this. To rationalize such behavior, we have generated 2 and 3-dimensional discrete network models [4,5] of these fiber networks, and recently, considered their interaction with the osmotically active ground matrix that is key for tissue hydration [3]. Refined models have been used to study the presence of defects in the collagen networks [4,6,7], and could thus shed light on the outstanding fracture mechanics properties of soft biological tissues. Many tissues possess further levels of structural hierarchy which once again lead to particular characteristics at the macroscale. For example, based on histological information and custom image analysis we have developed 3D computational models of the skeletal muscle microstructure to analyze the special asymmetric behavior of this tissue under tension and compression [8-10].
Electrospun membranes represent another class of fiber network materials, and are deemed great potential in biomedical engineering due to increased mechanical biocompatibility [11-13] and since the fiber mats can be generated from various biopolymers and with fiber diameters and pore sizes suitable to serve as scaffold materials for cells. Towards a better understanding of their multiscale mechanics we have generated computational models of these beam-like networks [14,15], and together with collaborators, we informed and validated them through cutting edge microscopy techniques [16,17]. By means of these models, we could rationalize the auxetic behavior displayed by some electrospun membranes, which leads to extreme volume gain under tensile loads [18].
Multiscale modeling also plays an important role in our group's mechanobiological research, since it allows studying in silico the relation between tissue scale loads and cell-scale forces and displacements. This transfer of loads and deformations across the length scales is a key factor for mechanotransduction, and we have created computational models to study the interaction of cells with both native collagenous tissues [19,20] and biomedical fibrous materials [21,22]. We are currently extending these methods to address the mechanics of the intracellular networks of endothelial cell layers, consisting of actin, intermediate filaments and microtubuli.
[1] Buerzle, W., & Mazza, E. (2013) On the deformation behavior of human amnion. J. Biomech. 46, 1777-1783. DOI: 10.1016/j.jbiomech.2013.05.018
[2] Ehret A.E., Bircher K., Stracuzzi A., Marina V., Zundel M., Mazza E. (2017) Inverse poroelasticity as a fundamental mechanism in biomechanics and mechanobiology. Nat. Commun. 8, 1002. DOI: 10.1038/s41467-017-00801-3
[3] Mauri A., Perrini, M., Ehret, A.E., De Focatiis, D.S.A., & Mazza, E. (2015) Time-dependent mechanical behavior of human amnion: macroscopic and microscopic characterization. Acta Biomater.11, 314-323. DOI: 10.1016/j.actbio.2014.09.012
[4] Mauri A., Hopf R., Ehret A.E., Picu C.R., Mazza, E. (2016) A discrete network model to represent the deformation behavior of human amnion. J. Mech. Behav. Biomed. Mater. 58, 45-56. DOI: 10.1016/j.jmbbm.2015.11.009
[5] Bircher K., Ehret A.E., Mazza E. (2017) Microstructure based prediction of the deformation behavior of soft collagenous membranes. Soft Matter 13, 5107-5116. DOI: 10.1039/c7sm00101k
[6] Bircher K., Zündel M., Pensalfini M., Ehret A.E., Mazza E. (2019) Tear resistance of soft collagenous tissues. Nat. Commun. 10, 792. DOI: 10.1038/s41467-019-08723-y
[7] Bircher K. Comparative Biomechanics: Analysis of the deformation and fracture behavior of soft collagenous tissues. ETH Diss. Nr. 26040 (2020).
[8] Kuravi R. Investigating the role of meso-scale structure on the mechanical response of skeletal muscle tissues. ETH Diss. Nr. 27212 (2021)
[9] Kuravi R., Leichsenring K., Böl M., Ehret A.E. (2021) 3D finite element models from serial section histology of skeletal muscle tissue – The role of micro-architecture on mechanical behaviour. J. Mech. Behav. Biomed. Mater. 113, 104109 (2021). DOI: 10.1016/j.jmbbm.2020.104109
[10] Kuravi R., Leichsenring K., Trostorf R., Morales-Orcajo E., Böl M., Ehret A.E. (2021) Predicting muscle tissue response from calibrated component models and histology-based finite element models. J. Mech. Behav. Biomed. Mater. 117, 104375. DOI: 10.1016/j.jmbbm.2021.104375
[11] Mazza E., Ehret A.E. (2015) Mechanical biocompatibility of highly deformable biomedical materials. J. Mech. Behav. Biomed. Mater. 48, 100-124. DOI: 10.1016/j.jmbbm.2015.03.023
[12] Hympánová L., Rynkevic R., Román S., Mori da Cunha M.G.M.C., Mazza E., Zündel M., Urbánková I., Gallego M.R., Vange J., Callewaert G., Chapple C., MacNeil S., Deprest, J. (2020) Assessment of electrospun and ultra-lightweight polypropylene meshes in the sheep model for vaginal surgery. Eur. Urol. Focus 6, 190-198. DOI: 10.1016/j.euf.2018.07.024
[13] Morel A., Guex A.G., Itel F., Domaschke S., Ehret A.E., Ferguson S.J., Fortunato G., Rossi R.M. (2021) Tailoring the multiscale architecture of electrospun membranes to promote 3D cellular infiltration. Mat. Sci. Eng. C 130, 112427. DOI: 10.1016/j.msec.2021.112427
[14] Zündel M., Mazza E., Ehret A.E. (2017) A 2.5D approach to the mechanics of electrospun fibre mats. Soft Matter, 13, 6407-6421. DOI: 10.1039/c7sm01241a
[15] Domaschke S., Zündel M., Mazza E., Ehret A.E. (2019) A 3D computational model of electrospun networks and its application to inform a reduced modelling approach, Int. J. Solids Struct. 158, 76-89. DOI: 10.1016/j.ijsolstr.2018.08.030
[16] Morel, A., Domaschke, S., Urundolil Kumaran, V., Alexeev, D., Sadeghpour, A., Ramakrishna, S. N., Ferguson S.J., Rossi R.M., Mazza E., Ehret A.E., Fortunato, G. (2018). Correlating diameter, mechanical and structural properties of poly (L-lactide) fibres from needleless electrospinning. Acta Biomater 81, 169-183. DOI: 10.1016/j.actbio.2018.09.055
[17] Domaschke S., Morel A., Kaufmann R., Hofmann J., Rossi R.M., Mazza E., Fortunato G., Ehret A.E. (2020) Predicting the macroscopic response of electrospun membranes based on microstructure and single fibre properties. J. Mech. Behav. Biomed. Mater. 104, 103634. DOI: 10.1016/j.jmbbm.2020.103634
[18] Domaschke S., Morel A., Fortunato G., Ehret A.E. (2019) Random auxetics from buckling fibre networks. Nat. Commun. 10, 4863. DOI: 10.1038/s41467-019-12757-7
[19] Stracuzzi A. Chemomechanical Interactions in Biomaterials: Multiphase and Multiscale Analyses. ETH Diss. Nr. 27113 (2021)
[20] Stracuzzi A., Britt B.R., Mazza E., Ehret A.E. (2022) Risky interpretations across the length scales: continuum vs. discrete models for soft tissue mechanobiology. Biomech. Model. Mechanobiol. DOI: 10.1007/s10237-021-01543-4
[21] Zündel M., Ehret A.E., Mazza E. (2019) The multiscale stiffness of electrospun substrates and aspects of their mechanical biocompatibility. Acta Biomater. 84, 146-158. DOI: 10.1016/j.actbio.2018.11.012
[22] Zündel M., Mechanical Interactions of Cells with Soft Synthetic Substrates: A Computational Analysis. ETH Diss. Nr. 25061 (2019)