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Mechanics of Biological Materials: A Theoretical and Computational Approach Using Machine Learning and Finite Element Analysis

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There are many important phenomena that are interdisciplinary between biology and mechanics. Mechanical factors such as force, stress, and strain generated within living cells as a result of actomyosin machinery activity have been found to act as a key regulator of the cell behavior including but not limited to programmed cell death (apoptosis). Further, hard biological materials, specifically abalone nacre, possess superior properties achieved during the process of evolution that outperform human-made materials. Understanding the fundamental mechanisms that are the underlying cause of these phenomena is an essential step toward tissue engineering, disease diagnosis/treatment, and developing advanced high-performance engineering materials. In this dissertation, the internal structure and composition of cells and biological materials were studied. We first examined how heterogeneity of the cell layer can alter emergent stress fields within two-dimensional multicellular systems. While studies have assumed simplifying assumptions such as homogeneity and isotropy in multicellular aggregates, we found that heterogeneous properties of the cell layer can invert the trend of predicted stress fields within the cell monolayer when compared to the trend in the case of homogeneous properties. The inverted trend is found to be more consistent with biological bio-markers. We then, using a combined analytical and computational approach, studied the effect of anisotropy and actin fiber alignment on the predicted stress field within the cell layer. Our results showed that uniform anisotropy cannot exist at the center of circular constrained cells and aggregates due to the occurrence of substantial stress concentration at the vicinity of the center. We found that considering the realistic anisotropic properties is crucial for the correct determination of stress fields within living cells. However, available experimental and computational techniques are not fully developed to capture anisotropic properties in soft biological materials and living cells. Therefore, we proposed a novel Machine Learning-based framework to characterize the anisotropic mechanical parameters in soft biological material using anisotropic indentation and Finite Element Analysis. Looking for a way to implement mechanisms used in nature into human-made engineered materials, we investigated the effect of tablet waviness in nacreous material. We realized that tablet waviness has a pivotal role in providing toughness and strength due to interlocking and negative Poisson’s ratio effects. We then implemented this mechanism in polymer-polymer and concrete-polymer engineered composites separately. Our results showed that designing the internal structure of composite material has an outstanding effect on increasing the performance and efficiency of engineered materials. This work provides new insights which can further be applied in tissue engineering, disease diagnosis/treatment, and designing new high-performance materials.

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  • etd-24611
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  • 2021
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  • 2021-05-14
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  • 2023-08-10

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Permanent link to this page: https://digital.wpi.edu/show/cr56n3934