Data-Driven Modeling of the Mechanics Behaviour of Architected and Soft Materials for Biomedical Applications

Abstract

The most relevant human-related problems where mechanics has played an important role are primarily due to the intersection with multidisciplinary biomedical applications such as implants or flexible sensors. Recent advances in sophisticated materials with customized properties envision the manufacturing of the future, in which the materials' design is precisely tailored to the purpose of the application. The implementation of data-driven methods from highly dynamic, complex, and nonlinear contexts holds promise for addressing this difficult materials science problem. Engineering has found two classes of materials of particular interest as study objects, namely soft multifunctional materials and architected materials. However, these exhibit difficult mechanical behaviors to fully comprehend, including viscoelastic properties, high nonlinear deformation, anisotropy, apparent properties, unconventional deformation mechanisms, complex manufacturing processes, and hysteresis. Stretchable multifunctional materials are closely related to the study of multiphysics responses from the standpoint of manipulating behavior under specific energy spectrum field, whereas architected materials or mechanical metamaterials can provide structural tensegrity behavior in order to manipulate shape response conditions. This thesis sheds light and insight on some ideas inspired by discussions and reflections to understand these materials via a succesful project-based methodology and curiosity-driven research.