A Multiphysics Framework for Bacterial Cellulose Sensor Modeling

Bacterial Cellulose (BC) is a promising biodegradable biopolymer synthesized by bacteria in a low energy consumption process based solely on renewable materials (a sucrose-based culture is required). BC-based composites exhibit excellent mechano-electrical transduction properties. However, there has been no systematic optimization of BC-based composites for the realization of transduction or low-cost electronics on BC. In this study, we propose different modeling paradigms categorized according to their basic principles: first principle white-box, grey-box, and black-box models. These paradigms have different levels of detail, interpretability and explainability, which are crucial for understanding model dynamics. The overall mltiphysics white-box model integrates electrical, mechanical and chemical effects into a unique solution, focusing on the coupling factors between the physics domains. In the case of grey-box models, reduced models are considered, while symbolic regression can be employed as enhanced black box models. The dynamic behavior of the BC model can be validated by data-driven characterization using experimental data.