A Dual-Ion Multiphysics Model for Smart and Sustainable Sensors Based on Bacterial Cellulose

Bacterial cellulose (BC) is an emerging smart material, synthesized through microbial fermentation of environmentally friendly substrates, including organic waste. When functionalized with ionic liquids (ILs) and coated with conductive polymers, BC forms soft, sustainable, and electroactive composites, making it suitable for sensors in soft robotics, wearable, biomedical, and environmental monitoring applications. However, modeling frameworks for BC–IL sensors are still lacking, hindering their integration into real-world applications. To bridge this gap and support smart material design, we propose a novel first-principle white-box modeling framework is proposed that couples a 2D finite element method (FEM) for mechanical deformation with 1D FEM sub-models for ion transport and voltage generation. Specifically, this work introduces the first dual-carrier multiphysics model for mechanoelectric transduction in BC–IL sensors. The model, experimentally calibrated and validated, resolves the spatio-temporal dynamics of mechanical deformation and dual-ion transport, including diffusion, electromigration, and advection. By explicitly incorporating the transport and interaction of both cations and anions, previously neglected in smart-sensors modeling, the proposed strategy provides a foundational simulation framework for the scalable, rapid, and intelligent design of next-generation biodegradable and multifunctional smart sensors, advancing the integration of green materials into intelligent systems.