Overhaul of nano-sensors through inventive head design and certified performance improvements using construction building information modeling

Piezoresistive MEMS pressure sensors are widely deployed across biomedical, automotive, and aerospace sectors, yet their sensitivity is often limited by suboptimal membrane geometry and material selection. While prior research has explored isolated design modifications, there remains a lack of systematic, comparative analysis integrating multiple geometric enhancements with material optimization for maximum performance. This study aims to address this gap by developing and evaluating a four-stage structural optimization framework that systematically enhances sensor sensitivity. The novelty lies in combining targeted geometric modifications, central relocation of transverse resistors, introduction of peripheral grooves, addition of sub-membrane support beams, and membrane thickness optimization, with a comparative assessment of silicon (Si) and germanium (Ge) membranes. This integrated approach enables a unified understanding of how architecture and material mechanics interact to influence piezoresistive output. The methodology employed high-fidelity finite element modeling (FEM) in COMSOL Multiphysics to simulate coupled mechanical–electrical behavior. Input parameters included precise geometric configurations, material properties, and applied pressure (1 psi), while outputs comprised stress distribution, maximum deflection, and Wheatstone bridge output voltage. Mesh convergence analysis ensured numerical accuracy without excessive computational cost. Simulation results show cumulative sensitivity improvements of 256.8% for Si and 140.6% for Ge over baseline designs. After thickness optimization, sensitivities reached 11.99 mV/psi (Si) and 12.51 mV/psi (Ge), closing the performance gap between materials. Si benefited most from thickness reduction due to its higher Young