Simulation of Chemical Engineering Memristive Biosensor

This paper introduces a perspective approach for simulating a memristive sensor tailored for low-power biological analyte detection. The necessity for such innovation stems from the increasing demand for efficient biosensing technologies that can operate with minimal power consumption. Within this study, a numerical dynamic memristive model serves as a basis platform for implementing an enhanced nano-sensing method characterized by low cost and high sensitivity. Numerous simulations were conducted to validate the suitability of the dynamic memristive model's behavior for emulating a chemical sensing approach. The simulated data is collected for deploying an AI application to ensure an advanced predictable biosensing intake function. All in all, this work paves the way for developing compact numerical models of memristive biosensors, addressing the pressing need for portable, low-power consumption biosensing solutions.