A multi-scale and multi-physics framework for integrated electronics operating in harsh environment: a sensor-to-system perspective

2020-03-22T03:15:59Z (GMT) by Xin Jin
In the modern IoT network, the design of edge computing electronics operating in harsh environment faces great challenges. In this doctoral thesis, we are developing an end-to-end modeling framework for two IoT-based applications: medical care and precision agriculture. By coupling the physics of analyte mass transfer, electrochemical reactions, and electrostatics, the framework paves the way for the development of the following new generation electrochemical/biosensors: 1) high sensitivity nano-electrode non-enzymatic/enzymatic amperometric glucose sensors, 2) self-powered enzymatic biofuel cell (EBFC)-based lactate sensors, and 3) roll-to-roll printed thin-film ion-selective electrode (ISE)-based soil nitrate sensors. By calibrating our physics-based model with experimental data, the framework explores the geometrical and electrochemical limitations of sensors and provides guidelines for improving the sensitivity, enhancing the selectivity, reducing the response time, and increasing the signal-to-noise ratio. On the other hand, the framework also focuses on the general reliability issues for the IoT edge-computing electronics in the system integration level. It includes the physics of the multiple degradation mechanisms in harsh environments, such as corrosion assisted by moisture diffusion, device instability due to ion drift, and dissolution of the packaging material in the salty biochemical environment. Our results can be used to predict the performance degradation and project the lifetime of electronic devices for implantable and autonomous sensors, providing direction to optimize the design of the protective packaging.