Graduation Year

2025

Document Type

Thesis

Degree

M.S.E.E.

Degree Name

MS in Electrical Engineering (M.S.E.E.)

Degree Granting Department

Electrical Engineering

Major Professor

Arash Takshi, Ph.D.

Committee Member

Sylvia Thomas, Ph.D.

Committee Member

Ehsan Sheybani, Ph.D.

Keywords

Auto Ranging Circuit, Chemiresistor, Electronic Nose, Interdigitated Electrode, Thin Film Sensor

Abstract

This thesis presents the development, characterization, and integration of a novel low-cost, high-dynamic-range sensor platform for the detection of volatile organic compounds (VOCs), leveraging the unique electrical properties of carbon nanotube (CNT) thin films. The platform introduces a fully integrated auto-ranging analog front-end circuit capable of real-time resistance measurement spanning over eight orders of magnitude ranging from tens of ohms to hundreds of megaohms, without compromising signal resolution or precision. This was achieved through a digitally controlled, multi-path feedback architecture and controllable current source.

To further enhance sensor performance, the system incorporates a copper trace heater beneath the sensor array, allowing programmable thermal modulation via PWM control. This heater accelerates sensor recovery and enables temperature-programmed analyte discrimination. The platform also integrates environmental monitoring via an HTU21D sensor for real-time temperature and humidity logging, ensuring the accuracy and repeatability of experiments.

Sensor fabrication involved drop-casting multi-walled CNT (MWCNT) dispersions onto three custom-designed interdigitated and gapped electrode geometries. Electrical and thermal tests confirmed stable and reproducible sensor responses to ethanol vapor, with the heater significantly reducing recovery time.

Altogether, this work demonstrates a flexible, scalable, and highly customizable VOC sensing platform that combines hardware adaptability with signal processing capability. Its compact architecture and modular design lay the foundation for future development in smart sensing systems, material optimization studies, and multi-analyte detection.

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