Sol - gel synthesis of ?-Fe2O3 nanoparticles applied to the detection of the chip-base gas sensor

Abstract

To prevent human beings from being harmed by toxic gases and to protect the environment the detection of toxic gases becomes increasingly important Therefore the environmentally-friendly materials such as semiconductor metal oxides have been considered as effective sensing materials for many years and have been extensively studied First a micro-electromechanical system (MEMS) technology was used to grow a low-stress dielectric layer under wet oxygen on a six-inch silicon wafer and to deposit metal afterward to fabricate interdigital sensing electrodes and micro heating element Finally inductively-coupled reactive ion etching (ICP RIE) was used to etch the backside of the device to render a suspended structure Before carrying out the measurement a voltage was applied to the microheater to increase the temperature while a thermal imager was used to monitor the temperature change To prepare the sensing material the sol-gel method was adopted to synthesize ?-Fe2O3 nanoparticles and the variations in the characteristics of the films prepared at different annealing temperatures were assessed The result showed that the grain size increases with the annealing temperature Specifically conducting the annealing at 400 °C for an hour would yield the ?- Fe2O3 sensing film surface with more porous holes and a higher surface area layer which is conducive for gas adsorption Finally before initiating the measurement task the initial resistance value should be stabilized first in the atmosphere to ensure the subsequent gas sensing readings are gathered on a reliable basis With various gases sensed and duly compared it is found that NOx appears to have a better sensing response and faster response/recovery times for ?- Fe2O3 nano-films while subjecting the sensor to NO with a concentration of 50 ppb at operating temperature 200°C would show that a maximum response of 48% reliable reproducibility and stability of 53 54%

Date of Award	2020
Original language	English
Supervisor	Wen-Kuei Chuang (Supervisor)