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DEVELOPMENT OF GRAPHENE-BASED VOLATILE ORGANIC COMPOUND (VOCs) SENSOR

NOR AFFIZAL, AMIRAH (2018) DEVELOPMENT OF GRAPHENE-BASED VOLATILE ORGANIC COMPOUND (VOCs) SENSOR. UNSPECIFIED.

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Abstract

Nowadays, Volatile Organic Compounds (VOCs) sensor has been widely used for many purposes such as safety, agriculture quality control, disease diagnostic and more. The most popular VOCs sensor among consumer is Metal Oxide-based sensor. This sensor has its own limitation such as high temperature operation (operating temperature: 212°C - 1000°C) and requires additional circuit for heater. Graphene has been the most promising sensing material recently due to its unique properties of an excellent electrical and mechanical properties. This research will focus more on a Graphene-based VOCs sensor for determination of fruit maturity. There are two different sensor platforms that will be used in this research which are Quartz Crystal Microbalance (QCM) and Interdigitated Electrode (IDE). First, QCM is used solely to verify the Graphene synthesize is capable to detect targeted VOCs. Graphene synthetization is prepared using Ascorbic Acid method. After using QCM sensor, the research will continue with the fabrication of IDE where it will be designed using AutoCAD software. The IDE is then fabricated using Lithography method. In the end of fabrication, an electrical characterization will also be conducted in order to study the Graphene-based sensor performance in detecting selected VOCs such as Limonene and α-pinene. Based on the experiment that has been conducted, the Graphene-based sensor was very sensitive and able to detect up till 10 ppm of Limonene and α-pinene. Moreover, the IDE sensor also shows a good response and recovery time which are 5 seconds and 1 minute 30 seconds respectively. Therefore, it is proved that Graphene-based sensor is a better option to replace MOX because of the good response time which is much faster compared to MOX sensor. Furthermore, the accuracy of the results measured is determined using the standard error of mean (SEM) and root mean square error (RMSE). From the analysis, the lowest RMSE is 0.43 and the highest RMSE is 0.98 which is proved the high accuracy of the sensor measurement meanwhile the lowest SEM is 0.13 and the highest SEM is 0.28 where it proved that the reading measurement mean has a small variation of the results. This Graphene-based VOCs sensor will improve the performance current sensor and help the farmer and consumer in determination of fruit maturity.

Item Type: Final Year Project
Academic Subject : Academic Department - Electrical And Electronics - Pervasisve Systems - Digital Electronics - Design
Subject: UNSPECIFIED
Divisions: Engineering > Electrical and Electronic
Depositing User: Ahmad Suhairi Mohamed Lazim
Date Deposited: 20 Jun 2019 10:41
Last Modified: 20 Jun 2019 10:41
URI: http://utpedia.utp.edu.my/id/eprint/19157

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