Mazlee Mazalan
Thumbnail Image
Preferred name
Mazlee Mazalan
Official Name
Mazlee, Mazalan
Alternative Name
Mazalan, Mazlee Bin
Mazalan, Mazlee
Main Affiliation
Scopus Author ID
54420543000
Researcher ID
FKZ-3093-2022

Research Output

Filters

1
1
1
Reset filters

Settings
Now showing 1 - 1 of 1
  • Publication
    Modelling and Simulation using Finite Element Method of Surface Acoustic Wave Biosensor for Gas Detection Application
    ( 2021-11-25)
    Anas Mohd Noor
    ;
    Ahmad Nasrul Norali
    ;
    Zulkarnay Zakaria
    ;
    Mazlee Mazalan
    ;
    Yufridin Wahab
    A surface acoustic wave (SAW) sensor detects changes in physical properties such as mass and density on its surface. Compared to other types of sensors, SAW sensor have a good stability, high selectivity and sensitivity, fast response, and low-cost. On the other hand, to design and optimize a SAW biosensor requires a long process including time and cost using conventional methods. Therefore, numerical simulation and computational modelling are useful and efficiently conduct analysis for the SAW biosensor. In this paper, a numerical simulation technique is used to analyse the SAW device sensitivity for the application of gas detection. The SAW biosensor can detect very small mass loading by changing its sensor resonance frequency. The two-dimensional (2D) device model is based on a two-port SAW resonator with a gas sensing layer. We made two design of SAW biosensor device with frequency of 872 MHz and 1.74 GHz. A gas with vary concentration from 1 to 100 ppm were used to determine the change of the device resonance frequency. As a result, the high frequency (1.74 GHz) device, shows that the resonance frequency is shifted larger than to the low frequency (872 MHz) device. In addition, the high frequency device offers five times more sensitivity than the low frequency device. By changing the sensor design, the sensor characteristics such as sensitivity can be altered to meet certain sensing requirements. Numerical simulation provides advantages for sensor optimization and useful for nearly representing the real condition.
      1