Design Optimization of a Capacitive Sensor for Mass Measurement of Nanometer-Sized Exhaust Carbon Particles

Authors

  • Vaishali Sanjay Kulkarni Department of Electronics and Telecommunication Engineering, All India Shri Shivaji Memorial Society’s Institute of Information Technology, Savitribai Phule Pune University, Pune, India
  • Suvarna Sandip Chorage Department of Electronics and Telecommunication Engineering, Bharti Vidyapeeth’s College of Engineering for Women, Savitribai Phule Pune University, Pune, India

DOI:

https://doi.org/10.46604/peti.2023.10200

Keywords:

capacitive sensing, nanometer-sized particulate mass, capacitive sensor, mass measurement

Abstract

Nanometer-sized carbon particulates generated by incomplete combustion in heavy-duty vehicles are harmful to human health. A high-resolution technique is needed to detect and measure these pollutants. This study aims to optimize a capacitive sensor design for detecting and measuring particulates. Firstly, the effect of design parameters on particulate detection and sensor compliance sensitivity is investigated by using the finite element method. By comparing the simulation results with literature findings for performance validation, the sensor structure is optimized to detect lower particulate concentrations. The simulation result shows that particulate detection sensitivity has linear variations with changes in particulate mass. With optimum electrode spacing and top insulation layer thickness of 5 µm, the sensor can detect a particulate deposition of 0.033 mg/min and generate a maximum capacitance of 581 pF. Since the optimized design can measure particulate deposition at a lower range and with higher sensitivity, it is suitable to be applied to detect nanometer-sized carbon particulates.

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Published

2023-04-28

How to Cite

[1]
Vaishali Sanjay Kulkarni and Suvarna Sandip Chorage, “Design Optimization of a Capacitive Sensor for Mass Measurement of Nanometer-Sized Exhaust Carbon Particles”, Proc. eng. technol. innov., vol. 24, pp. 53–62, Apr. 2023.

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