6 October 2017 Reliable before-fabrication forecasting of normal and touch mode MEMS capacitive pressure sensor: modeling and simulation
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J. of Micro/Nanolithography, MEMS, and MOEMS, 16(4), 045001 (2017). doi:10.1117/1.JMM.16.4.045001
Abstract
An analytical model and numerical simulation for the performance of MEMS capacitive pressure sensors in both normal and touch modes is required for expected behavior of the sensor prior to their fabrication. Obtaining such information should be based on a complete analysis of performance parameters such as deflection of diaphragm, change of capacitance when the diaphragm deflects, and sensitivity of the sensor. In the literature, limited work has been carried out on the above-stated issue; moreover, due to approximation factors of polynomials, a tolerance error cannot be overseen. Reliable before-fabrication forecasting requires exact mathematical calculation of the parameters involved. A second-order polynomial equation is calculated mathematically for key performance parameters of both modes. This eliminates the approximation factor, and an exact result can be studied, maintaining high accuracy. The elimination of approximation factors and an approach of exact results are based on a new design parameter ( δ ) that we propose. The design parameter gives an initial hint to the designers on how the sensor will behave once it is fabricated. The complete work is aided by extensive mathematical detailing of all the parameters involved. Next, we verified our claims using MATLAB® simulation. Since MATLAB® effectively provides the simulation theory for the design approach, more complicated finite element method is not used.
© 2017 Society of Photo-Optical Instrumentation Engineers (SPIE)
Sumit Kumar Jindal, Ankush Mahajan, Sanjeev Kumar Raghuwanshi, "Reliable before-fabrication forecasting of normal and touch mode MEMS capacitive pressure sensor: modeling and simulation," Journal of Micro/Nanolithography, MEMS, and MOEMS 16(4), 045001 (6 October 2017). http://dx.doi.org/10.1117/1.JMM.16.4.045001 Submission: Received 14 April 2017; Accepted 12 September 2017
Submission: Received 14 April 2017; Accepted 12 September 2017
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KEYWORDS
Sensors

Capacitance

Oxides

Microelectromechanical systems

Modeling and simulation

Silicon

Electrodes

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