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Research of Long-Term Stability of High-Sensitivity Piezoresistive Pressure Sensors for Ultralow Differential Pressures

Mikhail Basov

2024IEEE Sensors Journal31 citationsDOI

Abstract

Long-term stability of output characteristics of piezoresistive pressure sensor chips in the form of microelectromechanical systems (MEMS) is one of the most important parameters. The research analyzes the variation of the useful signal of high sensitive pressure sensor chips and its errors in mechanical and temperature characteristics, which are also time-dependent. The main feature of this study is the application of the previously developed construction of mechanical parts, which allows to achieve a balance between extremely high-sensitivity and low error rates for ultralow pressure range. The research demonstrates the changes after five years of aging for 24 pressure sensor chip samples (chip dimension <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$6.15\times 6.15$ </tex-math></inline-formula> mm2) for pressure range of 0.5 kPa with sensitivity <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${S}_{\text {0.5 after}} = $ </tex-math></inline-formula> (34.5 ± 6.0) mV/V/kPa, nonlinearity 2K<inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$_{\text {NL 0.5 after}} = $ </tex-math></inline-formula> (0.71 ± 0.47)%/FS and temperature hysteresis up to 0.5% in the temperature range from -30 °C to + 60 °C. The results of long-term stability of useful signal show that the errors for 10 out of 24 samples do not exceed the values of 1.5%, which mostly connects with the influence of residual mechanical stresses (MSs) from the assembly design of the pressure sensor.

Topics & Concepts

Piezoresistive effectSensitivity (control systems)Differential pressureMaterials scienceTerm (time)Pressure sensorStability (learning theory)Differential (mechanical device)Pressure measurementElectronic engineeringOptoelectronicsControl theory (sociology)EngineeringPhysicsMechanicsComputer scienceMechanical engineeringThermodynamicsMachine learningQuantum mechanicsArtificial intelligenceControl (management)Advanced MEMS and NEMS TechnologiesAdvanced Measurement and Metrology Techniques
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