“…( 4 ): where ε 1 and ε 2 are the dielectric constants of water and PI, respectively, and γ is the fractional volume of water molecules in the PI. where γ m is the maximum fractional volume of absorption at 298 K, R is the universal gas constant, T is the absolute temperature, x is the RH, α is the thermal coefficient of limiting absorption, E is the free energy of absorption, and b is an empirical factor that is determined via trial and error 38 . Fig.…”
Traditional humidity sensors for respiration monitoring applications have faced technical challenges, including low sensitivity, long recovery times, high parasitic capacitance and uncalibrated temperature drift. To overcome these problems, we present a triple-layer humidity sensor that comprises a nanoforest-based sensing capacitor, a thermistor, a microheater and a reference capacitor. When compared with traditional polyimide-based humidity sensors, this novel device has a sensitivity that is improved significantly by 8 times within a relative humidity range of 40–90%. Additionally, the integration of the microheater into the sensor can help to reduce its recovery time to 5 s. The use of the reference capacitor helps to eliminate parasitic capacitance, and the thermistor helps the sensor obtain a higher accuracy. These unique design aspects cause the sensor to have an excellent humidity sensing performance in respiration monitoring applications. Furthermore, through the adoption of machine learning algorithms, the sensor can distinguish different respiration states with an accuracy of 94%. Therefore, this humidity sensor design is expected to be used widely in both consumer electronics and intelligent medical instrument applications.
“…( 4 ): where ε 1 and ε 2 are the dielectric constants of water and PI, respectively, and γ is the fractional volume of water molecules in the PI. where γ m is the maximum fractional volume of absorption at 298 K, R is the universal gas constant, T is the absolute temperature, x is the RH, α is the thermal coefficient of limiting absorption, E is the free energy of absorption, and b is an empirical factor that is determined via trial and error 38 . Fig.…”
Traditional humidity sensors for respiration monitoring applications have faced technical challenges, including low sensitivity, long recovery times, high parasitic capacitance and uncalibrated temperature drift. To overcome these problems, we present a triple-layer humidity sensor that comprises a nanoforest-based sensing capacitor, a thermistor, a microheater and a reference capacitor. When compared with traditional polyimide-based humidity sensors, this novel device has a sensitivity that is improved significantly by 8 times within a relative humidity range of 40–90%. Additionally, the integration of the microheater into the sensor can help to reduce its recovery time to 5 s. The use of the reference capacitor helps to eliminate parasitic capacitance, and the thermistor helps the sensor obtain a higher accuracy. These unique design aspects cause the sensor to have an excellent humidity sensing performance in respiration monitoring applications. Furthermore, through the adoption of machine learning algorithms, the sensor can distinguish different respiration states with an accuracy of 94%. Therefore, this humidity sensor design is expected to be used widely in both consumer electronics and intelligent medical instrument applications.
“…Decreasing the thickness of the sensing film shortens the diffusion length of the water vapor molecules in the sensing material, hence improving the response time. 24 Capacitance also decreases with increasing thickness, which is supported by governing eq 5. Furthermore, as expected, thickness of the sensing film is a limiting phenomenon for affordable humidity sensors since fabrication methods must be kept in mind as it becomes more difficult at a smaller scale.…”
Section: Table 1 Structural Parameters Of the Capacitive Humidity Sensormentioning
confidence: 62%
“…Hence, by either increasing the spacing or decreasing the electrode width, the uncovered area of the sensing film increases. Thus, the contact area and rate of diffusion of water vapor in the sensing film increase, meeting the requirements of both high sensitivity and fast response. ,− …”
The geometrical dependence
of humidity sensors on sensing performance
has not been quantitatively outlined. Furthermore, the etching effect
on humidity sensors is still elusive due to the difficulty in separating
the effects of the geometrical change and etching-induced porosity
on the overall performance. Here, we use COMSOL Multiphysics to perform
a numerical study of a capacitive graphene oxide (GO) humidity sensor,
with emphasis on the dimensions and etching effect on their sensing
performance. GO is a useful and promising material in detecting humidity
because of its selective superpermeability to water molecules. The
mechanism of improved sensing performance of the etched humidity sensors
is discussed in terms of the morphological profile and the effective
permittivity including the etching-induced porosity effect. Our study
shows that as compared to the unetched sensors, isotropic etching
achieves the lowest response time of 1.011 s at 15.75% porosity, while
vertical etching achieves the highest capacitance sensitivity of 0.106
fF/RH %.
“…Watanabe et al [49] used ionic liquid (IL)-based polymer electrolytes comprising of block copolymers and polyimides to obtain easily processable ionic polymer actuators with high performance and durability. Zhou et al [50] prepared the parallel-plate capacitive humidity sensor with a polyimide (PI) film and obtained some promising results in improving response time.…”
This book chapter concentrates on energy storage applications of thin film containing electrochemical capacitors (supercapacitors) with specifically high-temperature polymers (fluorinated polymers, polyimides, polyarylenes, polyvinyl pyrollidone, etc.) for their good thermal and hydrolytic stability, excellent mechanical and chemical stability, low cost, flexibility and commercial availability. It consists of three main parts as given in the table of contents related to the 1) fluorinated high-performance polymers (FHPP) 2) nonfluorinated high-performance polymers (NFHPP) and 3) fluorinated and nonfluorinated high-performance polymers (FNFHPP) with their composites. A total of 141 literature reviewed references are cited.
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