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• W3118204119 endingPage "58316" @default.
• W3118204119 startingPage "58301" @default.
• W3118204119 abstract "Rationally designed pressure sensors for target applications have been in increasing demand. Capacitive pressure sensors with microstructured dielectrics demonstrate a high capability of meeting this demand due to their wide versatility and high tunability by manipulating dielectric layer material and microstructure geometry. However, to streamline the design and fabrication of desirable sensors, a better understanding of how material microstructure and properties of the dielectric layer affect performance is vital. The ability to predict trends in sensor design and performance simplifies the process of designing and fabricating sensors for various applications. A series of equations are presented that can be used to predict trends in initial capacitance, capacitance change, and sensitivity based on dielectric constant and compressive modulus of the dielectric material and base length, interstructural separation, and height of the dielectric layer microstructures. The efficacy of this model has been experimentally and computationally confirmed. The model was then used to illuminate, qualitatively and quantitatively, the relationships between these key material properties and microstructure geometries. Finally, this model demonstrates high tunability and simple implementation for predictive sensor performance for a wide range of designs to help meet the growing demand for highly specialized sensors." @default.
• W3118204119 created "2021-01-05" @default.
• W3118204119 creator A5042012998 @default.
• W3118204119 creator A5070314852 @default.
• W3118204119 date "2020-12-21" @default.
• W3118204119 modified "2023-10-12" @default.
• W3118204119 title "Designing Tunable Capacitive Pressure Sensors Based on Material Properties and Microstructure Geometry" @default.
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• W3118204119 doi "https://doi.org/10.1021/acsami.0c19196" @default.
• W3118204119 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/33345539" @default.
• W3118204119 hasPublicationYear "2020" @default.
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