Performance regulation of capacitive flexible pressure sensor based on non-uniformly distributed microstructure
[Objective]Generally,the sensitivity of capacitive flexible pressure sensors is affected by structural characteristics and geometric dimensions of the sensitive layer.Numerous studies have focused on establishing mathematical models to analyze and predict sensor sensitivity.However,most current research primarily concentrates on individual microstructural changes and pays little attention to analyses of microstructural distribution.Therefore,in this study,we consider the influence of distribution factors on the sensitivity and propose a predictive model for microstructures that are non-uniformly distributed.Additionally,based on this model,the optimal distribution form of microstructures is predicted.Finally,effects of different size parameters and multi-level microstructures on sensing performance are further analyzed.[Methods]First,a prediction model is established based on the theory of stress and deformation to predict the sensitivity of the sensor under different microstructure distributions in the sensitive layer.Second,for the purpose of using the predicted optimal distribution,PDMS is processed by a nanosecond ultraviolet laser(30 kHz,100 mm/s)so that sensitive layers with different microstructure sizes can be prepared.Subsequently,the prepared sensitive layer is placed between two ITO/PET films to assemble a flexible pressure sensor,and a sensitivity test is conducted to analyze the influence of the microstructure's size parameters and multi-stage microstructure on the sensor performance.Finally,the sensor with optimal parameters is prepared for performance and application testing.[Results]In this study,we present a mathematical model based on the non-uniform distribution of microstructures within the sensitive layer.In the model,the pressure on the corresponding microstructures is analyzed according to the distance relationship among them,and the deformation of the microstructures is further predicted.Based on the predicted microstructure deformation,the model predicts the sensitivity of the sensor in comparison with the actual measured value with the prediction error＜7％in the low-pressure range(0-100 Pa).Additionally,we investigate the influence of distribution factors on sensor performance.The model can predict the microstructure distribution with the highest sensitivity under specific sensor size conditions.Furthermore,the influence of microstructure size parameters and multi-stage microstructures on sensor performance is discussed.Results indicate that the microstructure height exerts a relatively small influence on sensitivity and linear range under low-pressure conditions.However,the sensitivity can be significantly improved by reducing the radius of the top surface,albeit at the cost of reducing the linear range.Moreover,the bottom surface radius imposes an impact only slightly on the sensitivity,but quite noticeably on the linear range.Increasing the number of microstructures reduces the sensitivity while enhancing its linear range.To demonstrate the practicality of the research,we fabricate sensors corresponding to the predicted optimal microstructure distribution and test their performances and application suitability.In performance testing,these sensors exhibit fast response times(400 ms)and low detection limits(2.3 Pa).They also demonstrate excellent dynamic response stability and reliable repeatability under repeated exposure to different pressure sequences.In application suitability tests,they effectively distinguish the bending state and behave suitably for real-time monitoring of joint motion and similar applications.Additionally,they can accurately reflect respiratory changes in individuals under different states and differentiate among three facial expressions:expressionless,slight frowning,and frowning.These findings highlight their potential applications in electronic skin,intelligent robotics,wearable electronic devices,and health monitoring,among other fields.[Conclusions]To regulate the performance of non-uniformly distributed flexible pressure sensors,we investigate the influence of microstructure distribution,size,and multi-level microstructures on the sensor performance.The relationship between different size parameters of the truncated cone-shaped microstructure and sensor performance reveals that the sensitivity of the sensor is closely related to the distribution and geometric parameters of microstructures.The performance of flexible pressure sensors can be regulated by controlling the microstructure distribution and the geometric parameters of the microstructures in the sensitive layer.The sensor exhibits high sensitivity of 2.07 kPa-1,a low detection limit of 2.3 Pa,and excellent stability over 1 000 cycles.These results demonstrate the effectiveness of the proposed method for regulating sensor performance and hopefully provide valuable guidance for the customized design of sensors targeting specific applications.
万方数据
维普
