Pressure Sensor Research Articles

Effect of Nanostructure Morphology and Concentration on the Piezoelectric Performance of Flexible Pressure Sensor based on PVDFTrFE/ Nano-ZnO Composite Thin Film

Background: The development of high-performance piezoelectric pressure sensors with outstanding sensitivity, good linearity, flexibility, durability, and biocompatibility is of great significance for smart robotics, human healthcare devices, smart sensors, and electronic skin. Thus, considerable progress has been achieved in enhancing the piezoelectric property of PVDF-TrFEbased composite pressure sensors by adding various ZnO nanostructures in PVDF-TrFE polymer acting as a nucleating agent and dielectric material. Aims: In this work, flexible pressure sensors with a sandwich structure based on PVDFTrFE/ nano-ZnO composite sensing film were fabricated using a simple spin-coating method and post-annealing process, while electrospinning and high-voltage polarization processes were not adopted. Methods: Poly (vinylidene fluoride-trifluoroethylene) (PVDF-TrFE)/nano-ZnO composite films were prepared via spin coating to fabricate flexible piezoelectric pressure sensors. ZnO nanoparticles (ZnO NPs), tetrapod ZnO (T-ZnO) and ZnO nanorods (ZnO NRs) were used as nano-fillers for piezoelectric PVDF-TrFE, to enhance the beta-crystal ratio as well as the crystallinity of PVDF-TrFE. The structural and surface morphologies of the composite films were investigated using Fourier transform infrared spectroscopy (FT-IR), X-ray diffraction (XRD) and scanning electron microscopy (SEM). Results: Among three different types of ZnO nanostructures with a concentration range (0-7.5 wt%), the sensor with 0.75 wt% ZnO NRs nanofiller exhibits a maximum output voltage of 1.73 V under an external pressure of 3 N and a maximum sensitivity of 586.3 mV/N at the range of 0-3 N. Further, the sensor can generate a clear piezoelectric voltage under bending and twisting deformation as well as compression and tensile deformation. Conclusion: To summarize, the addition of different concentrations of nano-ZnO can remarkably improve the piezoelectric performance of the composite sensor, and ZnO NRs can achieve better piezoelectric properties of the sensor as compared to ZnO NPs and T-ZnO. In addition, the sensor with 0.75 wt% ZnO NRs as nanofiller has the highest piezoelectric response, which is about 2.4 times that of the pure PVDF-TrFE sensor. It is demonstrated that the sensor has great potential applications in wearable health monitoring systems and mechanical stress measurement electronics.

Integrated Barometric Pressure Sensors on Legged Robots for Enhanced Tactile Exploration of Edges

Integrated Barometric Pressure Sensors on Legged Robots for Enhanced Tactile Exploration of Edges

Real-time monitoring system for blood pressure monitoring based on internet of things

Real-time monitoring system for blood pressure monitoring based on internet of things

High sensitivity distributed dynamic pressure sensor based on dual-linear frequency modulated optical frequency domain reflectometry.

In this Letter, we propose and experimentally demonstrate a highly sensitive distributed dynamic pressure sensor based on a dual-linear frequency modulated optical frequency domain reflectometry (OFDR) and a coating thickness-enhanced single-mode fiber (SMF). A dual-sideband linear frequency modulation (LFM) signal is used to interrogate the sensing fiber, which allows us to obtain a dual-sideband Rayleigh backscattering signal. Due to the opposite slopes of the two LFM sidebands, the Rayleigh backscattering spectra of the two sidebands drift in opposite directions when the fiber is disturbed. By subtracting the frequency shifts of the two spectra, we can double the system's sensitivity. We further enhance the sensitivity by using an SMF with a coating thickness of 200 μm. This results in a pressure sensitivity of 3979 MHz/MPa, a measurement accuracy of 0.76 kPa, and a spatial resolution of 35 cm over a 500 m optical fiber. Our system successfully detected a dynamic pressure change at a sampling rate of 1.25 kHz, demonstrating the sensor's excellent dynamic measuring capabilities.

Efficient Fabrication of Bioinspired Flexible Pressure Sensors via Electrohydrodynamic Jet Printing Method.

The bioinspired microdevices have made significant strides in various applications including human motion and health detection. However, the facile and highly efficient fabrication approach of flexible pressure sensors remains a great challenge. Herein, inspired by the gecko's foot structure, a flexible pressure sensor with microdomes structures was one-step fabricated by tip-assisted on-demand electrohydrodynamic jet (EHD-jet) printing method. Ascribed to the interlocking electrodes with microdome structure substantially enlarged 3D deformation rates. When the microdromes structure is under pressure, the resistivity of the CNTs film coated on the surface of the microdomes structure will change remarkably. By using the combined effect of assisted tip and ring focusing electrode, the influence and constraints on microstructure fabrication caused by substrate material and morphology are minimized. The desired uniform structures can be adjusted rapidly by changing the printing parameters and liquid properties. The high length-height ratio (0.64) of microdomes, notably enhances the sensitivity, the minimum detection limit is 2Pa and the response time is 40ms. Finally, the bionic flexible sensor shows excellent performance in capable of detecting pressure, sound vibrations, and human motion. This work introduces a previously unexplored method for the high-efficiency fabrication of micro-nano patterns for bionic flexible sensors, with potential applications in wearable devices and human health detection. This article is protected by copyright. All rights reserved.

Characterisation of particle single-scattering albedo with a modified airborne dual-wavelength CAPS monitor

Abstract. Atmospheric aerosols impact the Earth's climate system directly by scattering and absorbing solar radiation, and it is important to characterise the aerosol optical properties in detail. This study reports the development and validation of an airborne dual-wavelength cavity-attenuated phase-shift (CAPS) single monitor, named A2S2 (Aerosol Absorption Spectral Sizer), based on the commercial CAPS single-scattering albedo monitor (CAPS-PMSSA; Aerodyne), to simultaneously measure the aerosol optical scattering and extinction at both 450 and 630 nm wavelengths. Replaced pressure and temperature sensors and an additional flow control system were incorporated into the A2S2 for its utilisation on board research aircraft measuring within the troposphere. The evaluation of A2S2 characteristics was performed in the laboratory and included the investigation of the signal-to-noise ratio, validation of performance at various pressure levels, optical closure studies and intercomparing with the currently validated techniques. The chamber experiments show that the A2S2 can perform measurements at sample pressures as low as 550 hPa and at sample temperatures as high as 315 K. Based on the Allan analysis results, we have evaluated that the minimum detection limit of the measurements shows that the measurements have a limit accuracy of ∼ 2 Mm−1 at 450 nm and ∼ 1 Mm−1 at 630 nm for 1 Hz measurements of both scattering coefficients (σsca) and extinction coefficients (σext). The optical closure study with size-selected polystyrene latex (PSL) particles shows that the truncation error of the A2S2 is negligible for particles with particle volume diameter (Dp) < 200 nm, while, for the larger sub-micrometre particles, the measurement uncertainty of A2S2 increases but remains less than 20 %. The average factors to correct the truncation error are 1.13 and 1.05 for 450 and 630 nm, respectively. A simplified truncation correction, dependent on the scattering Ångström exponent (SAE), was developed to rectify truncation errors of the future A2S2 field measurement data. The σsca and σext measured by the A2S2 show good agreement with the concurrent measured results from the nephelometer and the CAPS particle extinction monitor (CAPS-PMex). The absorption coefficient (σabs) derived through the extinction-minus-scattering (EMS) method by the A2S2 also corresponds with the results obtained from the aethalometer. The A2S2 was successfully deployed during an aircraft measurement campaign (Atmospheric ChemistRy Of the Suburban foreSt – ACROSS) conducted in the vicinity of Paris and the surrounding regions. The average SSA measured during the entire ACROSS flight campaign is 0.86 and 0.88 at 450 and 630 nm, respectively, suggesting that light-absorbing organic aerosols play a significant role. The average SAE and absorption Ångström exponent (AAE) varied due to measurements in various pollution conditions. The results presented in this study indicate that the A2S2 instrument is reliable for measuring aerosol σsca and σext at both blue and red wavelengths, and it stands as a viable substitute for future airborne evaluations of aerosol optical properties.

Direct-write printed controllable concave surface for fabricating flexible metal electrode

Structured surface of flexible substrate could generate a positive impact on flexibility of metal electrode due to the surface free energy relaxation, which could make the flexibility of metal electrode meet the performance requirement of flexible electronics. However, the preparation of controllable structured surface of flexible substrate is still a tough and challenge process. In this research work, controllable concave surface of flexible substrate was prepared by direct-write print with a viscoelastic substrate. When the controllable concave surface of flexible substrate was evaporated with a nanoscale metal layer, various metal electrodes could be obtained with a controllable morphology of concave surface. The direct-write printed concave surface efficiently enhanced the flexibility of metal electrodes. When the prepared concave surface generated a continuous connected structure with a 0.1 mm printing space, an excellently enhanced flexibility of metal electrode was achieved with an internal bending flexibility of 93.72%, external bending flexibility of 93.67%, stretchability of 85% and number of stable cyclic bending times over 12,000. Meanwhile, the direct-write printed concave surface generated a reversed convex surface, which could be used for pressure sensing as a flexible pressure sensor. Therefore, this research work provides an efficient method for fabricating flexible electrode, which has important research and application value in the area of high-performance flexible electronics.

Novel design of double touch plano-convex mems capacitive pressure sensor: robust design, theoretical modeling, numerical simulation and performance comparison

Novel design of double touch plano-convex mems capacitive pressure sensor: robust design, theoretical modeling, numerical simulation and performance comparison

Structural insight into piezo-solvatochromism of Reichardt's dye.

To date, accurate modelling of the solvation process is challenging, often over-simplifying the solvent-solute interactions. The interplay between the molecular arrangement associated with the solvation process and crystal nucleation has been investigated by analysis of the piezo-solvatochromic behaviour of Reichardt's dye, ET(1), in methanol, ethanol and acetone under high pressure. High-pressure single-crystal X-ray diffraction and UV-Vis spectroscopy reveal the impact of solute-solvent interactions on the optical properties of ET(1). The study underscores the intricate relationship between solvent properties, molecular conformation and crystal packing. The connection between liquid and solid phases emphasizes the capabilities of high-pressure methods for expanding the field of crystal engineering. The high-pressure environment allowed the determination of the crystal structures reported here that are built from organic molecules fourfold solvated with ethanol or methanol: ET(1)·4CH3OH and ET(1)·4C2H5OH·H2O. The observed piezo-solvatochromic effects highlight the potential of ET(1) in nonlinear optoelectronics and expand the application of solvatochromic chemical indicators to pressure sensors.

Dual-responsive fully self-healing triboelectric pressure sensor: Integrating truncated sphere morphology with deep learning-enhanced signal

We crafted a cutting-edge pressure sensor that exhibits exceptional dual-signal responsiveness, a testament to the innovative application of smart materials and artificial intelligence. This advancement is anchored by the MXene-dispersed hexafluoroisopropylene diphthalic anhydride-polydimethylsiloxane (M-FPP) composite, which is a truncated sphere-shaped material. This unique structure interacts with the graphene-coated polycaprolactone (G-PCL), adjusting its contact area to maintain accurate linearity across pressures ranging from 5 to 50 kPa. FPP and PCL, materials chosen for their self-healing properties, enable the sensor to recover its full structure and function after damage with targeted heat treatment. The sensor's advanced morphology elevates its ability to detect variations in both pressure and the duration of contact. Integration with a 1D-Convolution Neural Network (CNN) model enhances signal classification, achieving an impressive accuracy of 98.26 %. Such sensitivity allows for the recognition of minute differences in pressure and temporal parameters, surpassing conventional sensors' capabilities. With the M-FPP's design, the sensor's performance is significantly optimized, catering to varying pressure conditions. This blend of intelligent design and deep learning technology marks a stride toward adaptive and responsive sensing devices, capable of navigating the complexities of real-world stimuli with remarkable accuracy.

Porous PVDF composites with ultralow percolation threshold for wide-range dynamic and static pressure sensing

Porous conductive polymer composites are very attractive for static pressure sensing due to high sensitivity and good elasticity contributed by the porous structure, while they are hard to detect dynamic pressure. Herein, we report a porous conductive poly (vinylidene fluoride) (PVDF) composite capable of detecting static and dynamic pressure over a pressure range of 0–1 MPa, which was fabricated by melt mixing PVDF, polyethylene oxide (PEO) and carbon nanofillers, followed by etching PEO with water. Such porous PVDF composites have a very low percolation threshold (0.035 wt%) of carbon nanostructures (i.e., branched carbon nanotubes) thanks to the selective distribution of conductive fillers in the pore wall after etching. At the same time, the pore size and porosity of the porous PVDF composites can be tuned by the molecular weight (Mw) and blending ratios of two polymers, leading to the kinetically-tailorable blend morphology for tunable mechanical and electrical properties. The as-fabricated porous PVDF composites with a good combination of mechanical properties and electrical conductivities, which can be used as pressure sensors toward wide-range (0–1 MPa) dynamic and static pressure sensing. Such pressure sensors demonstrate potential applications in detecting the degree of finger bending, distinguishing the walking and running, and monitoring a series of technical movements in playing soccer, i.e., static and dynamic exercises.

Endovascular Detection of Catheter-Thrombus Contact by Vacuum Excitation.

The objective of this work is to introduce and demonstrate the effectiveness of a novel sensing modality for contact detection between an off-the-shelf aspiration catheter and a thrombus. A custom robotic actuator with a pressure sensor was used to generate an oscillatory vacuum excitation and sense the pressure inside the extracorporeal portion of the catheter. Vacuum pressure profiles and robotic motion data were used to train a support vector machine (SVM) classification model to detect contact between the aspiration catheter tip and a mock thrombus. Validation consisted of benchtop accuracy verification, as well as user study comparison to the current standard of angiographic presentation. Benchtop accuracy of the sensing modality was shown to be 99.67%. The user study demonstrated statistically significant improvement in identifying catheter-thrombus contact compared to the current standard. The odds ratio of successful detection of clot contact was 2.86 (p = 0.03) when using the proposed sensory method compared to without it. The results of this work indicate that the proposed sensing modality can offer intraoperative feedback to interventionalists that can improve their ability to detect contact between the distal tip of a catheter and a thrombus. By offering a relatively low-cost technology that affords off-the-shelf aspiration catheters as clot-detecting sensors, interventionalists can improve the first-pass effect of the mechanical thrombectomy procedure while reducing procedural times and mental burden.

Durable and highly signal-stable pressure sensors prepared by sequential thiol-acrylate click reactions

Pressure sensors are an important part of the Internet of Things (IoT) and human–machine interaction (HMI), and their signal stability and durability are greatly affected by the interfacial interaction between the substrate and the conductive layer. Herein, a pressure sensor prepared by sequential radical-mediated thiol-acrylate click reactions is reported. In first click reaction, the porous substrate polyHIPE-SH with inherently thiols is fabricated. Those thiols give us second chance to chemically bridge carboxylic carbon nanotubes (CNT)/polyethylene glycol diacrylate (PEGDA) conductive coating to the substrate using the click reaction, with 21.5 % of the thiols on the substrate involved in the reaction. As expected, the obtained pressure-sensitive material CNT/PEGDA@polyHIPE-SH has a strong interfacial interaction between the substrate and the conductive layer, thus ensuring the good signal stability and durability. The sensor also has a sensitivity of up to −6.45 % kPa−1 and a wide response range from 0 to 400 kPa. Furthermore, the sensors are used as input devices to realize multi-mode HMI, and high-accuracy object recognition at low sensor densities via a convolutional neural network based deep learning model.

Integrating Interference and Resonance Effects in Microfiber Sensors for Simultaneous Pressure and Temperature Measurement

Integrating Interference and Resonance Effects in Microfiber Sensors for Simultaneous Pressure and Temperature Measurement

Flexible Capacitive Pressure Sensor Enhanced by Black Phosphorus-Au Nanocomposites/Ecoflex Sponge for Pressure and Proximity Detection

Flexible Capacitive Pressure Sensor Enhanced by Black Phosphorus-Au Nanocomposites/Ecoflex Sponge for Pressure and Proximity Detection

Development of a Predictive Model for Evaluation of the Influence of Various Parameters on the Performance of an Oscillating Water Column Device.

Oscillating Water Column (OWC) systems harness wave energy using a partially submerged chamber with an underwater opening. The Savonius turbine, a vertical-axis wind turbine, is well-suited for this purpose due to its efficiency at low speeds and self-starting capability, making it an ideal power take-off (PTO) mechanism in OWC systems. This study tested an OWC device with a Savonius turbine in an air duct to evaluate its performance under varying flow directions and loads. An innovative aspect was assessing the influence of power augmenters (PAs) positioned upstream and downstream of the turbine. The experimental setup included load cells, Pitot tubes, differential pressure sensors and rotational speed sensors. Data obtained were used to calculate pressure differentials across the turbine and torque. The primary goal of using PA is to increase the CP-λ curve area without modifying the turbine geometry, potentially enabling interventions on existing turbines without rotor dismantling. Additionally, another novelty is the implementation of a regression Machine-Learning algorithm based on decision trees to analyze the influence of various features on predicting pressure differences, thereby broadening the scope for further testing beyond physical experimentation.

Low-cost, reliable and flexible piezoresistive pressure sensors coated with single layer graphene and silver nanowires on three-dimensional polyurethane sponge

Flexible wearable sensors perform a significant role in practical applications such as medical monitoring, rehabilitation exercises, and artificial skin, as they can quantify and visualize external stress and strain. Polyurethane (PU) sponge stands out as a highly elastic and reproducible material frequently employed as a substrate in flexible electronic devices. Sponge materials with different pore sizes and densities exhibit varying degrees of deformation resistance under long-term cyclic pressure, thereby affecting the performance of sensors. Herein, piezoresistive pressure sensors based on PU with different pore diameters were successfully fabricated by dip-coating technology. By incorporating silver nanowires (AgNWs) and single layer graphene (SLG) into the sponge, both the low-density and high-density composite sponges can withstand over 70 % compressive strain, with stresses of 62.57 kPa and 31.79 kPa, respectively. Moreover, high-density composite sponge demonstrates a more stable conductive structure, more consistent relative resistance and better flame-retardant performance. The response and recovery time between 10 % and 40 % strains of the resulting pressure sensor based on high-density composite sponge (PU@AgNWs@SLG) are 110 ms and 106 ms and its gauge factor reaches 2.39. The pressure sensor exhibits a satisfactory reproducibility after over 3000 compression-release cycles, and performs during various applications, such as controlling brightness of LEDs, monitoring human activities, sensing finger movements.

Optimisation of properties of multidimensional hybrid polymer nanocomposites for flexible pressure sensors

Flexible, wearable pressure sensors provide a convenient, timely, and portable solution for human motion detection. However, there is still a lack of reports on the synergistic effect of multidimensional hybrid polymer nanocomposites for modulating the sensor’s key performance indexes. Herein, we present a cost-effective and scalable approach to preparing multidimensional hybrid polymer composites for piezoresistive pressure sensors. Composite charge-transfer paths and contact types are presented for the first time and analyzed in relation to the sensor sensitivity and linearity. The sensor has good characteristics, such as 0 ∼ 70 kPa range, 369.39 kPa−1 sensitivity, a minimum resolving power of 18 Pa and 68 ms, and 76 ms response and recovery times, owing to the interconnecting porous structure of MS and the synergistic effect of the composites. The sensor exhibited a stable piezoresistive response and good reproducibility over 9000 + cycles. The sensor was then attached to different parts of the human body and evaluated for its ability to detect various human movements, including speech and elbow flexion. Finally, a prototype haptic sensing array and a prototype force measurement platform based on these pressure sensors were demonstrated.

Sensitivity enhanced flexible capacitive pressure sensor microstructure optimization for biomedical applications

This paper explores the design and optimization of Flexible Capacitive Pressure Sensors (FCPS) using microfabrication technology for applications in the emerging field of flexible electronics, with a particular focus on measuring bio-signals characterized by lower pressure ranges. Sensitivity, a critical parameter for effective FCPS performance, is investigated through a comprehensive series of simulation analyses employing finite element modeling. The study involves varying geometrical and mechanical parameters that influence FCPS performance, individually adjusting each parameter while keeping others constant. Microstructures such as cuboids, truncated pyramids with an aspect ratio of 0.5, cylinders, pyramids, and cones are modeled on the dielectric material surface. The parameters considered include inter-space, base length, height, and elastic modulus, to enhance FCPS sensitivity and linearity. Among the different shapes modeled, the cone exhibits the highest sensitivity, followed by the pyramid structure. Comparative analysis indicates that the cone and pyramid shapes demonstrate 15- and 10-times higher sensitivity, respectively, compared to the cuboid structure under an applied pressure of 10 Pa. Simulation results suggest that sensitivity can be finely tuned, with higher inter-space and microstructure height, as well as lower base length and Young’s modulus of the dielectric material, contributing to increased sensitivity. However, it is noted that these conditions may lead to decreased capacitance in the absence of applied pressure due to air occupation relative to the dielectric material. The findings are further compared with existing literature, and the FCPS response analysis provides valuable insights for the future design of FCPS, particularly in the context of biomedical applications requiring precise low-pressure signal measurements. This research contributes to advancing the understanding of FCPS performance optimization and lays the groundwork for the development of sensors with enhanced sensitivity for bio-medical applications.

A smart detection method for sleep posture based on a flexible sleep monitoring belt and vital sign signals

People spend approximately one-third of their lives in sleep, but more and more people are suffering from sleep disorders. Sleep posture is closely related to sleep quality, so related detection is very significant. In our previous work, a smart flexible sleep monitoring belt with MEMS triaxial accelerometer and pressure sensor has been developed to detect the vital signs, snore events and sleep stages. However, the method for sleep posture detection has not been studied. Therefore, to achieve high performance, low cost and comfortable experience, this paper proposes a smart detection method for sleep posture based on a flexible sleep monitoring belt and vital sign signals measured by a MEMS Inertial Measurement Unit (IMU). Statistical analysis and wavelet packet transform are applied for the feature extraction of the vital sign signals. Then the algorithm of recursive feature elimination with cross-validation is introduced to further extract the key features. Besides, machine learning models with 10-fold cross validation process, such as decision tree, random forest, support vector machine, extreme gradient boosting and adaptive boosting, were adopted to recognize the sleep posture. 15 subjects were recruited to participate the experiment. Experimental results demonstrate that the detection accuracy of the random forest algorithm is the highest among the five machine learning models, which reaches 96.02 %. Therefore, the proposed sleep posture detection method based on the flexible sleep monitoring belt is feasible and effective.