Capacitive Sensor Research Articles

A Capacitive Pressure Sensor With Adjustable Working Range for Deep Sea

A Capacitive Pressure Sensor With Adjustable Working Range for Deep Sea

Stabilizing Metal Coating on Flexible Devices by Ultrathin Protein Nanofilms.

The significant modulus difference between a metal coating and a polymer substrate leads to interface mismatches, seriously affecting the stability of flexible devices. Therefore, enhancing the adhesion stability of a metal layer on an inert polymer substrate to prevent delamination becomes a key challenge. Herein, an ultrathin protein nanofilm (UPN), synthesized by disulfide-bond-reducing protein aggregation, is proposed as a strong adhesive layer to enhance adhesion between polymer substrate and metal coating. Unlike traditional biopolymer adhesives with micrometer-scale thicknesses, the UPN layer is minimized to nanometer/single-molecular scale. Such UPN thereby effectively enhances the interfacial adhesive strength and reduces the cohesion contribution in the entire adhesion system by directly connecting two interfaces with a nearly single-molecular thickness. Using UPN as the adhesive layer, a multifunctional metal coating could be reliably adhered on flexible polymer substrates by ion sputtering, delivering unprecedented adhesion stability even under repetitive mechanical deformation. Applications of this design include reversible transparency control, tension-responsive encryption, reusable optical sensing, and wearable capacitive touch sensors. This work highlights UPN's potential to create strong bonding strength between flexible polymers and metal coatings, offering a biocompatible solution with high surface activity and low cohesion, facilitating the development of hybrid devices with stable metal nano-coating.

Application of machine learning for reconstruction of multiphase fluid structure measured by a capacitance multi-electrode sensor

Non-invasive real-time measurements of phase content in the reservoir fluid are highly advantageous in the oil and gas industry and remain a current research topic. The paper presents an innovative, self-designed multi-electrode capacitance meter intended for detecting multiphase flow patterns in a low-permittivity medium, such as the reservoir fluid. The ca-pacitance sensor is built with delta-sigma charge modulators capacitance-to-digital converters. Machine learning is applied to convert the capacitance measurements into a tomographic image of the flow pattern. At present, the meter is built with eight electrodes. It is shown that the measurements are repeatable and have a good signal-to-noise ratio. The implemented neural network is capable of correctly reconstructing the tomographic images for a test tube filled with reservoir fluid and placed in various locations inside the test section.

Stretchable and High-Performance Fibrous Sensors Based on Ionic Capacitive Sensing for Wearable Healthcare Monitoring.

Electronic textiles with remarkable breathability, lightweight, and comfort hold great potential in wearable technologies and smart human-machine interfaces. Ionic capacitive sensors, leveraging the advantages of the electric double layer, offer higher sensitivity compared to traditional capacitive sensors. Current research on wearable ion-capacitive sensors has focused mainly on two-dimensional (2D) or three-dimensional (3D) device architectures, which show substantial challenges for direct integration with textiles and compromise their wearing experience on conformability and permeability. One-dimensional (1D) stretchable fiber materials serve as vital components in constructing electronic textiles, allowing for rich structural design, patterning, and device integration through mature textile techniques. Here, a stretchable functional fiber with robust mechanical and electrical performances is fabricated based on semi-solid metal and ionic polymer, which provided a high stretchability and good electrical conductivity, enabling seamless integration with textiles. Consequently, high-performance stretchable fiber sensors are developed through different device architecture designs, including pressure sensors with high sensitivity (7.21kPa-1), fast response (60ms/30ms), and excellent stability, as well as strain sensors with high sensitivity (GF = 1.05), wide detection range (0-300% strain), and excellent sensing stability under dynamic deformations.

AI-Based Evaluation of Homogeneous Flow Volume Fractions Independent of Scale Using Capacitance and Photon Sensors

Metering fluids is critical in various industries, and researchers have extensively explored factors affecting measurement accuracy. As a result, numerous sensors and methods are developed to precisely measure volume fractions in multi-phase fluids. A significant challenge in multi-phase fluid pipelines is the formation of scale within the pipes. This issue is particularly problematic in the petroleum industry, leading to narrowed internal diameters, corrosion, increased energy consumption, reduced equipment lifespan, and, most crucially, compromised flow measurement accuracy. This paper proposes a non-destructive metering system incorporating an artificial neural network with capacitive and photon attenuation sensors to address this challenge. The system simulates scale thicknesses from 0 mm to 10 mm using COMSOL multiphysics software and calculates counted rays through Beer Lambert equations. The simulation considers a 10% interval of volume variation in each phase, generating 726 data points. The proposed network, with two inputs—measured capacity and counted rays-and three outputs—volume fractions of gas, water, and oil—achieves mean absolute errors of 0.318, 1.531, and 1.614, respectively. These results demonstrate the system’s ability to accurately gauge volume proportions of a three-phase gas-water-oil fluid, regardless of pipeline scale thickness.

Comprehensive and Robust Anti-Jamming Dual-Electrode Pair Sensor.

Capacitive flexible sensors often encounter instability caused by temperature fluctuations, electromagnetic interference, stray capacitance effects, and signal noise induced by ubiquitous vibrations. The challenge lies in achieving comprehensive anti-jamming abilities while preserving a simplistic structure and manufacturing process. To tackle this dilemma, a straightforward and effective design is utilized to achieve comprehensive and robust anti-jamming properties in capacitive sensors. Electrospinning thermoplastic polyurethane (TPU) fiber mats soak with ionic liquid (IL) to create a co-continuous structure (TPU@IL) with high ionic conductivity and dielectric constant, which acts as the sensing units. The sensing mechanism of the TPU@IL with multiple electrode pairs encapsulated by polyethylene terephthalate (PET) is systematically elucidated. The optimal dual-electrode pair design for capacitive and resistive sensors, which have different sensitivities to temperature and stress, simultaneous realizes temperature-stress dual-mode sensing. Remarkably, the sensitivity curve of the TPU@IL/PET capacitive sensor exhibits an intriguing rarely reported S-shape with an adjustable step stress point. No liquid leakage even during extensive stress-strain cycling (>4000 cycles). Despite a slight compromise in sensitivity and response time, the TPU@IL/PET sensor demonstrates exceptional electromechanical stability, reliability, and powerful anti-jamming abilities against various interferences. A simple yet innovative sensor design enhances the performance and applicability of capacitive sensors in challenging environments.

Active micro-vibration isolation system for adaptive vibration suppression tests using piezoelectric stack actuator

An active micro-vibration isolation system for adaptive vibration suppression using piezoelectric stack actuators is presented, along with the discrete time modelling method, real-time adaptive controller design, and hardware implementation. The system comprises piezoelectric stack actuators, capacitive displacement sensors, power amplifiers, signal conditioners, and a real-time computer. A discrete asymmetric Bouc-Wen model is developed to characterize the nonlinear behavior of the piezoelectric stack actuators. System identification is conducted using an improved particle swarm optimization method, specifically the Hybrid PSO-Jaya algorithm, which sequentially integrates the PSO algorithm with the Jaya algorithm. Additionally, an improved adaptive filtering algorithm employing affine projection, referred to as the FXAPA algorithm, is introduced to facilitate real-time control. The efficacy of the proposed active micro-vibration isolation technology is validated through micro-vibration suppression tests.

2D heterostructures of graphene oxide and MoS2 to improve sensitivity performance of flexible pressure sensor with shell biological structure

Inspired by the multilayer structure of the shellfish, a novel two-dimensional (2D) composite structure consisting of graphene oxide, MoS2 and graphene oxide (G/M/G) was integrated to the flexible pressure sensing. The composite structure was prepared by the vacuum suction filtration in order to imitate the high toughness of shellfish. Based on the strategy of strain engineering, a comprehensive experimental bench capable of meeting different strain conditions was connected to a push–pull meter and an LCR digital bridge, and then a computer was used to record the changes in transducer capacitance when an external load was applied to the meter. Graphene oxide (GO) and G/M/G supercells were constructed, and density functional theory (DFT) simulations of the initial energy band structure under strain-free conditions were carried out to determine the relationship between the band gap, conductivity, capacitance, and sensitivity of the G/M/G structure based on band gap theory, and to easily understand the mechanism of the shellfish heterostructure leading to enhanced sensitivity of the sensors. Using two-point bending and axial tensile tests, a flexible pressure sensing device was designed to realize positive strains in the ranges of 0%–5 % and 5%–50 %. The results show that the sensitivity of both GO and G/M/G capacitive pressure sensors decreased with increased strain, and the sensitivity of the G/M/G sensors was significantly improved by 75%–102 % compared to the GO sensors at the same strain. The parallel-plate capacitor model and crack growth theory well explain the experimental results at small and large strains. Our results provide new concepts for the design of novel flexible sonar with high sensitivity and large strain operating range by a simple vacuum filtration method, which can be extended to the design of other high-performance 2D flexible electronic devices.

Humidity Sensing Using Polymers: A Critical Review of Current Technologies and Emerging Trends

In the post-pandemic era, human demand for a healthy lifestyle and a smart society has surged, leading to vibrant growth in the field of flexible electronic sensor technology for health monitoring. Flexible polymer humidity sensors are not only capable of the real-time monitoring of human respiration and skin moisture information but also serve as a non-contact human–machine interaction method. In addition, the development of moist-electric generation technology is expected to break free from the traditional reliance of flexible electronic devices on power equipment, which is of significant importance for the miniaturization, reliability, and environmentally friendly development of flexible devices. Currently, flexible polymer humidity sensors are playing a significant role in the field of wearable electronic devices and thus have attracted considerable attention. This review begins by introducing the structural types and working principles of various humidity sensors, including the types of capacitive, impedance/resistive, frequency-based, fiber optic, and voltage-based sensors. It mainly focuses on the latest research advancements in flexible polymer humidity sensors, particularly in the modification of humidity-sensitive materials, sensor fabrication, and hygrosensitivity mechanisms. Studies on material composites including different types of polymers, polymers combined with porous nanostructured materials, polymers combined with metal oxides, and two-dimensional materials are reviewed, along with a comparative summary of the fabrication and performance mechanisms of related devices. This paper concludes with a discussion on the current challenges and opportunities faced by flexible polymer humidity sensors, providing new research perspectives for their future development.

Customized flexible iontronic pressure sensors: Multilevel microstructures by 3D-Printing for enhanced sensitivity and broad pressure range

Flexible capacitive pressure sensors stand out for their energy efficiency, rapid responsiveness, and exceptional durability, with their performance hinging on the intricate design of microstructures and the strategic selection of dielectric materials. However, creating cost-effective and practical fabrication methods for these components continues to pose a significant challenge. This study unveils an innovative iontronic flexible pressure sensor that integrates an ionic layer with sophisticated multilayer microstructures, setting new benchmarks in pressure sensing technology. The sensor operates within an expansive pressure range, achieving sensitivities as high as 92.14 kPa−1 at pressures from 0 to 50 kPa, and 22.96 kPa−1 at pressures ranging from 50 to 800 kPa, demonstrating extraordinary sensitivity. It also achieves an exceptionally low detection limit of 6.67 Pa and features swift response times of 56 ms to activate and 18 ms to deactivate. Enhanced by the addition of CuSO4, the sensor not only withstands freezing conditions but also significantly boosts sensitivity. Moreover, this sensor is capable of detecting human joint movements and subtle pressure fluctuations under high-pressure conditions, suggesting a breakthrough in the field. This research presents a simple, reliable, and cost-efficient method for developing flexible iontronic pressure sensors, poised to revolutionize applications in wide-ranging pressures and adverse temperature environments.

Stretchable carbon Nanotube/Ecoflex conductive elastomer films toward multifunctional wearable electronics

Conductive elastomer films (CEFs) have found widespread applications toward flexible electronics and wearable devices. Silicones are particularly advantageous for fabricating high-performance CEFs. However, processing silicone/conductive filler composite prepolymers is challenging because of their high viscosity, especially when incorporating nanofillers like carbon nanotubes (CNTs) that can greatly increase the viscosity of silicone prepolymers. Herein, we present a simple, facile and versatile hexane-assisted air-spraying method for fabricating silicone-based CEFs from Ecoflex and CNTs. This method allows for processing CNT/Ecoflex prepolymers with CNT concentrations of 0.5 ∼ 5 wt%, resulting in stretchable CEFs with controllable structural, mechanical and electrical properties. We leveraged the distinct advantages of CNT/Ecoflex CEFs, including the excellent mechanoelectrical sensitivity, workable strain range and elasticity of the CNT1/Ecoflex group, and the high conductivity and low mechanoelectrical sensitivity of the CNT5/Ecoflex group. These properties enable their multifunctional applications as wearable and waterproof resistive strain sensors, multilayered capacitive pressure sensors, and wearable electric heaters. This work provides valuable insights into the development of high-performance and multifunctional silicone-based composite materials for advanced wearable electronics.

Control and monitor bottle filling, capping and labelling machine using a programmable logic controller and human machine interface

Bottle filling, closing, and labellingmachine control and monitoring tool using Programmable Logic Controller (PLC) and Human-Machine Interface (HMI). This tool is designed to optimize the production process in the bottled beverage industry,with dimensions of 200 cm × 70 cm × 100 cm. The conveyor transports bottles through the filling, capping, and labeling units. In each unit, sensors are installed to detect the presence of bottles. Bottle liquid volume is determined through time settings inputted through the HMI,and the filling is performed by a water pump. After filling, bottles are capped and tightened mechanically using an air impact system. Labeling is handled by two DC motors which unroll the label and rotate the bottle, ensuringthe label adheres evenlyto all sides of the bottle. The number of bottles produced is calculated using a capacitive proximity sensor and displayed on the HMI. Testing results show that the system effectivelycontrols and monitors the bottle filling, capping, and labeling process viaPLC and HMI. Based on the test results on the bottle filling unit, the system can fill water into the bottle with a maximum percentage error of 0.5% on a 1000 ml volume bottle. In the capping unit, the success rate achieved is 70%, while the success rate in the bottle labeling unit is 80%.

3D-Printed Multi-Axis Alignment Airgap Dielectric Layer for Flexible Capacitive Pressure Sensor

Flexible pressure sensors are increasingly recognized for their potential use in wearable electronic devices, attributed to their sensitivity and broad pressure response range. Introducing surface microstructures can notably enhance sensitivity; however, the pressure response range remains constrained by the limited volume of the compressible structure. To overcome this limitation, this study implements an aligned airgap structure fabricated using 3D printing technology. This structure, designed with a precisely aligned triaxial airgap configuration, offers high deformability under pressure, substantially broadening the pressure response range and improving sensitivity. This study analyzes the key structural parameters—the number of axes and pore size—that influence the compressibility and stability of the dielectric material. The results indicate that the capacitive pressure sensor with an aligned airgap structure, manufactured via 3D printing, exhibits a wide operating pressure range (50 Pa to 500 kPa), rapid response time (100 ms), wide limit of detection (50 Pa), and approximately 21 times enhancement in sensitivity (~0.019 kPa−1 within 100 kPa) compared with conventional bulk structures. Furthermore, foot pressure monitoring trials for wearable sensor applications demonstrated exceptional performance, indicating the sensor’s suitability as a wearable device for detecting plantar pressure. These findings advocate for the potential of 3D printing technology to supplant traditional sensor manufacturing processes.

Enhancing Sensing Performance of Capacitive Sensors Using Kirigami Structures.

Capacitive sensors have widespread applications in human-machine interaction, Internet of Things, and smart home systems due to their low cost, high sensitivity, and ease of integration. However, improving the sensitivity and sensing distance of capacitive sensors remains a challenging issue. This study proposes a novel capacitive sensor design method based on Kirigami structures, which enhances sensor performance by introducing specific cutting patterns into the conductive layer to leverage edge effects. Through experimental testing and statistical analysis, we systematically investigated the influence of Kirigami geometric parameters on sensor sensitivity and sensing distance. We designed and fabricated 12 different Kirigami structures, including circular flower patterns, array patterns, layered pointed flower patterns, and circular strip structures, and compared them with traditional non-cut structures. The results show that Kirigami structures significantly improved sensor performance. Compared to traditional sensors without Kirigami structures, optimally designed Kirigami capacitive sensors demonstrated approximately a 3-fold increase in sensitivity and up to 170 percent extension in sensing distance. Multivariate regression analysis and nonlinear models revealed complex relationships between Kirigami structural parameters and sensor performance. Notably, the circular strip (three-layer) structure exhibited the best performance, possibly due to its maximization of edge effects and optimization of electric field distribution. This study provides new design insights for developing high-performance capacitive sensors, with potential applications in improving smart home systems and indoor activity monitoring for solitary elderly individuals.

Optimal design parameter estimation and analytical investigation of MEMS quadruple touch mode capacitive pressure sensor

Purpose Touch mode capacitive pressure sensors (TMCPS) offer superior sensitivity and linearity in comparison to normal mode CPS and have therefore seen substantial improvements in modeling and construction. This study aims to develop a sensor that is highly robust, with near-linear output characteristics, increased sensitivity and superior overload protection, making it an ideal choice for deployment in harsh industrial environments. Design/methodology/approach The proposed sensor design uses a substrate with a multi-step notch, introducing a new quadruple TMCPS and uses a small deflection model for mathematical analysis. Addition of a multi-step notch to traditional touch mode capacitive sensors results in quadruple touch regions which further enhances its operational range performance. Findings The simulation of diaphragm deflection in response to pressure is carried out by using COMSOL Multiphysics, whereas MATLAB is used for analytical simulations pertaining to variations in capacitance and capacitive sensitivity. Comparing with earlier models, there is a noticeable enhancement in capacitance, experiencing a fivefold increase. The achieved value stands at 50.1 pF, reflecting improved sensitivity for applied pressure ranging from 0 to 2 MPa. Originality/value In existing literature to improve the performance of the single TMCPS, a double-sided TMCPS has been developed. To enhance sensor performance, a substrate with a multi-step notch is proposed. The notch creates four touch regions with varying gap depths, resulting in increased capacitance and capacitive sensitivity.

MEMS capacitive pressure sensor: analysis, theoretical modeling, simulation and performance comparison of the effect of a conical notch

Abstract Micro-Electro-Mechanical Systems (MEMS) pressure sensors are widely used in various applications due to their high sensitivity, low power consumption, and compactness. This work involves the design and simulation of a MEMS-based Touch Mode Capacitive Pressure Sensor (TMCPS). The proposed sensor is based on a substrate with an integrated conical notch featuring a circular diaphragm, aiming to enhance the key performance parameters of the sensor. The integration of a conical notch in the substrate increases the touch area between the diaphragm and substrate compared to the literature, ensuring increased capacitance and capacitive sensitivity. In this work the mathematical analysis of deflection of a circular diaphragm employing thin plate theory, capacitance, and capacitive sensitivity, along with step-by-step explanations, is provided. The results are obtained from MATLAB simulations. The deflection of the diaphragm is validated through Finite Element Analysis (FEA) using COMSOL Multiphysics. The proposed work demonstrates a significant improvement in sensor sensitivity compared to the existing literature.

Inductor-capacitor passive wireless sensors using nonlinear parity-time symmetric configurations

An inductor–capacitor passive wireless sensor is essential to physical, chemical, and biological sensing for scenarios where physical access is difficult. Exceptional points of parity-time symmetric inductor–capacitor systems featuring the linear loss and gain have been utilized for enhancing sensing. However, the exceptional point sensing scheme might bring about fundamental resolution limits and noise enhancement. Here we show, employing a nonlinear saturable gain, the responsivity has a cube-root singularity distinct from a square-root singularity of the linear exceptional point scheme. The saturable gain eliminates the imaginary part of the eigenfrequencies and significantly suppresses the noise. Through an example of inductor–capacitor wireless wearable temperature sensors, we demonstrate the high figure of merit for the nonlinear PT-symmetric configuration. Our results resolve a debate on the effectiveness of the exceptional point sensing scheme for inductor–capacitor sensors and provide a way of enhancing precision for these types of sensors.

Voxel Interface Control in Multimaterial Extrusion 3D Printing.

Interfaces are crucial in natural and engineered systems, dictating essential biological, ecological, and technological properties that augment performance, functionality, and user experience. Yet, achieving precise interfacial control poses significant challenges in both conventional and additive manufacturing, where scalability constraints impede the controlled deposition of quasi-2D layers within 3D objects. This paper introduces Voxel-Interface 3D Printing (VI3DP), which enables comprehensive control over extruded voxel interfaces irrespective of the printhead diameter that conventionally dictates feature size. Various optical, mechanical, and electrical functionalizations, attaining interface thicknesses up to three orders of magnitude smaller than the voxel size are reported. Notable applications include encoding data in soft matter through fluorescent interfaces, creating tight fits and movable mechanisms through non-adhesive interfaces, fabricating bio-inspired composites with tailored failure modes, and developing a single filament capacitive touch sensor. VI3DP opens new avenues for enhanced functionality and efficiency across multiple fields, including biomedical technology, electronics, optics, andnanotechnology.

Biodegradable, Self‐Adhesive, Stretchable, Transparent, and Versatile Electronic Skins Based on Intrinsically Hydrophilic Poly(Caproactone‐Urethane) Elastomer

In biomedical sciences, there is a demand for electronic skins with highly sensitive tactile sensors that have applications in patient monitoring, human–machine interfaces, and on‐body sensors. Sensor fabrication requires high‐performance conductive surfaces that are transparent, breathable, flexible, and easy to fabricate. It is also preferable if the electrodes are easily processable as wastes, for example, are degradable. In this work, the design and fabrication of hydrophilic silanol/amine‐terminated poly(caprolactone‐urethane) (SA‐PCLU) elastomer‐based breathable, stretchable, and biodegradable electrodes are reported. Ag nanowires dispersed in water are sprayed onto the intrinsically hydrophilic electrospun SA‐PCLU that became embedded into the scaffold and formed conformal hydrophilic polyurethane‐based conductive networks (HPCN). The electrodes are used to fabricate capacitive, curvature, and strain sensors, all having monomaterial composition. In addition to displaying particularly good transparencies at low sheet resistances, stretchability, hydrophilicity, and tight and conformal bonding with the target surface, the electrodes also allow the evaporation of perspiration, making them suitable for epidermal sensors for long‐time use. The application of the HPCN electrodes in flexible electronics and bionic skin applications is demonstrated through gesture monitoring experiments and swelling sensors.

Neo-Hookean modeling of nonlinear coupled behavior in circular plates supported by micro-pillars

In the contemporary era, the enhancement of wearable capacitive sensors is achieved through the utilization of polymeric micropillars as filler materials between electrode plates. To gain a deeper understanding of the dynamic response of the system, nonlinear coupled governing equations of a circular microplate motion resting on an array of polymeric micropillars have been derived. These equations are used to model the system’s behavior. In addition, the squeezing motion of the micro-pillars is characterized using the incompressible Neo-Hookean model. Both static and dynamic responses, including transient and steady-state solutions, are investigated in detail by discretizing over spatial coordinates using a weak formulation approach. A frequency response analysis is conducted using a continuation-based method. This entails expanding the steady-state solution using a Fourier transform and employing the energy balance principle. The unknown coefficients of the expansion series are calculated using a gradient descent-based learning approach that is physically motivated. Furthermore, a dynamic step size strategy for frequency increments is employed to effectively follow the solution path. This strategy is implemented via the ARC length method. In this study, we examine the impact of varying PDMS (polydimethylsiloxane) hydrogel mechanical and geometrical configurations. It can be reasonably concluded that the mechanical properties of the pillars and the geometrical configuration of the circular plate and micropillars have a significant impact on the maximum tolerable pressure, fast transient response, and frequency response analysis.