Capacitive Sensor Research Articles

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.

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.

Microstructured Self-Healing Flexible Tactile Sensors Inspired by Bamboo Leaves.

Wearable electronic devices with multifunctions such as flexible, integrated, and self-powered play a crucial role in the fields of health monitoring, motion monitoring, and human-computer interaction. However, their core basic components, flexible pressure sensors, face challenges including poor long-term stability and insufficient real-time sensing accuracy. In order to solve the challenges of long-term, stable, and accurate sensing of the sensor, this paper prepares polydimethylsiloxane (SHPDMS) with intrinsic self-healing property and designs a high-sensitivity self-healing capacitive flexible pressure sensor with dual microstructures (grating microstructured electrodes and microporous dielectric layer) as the substrate based on SHPDMS. Specifically speaking, the self-healing of the sensor under mild conditions was realized by introducing reversible imine bonds with low bonding energy into the polydimethylsiloxane (PDMS) flexible substrate, which solved the problem of the material's long-term service durability. A grating-like microstructure was introduced into the flexible electrode by using a spotted bamboo taro leaf as a template, and a dual microstructure sensor was constructed by combining it with a microporous dielectric layer doped with single-walled carbon nanotubes. This way reduces the elastic modulus of the dielectric layer, improves the dielectric constant of the sensor under loading, and thus significantly improves the sensor's sensitivity and extends the measurement accuracy in a low-stress range. The prepared self-healing flexible sensor achieves a sensitivity of 3.6 kPa-1, a minimum detection limit of 5 Pa, a response recovery time of less than 80 ms, and stability over 5000 cycles, which exceeds most previously reported silicone rubber-based capacitive flexible sensors.

One-Dimensional Flexible Capacitive Sensor with Large Strain and High Stability for Human Motion Monitoring.

Flexible capacitive sensors have attracted the attention of researchers owing to their simple structure, ease of realization, and wearability. Currently, flexible capacitive sensors mainly have three-dimensional and two-dimensional structures, which are subject to several limitations in their applications. A low-cost, high-efficiency, and continuously processable process was used to wrap nylon DTY (PA) filaments on the surface of silver-coated nylon (SCN) core yarns and impregnate them with waterborne polyurethane (WPU) to obtain SCN/PA/WPU composite yarns, which were then utilized in the design of SCN/PA/WPU for the preparation of one-dimensionally structured flexible capacitive sensors. The morphology and mechanical properties of the SCN core yarn, SCN/PA wrapped yarn, and SCN/PA/WPU composite yarn were characterized. The strain-sensing performance of the sensor was analyzed, and the sensor was used to monitor human physiological activities. The sensor exhibited excellent strain capacitance sensing performance with a strain range of up to 140%. With a gauge factor of 0.66 at 10% tensile strain, it can detect strains as low as 1% and has good repeatability, withstanding more than 3200 tensile-unload cycles at 80% strain. The one-dimensional structure sensor can be used to monitor the large-scale movements of joints and muscles in various parts of the human body and the physiological signals of tiny human movements, such as breathing, coughing, and facial expressions, which have potential applications in the fields of sports monitoring and smart wearable.

High-Performance Supercapacitive Pressure Sensors via Height-Grading Micro-Domes of Ionic Conductive Elastomer.

Soft capacitive sensors present numerous appealing characteristics, including simple structure, low power consumption, and fast response. However, they often suffer from low sensitivity and a limited linear sensing range. Herein, a concept is presented to enhance the sensitivity and linearity of supercapacitive pressure sensors by functionally grading the heights of macrodomes constructed from a highly elastic and ionic conductive elastomer made of poly(vinyl alcohol) and phosphoric acid (PVA/H3PO4). The resultant supercapacitive sensors exhibit a high sensitivity (423.42 kPa-1), wide linear sensing range (0-400 kPa), ultralow limit of detection (0.48 Pa), and high durability (stable signal outputs up to 5000 cycles of loading/unloading). Additionally, the sensors can maintain consistent sensing performance within a temperature range of 25-40 °C. The potential of the sensor in health monitoring is demonstrated through ultrahigh-resolution weight measurement, pulse detection, and respiration monitoring.

Theoretical development and validation of asphalt concrete density measurement using non-contact interdigital coplanar capacitive sensor

Asphalt concrete (AC) density serves as a critical criterion for quality control and quality assurance in asphalt pavement construction. Current non-destructive testing (NDT) approaches have shown potential for AC density measurement, but they present disadvantages such as inefficiency and unstable accuracy. This paper developed a novel NDT approach for AC density measurement based on non-contact interdigital coplanar capacitive sensor (ICCS). The feasibility of this approach was evaluated through both numerical and experimental validations. Firstly, the theoretical model of non-contact ICCS for AC density measurement was established based on conformal mapping technique, partial capacitance technique, and dielectric mixing model. Secondly, numerical simulations were performed to validate the developed theoretical model under two scenarios. Thirdly, laboratory experiments were conducted to measure capacitance data and predict density for three common types of ACs. Finally, the error of non-contact ICCS was discussed and compared with that of other NDT instruments. The results indicated that the developed theoretical model could establish the relationship between AC density and capacitance value, which provided the basis for AC density measurement using non-contact ICCS. It was also observed that the capacitance data obtained by the proposed model closely matched those computed by numerical simulations. The maximum errors between theoretical and numerical data were 4.10% and 1.08% for two cases respectively, which proved the feasibility of the theoretical model. Furthermore, experimental results indicated that the capacitance value of AC specimens increased by about 1 pF as the rolling time increases due to a decrease in the volume of air in AC, which reaffirms the validity of AC density measurement using non-contact ICCS. Additionally, the non-contact ICCS demonstrated excellent accuracy with a maximum error of 6.69%, which is comparable to the current mainstream NDT approaches. And it has the advantages of lower cost, simpler data processing and higher efficiency. The findings of this paper offer a new and reliable method and tool for non-destructive and large-scale AC density measurement.

E-waste driven eco-friendly highly sensitive wearable capacitive sensors for physical activity monitoring and sign language recognition

Owing to the continual and rapid advancement in technology, there has been a significant surge in electronic waste (e-waste) in recent decades, resulting in a harmful impact on our environment. Due to the growing demand for battery-powered devices, non-rechargeable batteries are a significant source of e-waste. This study describes fabricating a paper-based graphite strain sensor that is eco-friendly, inexpensive, biodegradable, and sensitive to the applied strain. Readily accessible materials are employed to design and fabricate MIDC strain sensors. The Modified Interdigital Capacitor (MIDC) structure is formed on basic printing paper, and the conductive substance made with the ink of a gel pen and graphite from a drained dry cell is painted on the paper and used as electrode material. The suggested sensor has a high gauge factor value of 1998.578 and fast response and recovery time of 112 ms and 100 ms, respectively. The proposed prototype has also been utilized to inspect fitness exercises and physical activities on the human body, inspiring the potential for its integration into wearable systems for various applications. Reliable detection and differentiation of finger positions are achieved, highlighting the sensor's potential for more advanced sign language applications. It’s a good option to integrate the suggested strain sensor in wearable systems, such as telemedicine systems, electromechanical detection, healthcare, and physical activity monitoring of humans.

Enhancing sensitivity in wireless capacitive pressure sensors via highly flexible LC circuits utilizing porous polydimethylsiloxane dielectric layer

In this study, we introduce a highly flexible LC circuit-based wireless capacitive pressure sensor (CPS) that utilizes porous polydimethylsiloxane (PDMS) as a dielectric layer, demonstrating its transformative potential in tactile sensing, physiological monitoring, and flexible electronics. To optimize sensor performance, various porous PDMS thin films (100 μm) with different porosities (ranging from 0 % to 75 %) were prepared using a novel steaming method, and their properties were thoroughly analyzed using field emission scanning electron microscopy (FE-SEM) and capacitance measurements. Remarkably, the sensor with a 75 % porous PDMS film demonstrated enhanced sensitivity up to 11 times compared to the 0 % porous (pristine) PDMS film when subjected to a 300 g weight. High sensitivities of 0.046 kPa^-1, 0.036 kPa^-1, and 0.028 kPa^-1 were attained for the pressure sensor in the pressure ranges of 0–9.8 kPa, 0–19.6 kPa, and up to 29.4 kPa, respectively. Additionally, a real-time resonance frequency analysis was conducted using a network analyzer, allowing the detection of tiny pressure changes in an artificial blood vessel. Finally, the flexibility of the wireless CPS was investigated by studying various parameters, including body temperature, facial expressions such as smiling, selected speech characters (M, N, T, L), and swallowing actions.

Self‐Powered Iontronic Capacitive Sensing Unit with High Sensitivity in Charge‐Output Mode

AbstractThe operation of iontronic capacitive sensors typically requires an external alternating current (AC) power source, resulting in additional energy consumption and AC‐frequency‐related sensing performance. Here, a class of self‐powered iontronic capacitive sensing units (SICSUs) is proposed based on a dynamic electric double layer (EDL), with a significant charge sensitivity of up to 24270 pC N−1, surpassing most piezoelectric materials by nearly 10 times. The effects of various design parameters and loading conditions on the sensing performance of the SICSUs are systematically investigated. The EDL at the hydrogel‐electrode interface is characterized in situ, revealing the underlying mechanism for high sensitivity and linearity. The capability of SICSUs in detecting diverse human‐related mechanical loads is demonstrated. Furthermore, a robotic hand equipped with a SICSU‐based artificial algesia sensor is fabricated to mimic the withdrawal reflex behavior of a human hand when its skin detects noxious stimuli caused by sharp objects.

Enabling High Strength and Toughness Polyurethane through Disordered-Hydrogen Bonds for Printable, Recyclable, Ultra-Fast Responsive Capacitive Sensors.

The rapid advancement of smart, flexible electronic devices has paralleled a surge in electronic waste (e-waste), exacerbating massive resource depletion and serious environmental pollution. Recyclable materials are extensively investigated to address these challenges. Herein, this study designs a unique polyurethane (SPPUs) with ultra-high strength up to 60MPa and toughness of 360MJ m-3. This synthetic SPPUs can be fully recycled at room temperature by using green solvents of ethanol. Accordingly, the resultant SPPU-Ni composites, created by mixing the ethanol-dissolved SPPUs solution with nickel (Ni) powder, effectively combine the flexibility and recyclability of SPPUs with the electrical conductivity of the nickel filler. Notably, this work develops the printable capacitive sensors (PCBS) through transcribing the paste of SPPUs-Ni slurry onto PET film and paper using screen-printing technology. The devised PCBS have fast response time ≈50ms, high resolution, and multiple signal recognition capabilities. Remarkably, SPPUs and Ni powder can be fully recycled by only dissolving the waste PCBS in ethanol. This work offers a sustainable solution to the growing e-waste problem in recyclable flexible electronics.

Design of a Capacitive Tactile Sensor Array System for Human-Computer Interaction.

This paper introduces a novel capacitive sensor array designed for tactile perception applications. Utilizing an all-in-one inkjet deposition printing process, the sensor array exhibited exceptional flexibility and accuracy. With a resolution of up to 32.7 dpi, the sensor array was capable of capturing the fine details of touch inputs, making it suitable for applications requiring high spatial resolution. The design incorporates two multiplexers to achieve a scanning rate of 100 Hz, ensuring the rapid and responsive data acquisition that is essential for real-time feedback in interactive applications, such as gesture recognition and haptic interfaces. To evaluate the performance of the capacitive sensor array, an experiment that involved handwritten number recognition was conducted. The results demonstrated that the sensor accurately captured fingertip inputs with a high precision. When combined with an Auxiliary Classifier Generative Adversarial Network (ACGAN) algorithm, the sensor system achieved a recognition accuracy of 98% for various handwritten numbers from "0" to "9". These results show the potential of the capacitive sensor array for advanced human-computer interaction applications.

Spiking Neural Network Pressure Sensor.

Von Neumann architecture requires information to be encoded as numerical values. For that reason, artificial neural networks running on computers require the data coming from sensors to be discretized. Other network architectures that more closely mimic biological neural networks (e.g., spiking neural networks) can be simulated on von Neumann architecture, but more important, they can also be executed on dedicated electrical circuits having orders of magnitude less power consumption. Unfortunately, input signal conditioning and encoding are usually not supported by such circuits, so a separate module consisting of an analog-to-digital converter, encoder, and transmitter is required. The aim of this article is to propose a sensor architecture, the output signal of which can be directly connected to the input of a spiking neural network. We demonstrate that the output signal is a valid spike source for the Izhikevich model neurons, ensuring the proper operation of a number of neurocomputational features. The advantages are clear: much lower power consumption, smaller area, and a less complex electronic circuit. The main disadvantage is that sensor characteristics somehow limit the parameters of applicable spiking neurons. The proposed architecture is illustrated by a case study involving a capacitive pressure sensor circuit, which is compatible with most of the neurocomputational properties of the Izhikevich neuron model. The sensor itself is characterized by very low power consumption: it draws only 3.49 μA at 3.3 V.

Design optimization of a phase-change capacitive sensor for irreversible temperature threshold monitoring and its eco-friendly and wireless implementation

Monitoring the temperature of perishable goods during transport and storage is essential to prevent waste and maintain product quality. Exploiting the unique property of phase-change materials (PCM), altering their physical state at specific temperatures, we optimize a capacitive sensor design based on a copper on polyimide interdigitated spiral (IDE) structure coated with a PCM to irreversibly detect temperature thresholds. The effect of the sensor dimensioning on its response is analyzed using a finite element model simulation. The model predicted up to 51% capacitance variation for optimal coverage of the PCM after spreading over the IDE, which was validated experimentally within a 5% error. Two melting concepts utilizing the spreading or the removal of the melted PCM over the IDE are investigated based on a capillary retention mechanism to maintain sensor sensitivity under inclination. Finally, an eco-friendly implementation of the capacitive structure and its wireless operation at 460 MHz is demonstrated on paper with a printed zinc transducer passivated with beeswax and covered with jojoba oil. Melting of the oil at a threshold temperature of 12.3 °C resulted in an irreversible shift in resonance frequency of 14 MHz. This study provides guidelines for the design and implementation of irreversible temperature monitoring capacitive sensors.

A Novel Wearable Sensor for Measuring Respiration Continuously and in Real Time.

In this work, a flexible textile-based capacitive respiratory sensor, based on a capacitive sensor structure, that does not require direct skin contact is designed, optimised, and evaluated using both computational modelling and empirical measurements. In the computational study, the geometry of the sensor was examined. This analysis involved observing the capacitance and frequency variations using a cylindrical model that mimicked the human body. Four designs were selected which were then manufactured by screen printing multiple functional layers on top of a polyester/cotton fabric. The printed sensors were characterised to detect the performance against phantoms and impacts from artefacts, normally present whilst wearing the device. A sensor that has an electrode ratio of 1:3:1 (sensor, reflector, and ground) was shown to be the most sensitive design, as it exhibits the highest sensitivity of 6.2% frequency change when exposed to phantoms. To ensure the replicability of the sensors, several batches of identical sensors were developed and tested using the same physical parameters, which resulted in the same percentage frequency change. The sensor was further tested on volunteers, showing that the sensor measures respiration with 98.68% accuracy compared to manual breath counting.

Flexible wide-range, sensitive three-axis pressure sensor array for robotic grasping feedback

Flexible pressure sensors capable of detecting normal and tangential forces through physical contact have garnered considerable interest in the realm of human-interactive systems. However, simultaneous detection of multi-directional forces is still a challenge for current research. Herein, a capacitive flexible pressure sensor based on a sandwich structure for three-dimensional force detection is proposed. The fabrication process of the sensor array is straightforward, capable of effectively distinguishing between normal and tangential forces. Polyimide (PI) serves as the flexible substrate for depositing the metal electrode pattern, while Polydimethylsiloxane (PDMS) acts as the intermediate dielectric layer material and the three-dimensional force conduction block. Through a comparative study of the thickness of the hollow dielectric layer, a pressure sensor with superior performance was prepared, featuring high sensitivity across a wide working range. Test results demonstrate its capability to detect normal forces ranging from 0 to 46 N (0–520 kPa) with a sensitivity of 0.442 N−1 (0.031 kPa−1) and tangential forces from 0 to 10 N with a sensitivity of 0.08 N−1 (X-axis) and 0.07 N−1 (Y-axis). The designed acquisition system can simultaneously gather data from 6 sensor arrays, totaling 240 channels, with a response time of 11 ms. This sensor array, characterized by flexibility, versatility, and a wide range, is suitable for applications in robot tactile perception.

Highly robust electronic skin for object recognition of robot hand based on carbon nanomaterials and SEBS

When robot hands work in a complex environment, they not only need to sense the objects in contact but also need to respond to remote events before physical contact. In this way, robot hands can make predictions, to better adapt to the complex environment. In this paper, we have designed a flexible sensor array, which integrates a piezoresistive sensor and a capacitive sensor for detecting pressure and proximity direction and distance signals simultaneously. Piezoresistive sensors can detect pressure signals in real-time, and capacitive sensors detect pressure and proximity signals. The sensors are arranged in a patterned array and installed on the robot hand to help the robot hand detect the distance and direction of approaching objects, as well as the shape and size of the grasped objects. To avoid mechanical mismatch, piezoresistive sensors and capacitive sensors are fabricated with the same flexible materials. In addition, after extreme pressure tests, the sensors can still work normally, to ensure that the robot hands can work normally after collision. We also combined the detected signal with machine learning, so that the robot can accurately identify objects of different shapes. In the fruit recognition test, the recognition accuracy reached 90 %.

Additively manufactured micro-lattice dielectrics for multiaxial capacitive sensors.

Soft sensors that can perceive multiaxial forces, such as normal and shear, are of interest for dexterous robotic manipulation and monitoring of human performance. Typical planar fabrication techniques have substantial design constraints that often prohibit the creation of functionally compelling and complex architectures. Moreover, they often require multiple-step operations for production. Here, we use an additive manufacturing process based on continuous liquid interface production to create high-resolution (30-micrometer) three-dimensional elastomeric polyurethane lattices for use as dielectric layers in capacitive sensors. We show that the capacitive responses and sensitivities are highly tunable through designs of lattice type, thickness, and material-void volume percentage. Microcomputed tomography and finite element simulation are used to elucidate the influence of lattice design on the deformation mechanism and concomitant sensing behavior. The advantage of three-dimensional printing is exhibited with examples of fully printed representative athletic equipment with integrated sensors.

Investigation and analysis of MEMS based capacitive sensor’s characteristics with the effect of electrode pattern

Investigation and analysis of MEMS based capacitive sensor’s characteristics with the effect of electrode pattern