Capacitive Sensor Research Articles

Direct Ink Write 3D Printing of Fully Dense and Functionally Graded Liquid Metal Elastomer Foams

AbstractLiquid metal (LM) elastomer composites offer promising potential in soft robotics, wearable electronics, and human‐machine interfaces. Direct ink write (DIW) 3D printing offers a versatile manufacturing technique capable of precise control over LM microstructures, yet challenges such as interfilament void formation in multilayer structures impact material performance. Here, a DIW strategy is introduced to control both LM microstructure and material architecture. Investigating three key process parameters–nozzle height, extrusion rate, and nondimensionalized nozzle velocity–it is found that nozzle height and velocity predominantly influence filament geometry. The nozzle height primarily dictates the aspect ratio of the filament and the formation of voids. A threshold print height based on filament geometry is identified; below the height, significant surface roughness occurs, and above the ink fractures, which facilitates the creation of porous structures with tunable stiffness and programmable LM microstructure. These porous architectures exhibit reduced density and enhanced thermal conductivity compared to cast samples. When used as a dielectric in a soft capacitive sensor, they display high sensitivity (gauge factor = 9.0), as permittivity increases with compressive strain. These results demonstrate the capability to simultaneously manipulate LM microstructure and geometric architecture in LM elastomer composites through precise control of print parameters, while maintaining geometric fidelity in the printed design.

Polyimide aerogel-based capacitive pressure sensor with enhanced sensitivity and temperature resistance

The development of intelligent electronic power systems necessitates advanced flexible pressure sensors. Despite improved compressibility through surface micro-structures or bulk pores, conventional capacitive pressure sensors face limitations due to their low dielectric constant and poor temperature tolerance of most elastomers. Herein, we constructed oriented polyimide-based aerogels with mechanical robustness and notable changes in dielectric constant under compression. The enhancement is attributed to the doping of surface-modified dielectric nanoparticles and graphene oxide sheets, which interact with polymer molecular chains. The resulting aerogels, with their excellent temperature resistance, were used to assemble high-performance capacitive pressure sensors. The sensor exhibits a maximum sensitivity of 1.41 kPa−1 over a wide working range of 0–200 kPa. Meanwhile, the sensor can operate in environments up to 150 °C during 2000 compression/release cycles. Furthermore, the aerogel-based sensor demonstrates proximity sensing capabilities, showing great potential for applications in non-contact sensing and extreme environment detection.

Parameter Optimization and Capacitance-Based Monitoring of In Situ Cell Detachment in Microcarrier Cultures

This study delves into the scale-down optimization of the in situ cell detachment process for MA 104 cells cultivated on Cytodex 1 microcarriers (MCs). Through a systematic exploration, critical operational parameters—the agitation speed, incubation time, Trypsin–EDTA volume and corresponding activity, and washing steps—were identified as key factors influencing the efficiency and scalability of in situ cell detachment in microcarrier-based cell culture. Maintaining an appropriate agitation speed (1.25 × Njs, minimum agitation speed at which no microcarriers remain stationary for the signification period of 5 s), optimizing the Trypsinization incubation time (up to 60 min), and implementing multiple washing steps (two times) post-medium removal were found to be crucial for efficient cell detachment and subsequent growth. Our study demonstrates the feasibility of reducing the final Trypsin volume to 50 mL per gram of microcarrier while maintaining a Trypsin activity above 380 USP/mL. These conditions ensure complete cell dissociation and improve the cost effectiveness in large-scale productions. Additionally, we introduced real-time monitoring using a capacitance sensor during in situ cell detachment. This method has proven to be an effective process analytical technology (PAT) tool for tracking the cell detachment progress and efficiency. It allows for the prediction of cell detachment based on signals recorded between 3 and 7 min of Trypsinization, enabling rapid process decisions without the need for offline sampling, thereby enhancing the overall process control. This systematic approach not only optimizes in situ cell detachment processes but also has significant implications for the scalability and efficiency of microcarrier-based cell culture systems.

MXene/MWCNTs-based capacitive pressure sensors combine high sensitivity and wide detection range for human health and motion monitoring

Wearable pressure sensors with exceptional performance are playing a crucial role in various fields such as electronic skin, human motion monitoring, medical diagnosis, and human-computer interaction. However, achieving both high sensitivity and a wide sensing range with simple fabrication and low cost has proven to be a significant challenge for sensors. In this study, a simple capacitive pressure sensor is proposed that multi-walled carbon nanotubes (MWCNTs) are introduced into MXene (Ti3C2TX) as a ‘bridge’. Then the electrode which has excellent conductivity is obtained by filtration of MXene solution and MXene/MWCNTs solution at intervals. Additionally, green and degradable cellulose paper is used as the dielectric layer. The fabricated pressure sensor exhibits a high sensitivity of 4.7 kPa−1 for low pressure from 0 to 1 kPa, a wide detection range of 0–700 kPa, ultra-fast response and recovery times of 46 ms and 62 ms, respectively, and an extremely low detection limit of 0.32 Pa. The sensor remains stable even after 4500 cycles and can accurately monitor the movement of the human joints. Furthermore, it can track human physiological signals, which is beneficial for medical diagnosis and disease prevention, and has significant potential for application in the wearable technology field.

Multi‐Functional Ti3C2Tx‐Silver@Silk Nanofiber Composites With Multi‐Dimensional Heterogeneous Structure for Versatile Wearable Electronics

AbstractSilk nanofibers (SNFs) from abundant sources are low‐cost and environmentally friendly. Combined with other functional materials, SNFs can help create bioelectronics with excellent biocompatibility without environmental concerns. However, it is still challenging to construct an SNF‐based composite with high conductivity, flexibility, and mechanical strength for all SNF‐based electronics. Herein, this work reports the design and fabrication of Ti3C2Tx‐silver@silk nanofibers (Ti3C2Tx‐Ag@SNF) composites with multi‐dimensional heterogeneous conductive networks using combined in situ growth and vacuum filtration methods. The ultrahigh electrical conductivity of Ti3C2Tx‐Ag@SNF composites (142959 S m−1) provides the kirigami‐patterned soft heaters with a rapid heating rate of 87 °C s−1. The multi‐dimensional heterogeneous network further allows the creation of electromagnetic interference shielding devices with an exceptionally high specific shielding effectiveness of 10,088 dB cm−1. Besides working as a triboelectric layer to harvest the mechanical energy and recognize the hand gesture, the Ti3C2Tx‐Ag@SNF composites can also be combined with an ionic layer to result in a capacitive pressure sensor with a high sensitivity of 410 kPa−1 in a large range due to electronic‐double layer effect. The applications of the Ti3C2Tx‐Ag@SNF composites in recognizing human gestures and human‐machine interfaces to wirelessly control a trolley demonstrate the future development of all SNF‐based electronics.

Development of a Capacitive Pressure Sensor Based on Nanoporous Anodic Aluminium Oxide

Capacitive pressure sensors make pressure sensing technology more accessible to a wider range of applications and industries, including consumer electronics, automotive, healthcare etc. However, developing a capacitive pressure sensor with brilliant performance using a lowcost technique remains a difficulty. In this work, the development of a capacitive pressure sensor based on nanoporous AAO fabricated by a two-step anodization approach which offers a promising solution for precise pressure measurement is fabricated by a two-step anodization approach. A parallel plate capacitive sensor was fabricated by placing two AAO deposited sheets are placed face to face, with the non-anodized aluminum component at the base functioning as the top and bottom electrodes. A variation in the capacitance value of the as fabricated sensor was observed over an applied pressure range (100 Pa-100 kPa). This change in capacitance can be attributed to the decrease in the distance between the two plates and the non-homogenous distribution of contact stress and strain due to the presence of nanoporous AAO structure. In this pressure range the sensor showed high sensitivity, short response time and excellent repeatability which indicates a promising future of the fabricated sensor in consumer electronics, intelligent robotics etc.

A Battery‐Free Wireless Tactile Sensor for Multimodal Force Perception

AbstractMultimodal tactile sensors, as key information input channel in human‐machine interactions, have faced the significant challenges including high power‐consumption, multimodal data fusion, and wireless transmission. In this work, a battery‐free multimodal wireless tactile sensor (TC‐MWTS) based on tribo‐capacitive coupled effect for normal and shear force fusion sensing is proposed, which is enabled by a 3D structure combining a triboelectric sensor and a capacitive sensor coupled with an inductive coil. A triboelectric sensor equipped with contact‐discharge structures exhibits 25‐fold wireless signal enhancement compared to conventional triboelectric sensors. Based on the characteristics of dual time‐frequency domain information existing in the wireless signals, both normal and shear forces can simultaneously be converted into voltage amplitude V and eigenfrequency f, respectively, without crosstalk and complex decoupling signals. The TC‐MWTS exhibits a maximum sensitivity of 2.47 V kPa−1 for normal force from 2 to 30 kPa and a sensitivity of 0.28 MHz N−1 for shear force between 0.3 and 1.0 N. Finally, the excellent sensing capability of TC‐MWTS to sense complex multidimensional forces in human‐machine interaction is demonstrated. This work innovatively proposes a new mechanism and methodology for effectively fusing and processing multimodal tactile information, which may drive the tremendous development of low‐power multimodal tactile sensing system.

Field-grown lettuce production optimized through precision irrigation water management using soil moisture-based capacitance sensors and biodegradable soil mulching

AbstractScientists, environmentalists, and farmers are currently in pursuit of sustainable agricultural practices that can effectively ensure global food security while simultaneously mitigating environmental degradation. A field experiment was conducted to elucidate the impact of low-cost capacitance soil moisture-based sensors on lettuce (Lactuca sativa L.) irrigation water conservation, agro-physiological aspects, and nutritional characteristics. The experiment also involved the use of five different types of soil mulching films: white geotextile (WGup), green geotextile (GGup), black plastic (BPup), white geotextile for both above and below ground (WGup-down), green geotextile for both above and below ground (GGup-down), in addition to un-mulched soil (control). The findings demonstrated that the application of WGup, BPup, WGup&down, and GGup&down resulted in a significant improvement in irrigation water conservation, with WGup exhibiting the highest savings at 41.86%, while the control group exhibited the least amount of water savings at 19.87%. Moreover, the highest productivity levels were observed in plants mulched with GGup&down, reaching 47,944.68 kg ha−1, whereas the lowest productivity was recorded in plants mulched with green geotextile GGup at 22,377.89 kg ha−1. In terms of irrigation water productivity (IWP), the order of effectiveness was BPup > GGup-down > WGup > WGup-down > GGup > Control, with BPup achieving the highest IWP at 60.19 kg m−3 and the control treatment reporting the lowest at 27.80 kg m−3. The percentage of the irrigation water applied for crop evapotranspiration (Irc) showed that the control treatment saved the least amount of irrigation water, saving only 19.87%, while the best treatment was WGup, achieved the highest percentage of irrigation water savings at 41.86%. Additionally, mulched plants exhibited higher levels of nutrients (N, P, Ca, Mg, Fe, Mn, and Zn), ascorbic acid (AsA), and total phenol content (TPC), while showing lower nitrate content in the leaves compared to non-mulched plants. Overall, the utilization of soil moisture-based capacitance sensors and biodegradable mulching films has proven to be highly effective and low cost by 16.633 US$ year−1 to enhance irrigation water productivity, growth performance, nutritional quality, and overall productivity of lettuce crops, thereby contributing to the sustainability of lettuce production in arid regions.

Flexible and High-Strength Porous Graphene/Polyurea Composite Film for Multifunctional Applications

Porous composites possess distinctive structural features and performance advantages, making them promising for applications in various domains such as sensing, energy storage, and acoustics. A simple, efficient, and environmentally friendly method was employed to prepare porous polyurea materials, which were then modified with graphene nanosheets. The resulting graphene/polyurea porous composites demonstrated enhanced mechanical properties, with a 35.04% increase in tensile strength at a graphene content of 5 wt%. These composites exhibited exceptional multifunctionality, achieving a specific capacitance of 35.74 F/g when used as capacitor electrodes. Additionally, they displayed high sensitivity to resistance and capacitance changes under various mechanical loads, such as tensile, torsional, and bending stresses, with a resistance change rate of 57.72% under 180-degree torsion, highlighting their potential as resistive and capacitive sensors. Compared to traditional materials, the multifunctional composites maintained a resistance change rate below 40% and a capacitance retention rate above 95.07% after 10,000 cycles, underscoring their durability and reliability. Moreover, the developed graphene/polyurea porous composites exhibited good corrosion resistance and an impressive sound absorption rate of 30.68% for high-decibel noise, reducing environmental limitations for their applications. These properties position the composite as a durable, high-sensitivity, multifunctional material with significant potential in sensing, energy storage, and noise reduction applications.

Artificial Intelligence Using FFNN Models for Computing Soil Complex Permittivity and Diesel Pollution Content

Soil pollution caused by hydrocarbons, such as diesel, poses significant risks to both human health and the ecosystem. The evaluation of soil pollution and various soil engineering applications often relies on the analysis of complex permittivity, encompassing parameters such as dielectric constant and dielectric loss. Various computational models, including theoretical physics-based models, mixture theory models, statistical empirical models, and artificial neural network (ANN) models, have been explored for computing soil complex permittivity and predicting water and pollutant content. Theoretical models require detailed data that is often unavailable, and thus have limited applicability. Mixture models tend to underestimate soil characteristics due to inaccuracies in permittivity estimation of soil phases. While empirical models are widely used, their applicability is restricted to specific soil types, datasets, and locations. ANN models offer promising predictions, accommodating nonlinear phenomena and allowing for missing information and variables. In this study, capacitive electromagnetic electrode sensors were utilized to determine the complex permittivity of soil contaminated with varying levels of diesel at different moisture levels. Theoretical mixture, empirical, and Feed Forward Neural Network (FFNN) models were employed to compute the permittivity of polluted soil based on its phases and to predict the level of diesel pollution. A comparison of these modeling approaches revealed that the FFNN model exhibited the best performance. The ANN model demonstrated superior performance metrics, including a high correlation coefficient and lower mean square error. Specifically, the correlation coefficients for the FFNN model were 0.9942 for training samples, 0.9967 for validation samples, and 0.9977 for test samples. Additionally, the ANN model yielded the lowest mean square error compared to the other three models. Doi: 10.28991/CEJ-2024-010-09-018 Full Text: PDF

Design and FEA verification of high dimensional and multi-field smart soft material

Abstract We designed a sophisticated smart soft tissue material that simulates the properties of biological soft tissue and detects three-dimensional force. Inspired by electronic skin, this material uses capacitive pressure sensors and multi-layer sensor packaging. Finite element analysis and multi-field simulation were employed for structural design and verification. The study evaluated the theory and practicality of a flexible capacitive 3D force sensor for detecting pressure and shear force. Mechanical and electrical properties were confirmed through force and electric field simulations. The 3D force detection method proved feasible, achieving sensitivity levels of 10−4 kPa −1 in the X and Y directions, and 10−3 kPa −1 in the Z direction, demonstrating the effectiveness of our design.

Study on Static Deflection Model of MEMS Capacitive Microwave Power Sensors

Study on Static Deflection Model of MEMS Capacitive Microwave Power Sensors

A CMOS front-end circuit for capacitive sensors with zero adjustment

A front-end circuit with measurement zero adjustment was designed using 180nm CMOS technology for capacitive sensors. A series-switched capacitor composed of capacitor under test and MOSFETs is controlled by a clock signal to convert capacitance to current. The minimum output current at fixed capacitance can be adjusted by applying different voltage to realize zero adjustment. The test shows that the output current has a monotonic linear relationship with the measured capacitance, with capacitance detection range reaches 50pF-3000pF and an output current range of 0.59mA-22.2mA. The maximum span of multiple measurements was lower than 8.37uA. The stable time is less than 23ms and sensitivity is 19.8uA/pF. This circuit is suitable for long-distance and wide-range capacitance detections.

Vibrational Feedback for a Teleoperated Continuum Robot with Non-contact Endoscope Localization

Abstract Limited or absent haptic feedback is reported as a factor hindering the continued adoption of surgical robots. This article presents a proof of concept for vibrotactile feedback integrated into a continuum robot to explore whether such feedback improves spatial perception in surgical settings. The robot is equipped with a capacitive sensor for noncontact endoscope localization, enabling spatial awareness of the robot’s tool center point (TCP) within the surgical environment. The data from the sensor is processed and transmitted to a bracelet worn by the user, which generates vibrotactile feedback. The bracelet contains four vibration motors providing tactile cues for navigation and positioning of the robot’s TCP. All subsystems are integrated into a unified system to deliver vibrotactile feedback to the user. When the user maneuvers the TCP of the robot near an object, they receive vibrotactile feedback via the bracelet. Thereby, the intensity of vibration increases as the TCP approaches the object, and the direction of the obstacle is mapped on the bracelet. Initial functional tests were performed and prove the functionality of the proposed system.

The Application of Touch Sensors

Touch sensors have a wide range of applications in smart homes, enabling the control of lighting, air conditioning, curtains, and other equipment. This paper summarizes the principles, applications, and future developments of touch sensors, including capacitive, resistive, and piezoelectric sensors. The capacitive touch sensor operates based on the capacitance formula, the resistive sensor on the resistivity formula, and the piezoelectric sensor on the piezoelectric effect. Capacitive touch sensors can detect the movement and position of objects and respond quickly, but they require power. Resistive sensors have a fast response time, long durability, low cost, and high sensitivity, but they also require power. Piezoelectric sensors do not require power, can detect dynamic physical quantities, but are unable to detect static ones. Both capacitive and piezoelectric sensors are used in smart mobile devices, while resistive sensors are used in all-in-one machines. Given their principles and current applications, touch sensors are expected to be utilized in the touch screens of operation interfaces in more machines and the bionic skin of androids.

Coral-Inspired Capacitive Pressure Sensor with High Sensitivity and Wide Range for Human–Computer Interaction

Coral-Inspired Capacitive Pressure Sensor with High Sensitivity and Wide Range for Human–Computer Interaction

Screen-Printed Capacitive Tactile Sensor for Monitoring Tool–Tissue Interactions and Grasping Performances of a Surgical Magnetic Microgripper

Screen-Printed Capacitive Tactile Sensor for Monitoring Tool–Tissue Interactions and Grasping Performances of a Surgical Magnetic Microgripper

New parameters for the capacitive accelerometer to reduce its measurement error and power consumption

Capacitive accelerometers are essential components in a wide range of electronic devices, enabling crucial functionalities such as touch sensitivity and proximity detection. Ensuring optimal accuracy is crucial for their effective performance in various applications. A key factor in this accuracy is the frequency margin, a parameter that significantly influences the sensor's ability to detect and respond to changes in capacitance.In this article, we will delve deeply into strategies aimed at optimizing capacitive sensors with a focus on improving their frequency margin. By exploring the methodologies and techniques that enhance the sensor's ability to operate within an ideal frequency range, we aim to improve the measurement accuracy of capacitive accelerometers by reducing measurement errors and power consumption. This optimization process involves meticulous calibration of sensor parameters such as sensitivity, resonance frequency, and damping factors to maximize performance under various environmental conditions. The new capacitive accelerometer structure improves sensitivity, linearity, and accuracy through advanced measurement setups and design, offering high-performance acceleration measurements suitable for various applications and reliable data collection and calibration.

Fringing‐Effect‐Based Capacitive Proximity Sensors

AbstractProximity sensing technology, which can obtain information without physical contact, has become an ideal choice in scenarios where physical contact is not feasible. Despite substantial advancements in tactile sensing, proximity sensing technology still holds great potential and has yet to be fully developed. Among numerous proximity sensing technologies, the fringing‐effect‐based capacitive proximity sensor (FE‐CPS) has garnered considerable attention due to its low cost, low power consumption, wide sensing range, and flexible and versatile structural design. However, research on FE‐CPS has not yet formed a complete system, and its development and intellectualization are still in their infancy, urgently requiring a systematic review to advance its development. This paper systematically summarizes the recent advances in FE‐CPS, from basic theory to practical applications. The working principle and typical structure of FE‐CPS are first introduced, followed by a discussion of methods for optimizing device performance. Furthermore, the application scenarios of FE‐CPS in intelligent pre‐alarm systems, intelligent control systems, and intelligent material perception systems are reviewed. Finally, the future development and challenges faced by FE‐CPS are prospected.

Low humidity hysteresis and fast response silicon based capacitive humidity sensor based on SiO2 supported GO film

Low humidity hysteresis and fast response are important parameters for evaluating sensor performances. However, it is difficult for a sensor to simultaneously obtain a low humidity hysteresis and fast response time. In this work, a low humidity hysteresis and fast response silicon based capacitive humidity sensor was fabricated based on a two-step deposition strategy using SiO2 and GO. The scanning electron microscope (SEM) was used to characterize the morphologies for the fabricated sensor, demonstrating the successful synthesis of sensitive films. The experimental results suggested that, compared with the pure GO and GO/SiO2 composite film sensors, the two-step deposition strategy fabricated layered SiO2 supported GO film humidity sensor exhibited the lowest humidity hysteresis and the fastest response speed. The humidity hysteresis and response/recovery time are 3.5 % and 3 s/2 s, respectively. The humidity sensing mechanism for the observed low humidity hysteresis and fast response was analyzed via morphologic structures and Young-Laplace equation. This work demonstrates that the morphological structures modulation is an important and effective method for improving sensor performance, providing a valuable reference for high performance sensor fabrication.