Fabrication Of Pressure Sensor Research Articles

A sustainable strategy to transform disposed oil-flax into renewable fabric-based pressure sensor

A reutilization strategy for disposed plants is proposed for the fabrication of pressure sensor, which is achieved by the assembly of oil-flax nonwoven fabric, MXene, polydimethylsiloxane (PDMS) and interdigital electrode. The sensor exhibits excellent sensing performance, including a high sensitivity of 6.25 kPa−1, a wide sensing range of 100 kPa, and exceptional stability over 700 loading cycles. These characteristics make the sensor suitable for various applications, such as human movement monitoring, air flow monitoring, speech recognition, and touch screens. This method of utilizing discarded plants to develop smart wearable devices holds great significance in terms of effective resource utilization and the expansion of application domains.

Fabrication of Flexible Capacitive Pressure Sensors by Adjusting the Height of the Interdigital Electrode

Fabrication of Flexible Capacitive Pressure Sensors by Adjusting the Height of the Interdigital Electrode

Ultrasensitive flexible pressure sensor for soft contraction detection

We report the fabrication and characterization of a highly sensitive pressure sensor that has been successfully tested using 3D-bioprinted skeletal muscle tissue. The proposed pressure sensor consists of two assembled 3D printed specimens, which were obtained using 60/40 v/v poly(3,4-ethylenedioxythiophene):polystyrene sulfonic acid (PEDOT:PSS) / poly(ethylene glycol) diacrylate (PEGDA) mixture, placed between two indium tin oxide-coated polyethylene terephthalate (PET-ITO) films. The printed specimens were shaped with a serrated structure, improving the sensitivity of the contact when pressed against PET-ITO film. Initially, the performance of the fabricated pressure sensor was tested using light cylindrical weights, which corresponded to pressures ranging from 0.99 to 14.71 kPa, and as prove of concept, carefully pressing with the finger (from 2.91 to 6.81 kPa). As the sensitivity and fast response of sensor were compatible with detection of soft muscle contractions, 3D-bioprinted skeletal muscle bioactuators were manufactured using myoblast cells. The contractions of the bioactuators, which were induced using electrical stimulation, exerted a pressure of 1.5 kPa only that was clearly and precisely detected by the sensor. Overall, the potential application of proposed pressure sensor for wearable and biomedical devices is evidenced by demonstrating its fast response time (< 50 ms) and sensitivity.

Batch fabrication of ultrathin flexible pressure sensors enabled by full printed technique

Flexible pressure sensors have gained significant attention in recent years owing to their versatile applications in health monitoring, human-machine interfaces, and artificial robotics. Geometric microengineering of the active layer, including micropatterned structures, porous layers, and multilayered packed structures has been investigated to improve the sensing performance. However, accompanying challenges such as increased thickness and difficulties in achieving mass production still persist. This work presents a full printed technique for fabricating high-performance piezoresistive pressure sensors. Thermal-treated graphene oxide (TGO) colloid was selected as the printing ink. Combined with an in-situ chemical foaming strategy, structural microengineering of the piezoresistive layer was achieved. The obtained hierarchical protruding micro-domes endow the piezoresistive pressure sensors with a wide sensing range of 550 kPa and ultrathin features (18 μm). In addition, the full-printed manufacturing method enables the batch-producible fabrication of pressure sensors. These sensors can be employed for human motion detection and pressure mapping applications.

Design and fabrication of a novel all-quartz resonant pressure sensor with continuously variable section of DETF

This paper reports a novel piezoelectric quartz crystal pressure sensor with a double-ended tuning fork (DETF) resonator. The key design is the resonator beams with a continuously variable section shape. Different from the traditional DETF with straight beams or the one with variable sections with steps, this design can improve sensitivity effectively. Theoretical analysis indicates that the sensitivity will increase with a decrease in beam width. Resonant pressure sensors with three different DETFs are designed and analyzed by finite element analysis software. Simulation results show that the sensitivity of this design is 162.27 Hz/MPa. This sensor has a typical structure, which includes three parts: the diaphragm, DETF resonator, and back-cavity structure. Quartz MEMS processes have been used in fabrication. The three parts are bonded together by vacuum glass frit sealing process. Test results of this sensor show that the natural frequency is 44.709 kHz with a quality factor of 12 717. The sensitivity is 155.6 Hz/MPa in the pressure range of 0–20 MPa. The results indicate that this novel design has advantages in sensitivity and fabrication processes. It will be a benefit for a high-performance and low-cost pressure measurement.

Piezoelectric Micromachined Ultrasonic Transducers with Micro-Hole Inter-Etch and Sealing Process on (111) Silicon Wafer.

Piezoelectric micromachined ultrasound transducers (PMUTs) have gained significant popularity in the field of ultrasound ranging and medical imaging owing to their small size, low power consumption, and affordability. The scar-free "MIS" (micro-hole inter-etch and sealing) process, a novel bulk-silicon manufacturing technique, has been successfully developed for the fabrication of pressure sensors, flow sensors, and accelerometers. In this study, we utilize the MIS process to fabricate cavity diaphragm structures for PMUTs, resulting in the formation of a flat cavity diaphragm structure through anisotropic etching of (111) wafers in a 70 °C tetramethylammonium hydroxide (TMAH) solution. This study investigates the corrosion characteristics of the MIS technology on (111) silicon wafers, arranges micro-pores etched on bulk silicon around the desired cavity structure in a regular pattern, and takes into consideration the distance compensation for lateral corrosion, resulting in a fully connected cavity structure closely approximating an ortho-hexagonal shape. By utilizing a sputtering process to deposit metallic molybdenum as upper and lower electrodes, as well as piezoelectric materials above the cavity structure, we have successfully fabricated aluminum nitride (AlN) piezoelectric ultrasonic transducer arrays of various sizes and structures. The final hexagonal PMUT cells of various sizes that were fabricated achieved a maximum quality factor (Q) of 251 and a displacement sensitivity of 18.49 nm/V across a range of resonant frequencies from 6.28 MHz to 11.99 MHz. This fabrication design facilitates the achievement of IC-compatible and cost-effective mass production of PMUT array devices with high resonance frequencies.

Wearable 3-D Meshed Textile Pressure Sensor for Physiological Signal Monitoring

Wearable 3-D Meshed Textile Pressure Sensor for Physiological Signal Monitoring

High-sensitivity, ultrawide linear range, antibacterial textile pressure sensor based on chitosan/MXene hierarchical architecture

It is still a great challenge for the flexible piezoresistive pressure sensors to simultaneously achieve wide linearity and high sensitivity. Herein, we propose a high-performance textile pressure sensor based on chitosan (CTS)/MXene fiber. The hierarchical "point to line" architecture enables the pressure sensor with high sensitivity of 1.16kPa-1 over an ultrawide linear range of 1.5 MPa. Furthermore, the CTS/MXene pressure sensor possesses a low fatigue over 1000 loading/unloading cycles under 1.5 MPa pressure load, attributed to the strong chemical bonding between CTS fiber and MXene and excellent mechanical stability. Besides, the proposed sensor shows good antibacterial effect benefiting from the strong interaction between polycationic structure of CTS/MXene and the predominantly anionic components of bacteria surface. The sensor is also applied to detect real-time human action, an overall classification accuracy of 98.61% based on deep neural network-convolutional neural network (CNN) for six human actions is realized.

Fabric Pressure Sensors for Fine-Grained Interaction Detection in Plush Toys

Recent advances in fabric-based sensors have made it possible to densely instrument plush toys without altering their aesthetic or tactile appeal, unlike traditional sensors whose rigid components can negatively impact the interactive experience. This innovation opens a new realm of interaction possibilities, allowing for the detection of nuanced gestures and movements that are crucial for understanding behavior, enhancing engagement, and potentially monitoring cognitive functions in therapeutic contexts.

Accurate and Efficient Sitting Posture Recognition and Human‐Machine Interaction Device Based on Fabric Pressure Sensor Array and Neural Network

AbstractThis article presents a novel approach to interact with users through posture recognition, leveraging its advantages of convenience and real‐time feedback to enhance user engagement and personalized experiences. In contrast to traditional methods that rely on camera‐based posture detection, this study proposes a deep learning‐based framework for posture recognition by classifying the distribution of body pressure under different sitting positions. The system integrates a large‐area, highly flexible fabric pressure sensor array into the chair, which collects data on posture‐specific pressure patterns for training and identification purposes. A deep learning algorithm, specifically the LeNet architecture, is employed to classify 49 different sitting positions based on angular variations, including body tilt to the left or right, standard posture, and forward or backward leaning. The proposed approach achieves an impressive accuracy rate of 99.86%. Furthermore, the application of this posture recognition system in VR devices enables intelligent chair control for VR games. This research provides strong support for future advancements in chair design and human‐computer interaction technologies, enhancing ergonomic designs in various domains such as automotive seats, office chairs, and medical seating, while simultaneously improving user comfort and well‐being.

Dual-Stage Surficial Microstructure to Enhance the Sensitivity of MXene Pressure Sensors for Human Physiological Signal Acquisition.

Accompanying the rapid growth of wearable electronics, flexible pressure sensors have received great interest due to their promising application in health monitoring, human-machine interfaces, and intelligent robotics. The high sensitivity over a wide responsive range, integrated with excellent repeatability, is a crucial requirement for the fabrication of reliable pressure sensors for various wearable scenes. In this work, we developed a highly sensitive and long-life flexible pressure sensor by constructing surficial microarrayed architecture polydimethylsiloxane (PDMS) film as a substrate and Ti3C2TX MXene/bacterial cellulose (BC) hybrid as an active sensing layer. The specific surficial morphology of PDMS couples with nanointercalated structure of Ti3C2Tx MXene/BC can effectively improve the sensitivity through controlling the stress distribution and layer spacing under different levels of pressure loading. In addition, abundant spontaneous hydrogen bonds between BC and Ti3C2Tx MXene nanosheets endow the MXene coating with highly adhesive strength on the PDMS surface; hence, the cyclic stability of the pressure sensor is greatly boosted. As a result, the obtained MXene/BC/PDMS (MBP) pressure sensor delivers high sensitivity (528.87 kPa-1), fast response/recovery time (45 ms/29 ms), low detection limit (0.6 Pa), and outstanding repeatability of up to 8000 cycles. Those excellent sensing properties of the MBP sensor allow it to serve as a reliable wearable device to monitor full-range human physiological motions, and it is expected to be applied in next-generation portable electronics, such as E-skins, smart healthcare, and the Internet of Things technology.

Flexible Iron-On Sensor Embedded in Smart Sock for Gait Event Detection.

Portable and wearable electronics for biomechanical data collection have become a growing part of everyday life. As smart technology improves and integrates into our lives, some devices remain ineffective, expensive, or difficult to access. We propose a washable iron-on textile pressure sensor for biometric data acquisition. Biometric data, such as human gait, are a powerful tool for the monitoring and diagnosis of ambulance and physical activity. To demonstrate this, our washable iron-on device is embedded into a sock and compared to gold standard force plate data. Biomechanical testing showed that our embedded sensor displayed a high aptitude for gait event detection, successfully identifying over 96% of heel strike and toe-off gait events. Our device demonstrates excellent attributes for further investigations into low-cost, washable, and highly versatile iron-on textiles for specialized biometric analysis.

Sleep position classification with a compact pressure textile sensor mattress using convolutional neural networks

Robust body position classification during sleep is crucial for closed-loop robotic interventions in position-dependent sleep disorders. This work investigates a compact, custom-made textile pressure sensor to automatically classify recumbent body positions. We implemented a range of traditional classification methods, including Naïve Bayes, Decision Trees, and Support Vector Machines. Furthermore, we trained different machine learning models on recordings from 19 participants, with a varying amount of personalized training data (i.e. from a generalized inter-person classifier towards fully personalized classifiers). We computed the performance metrics F1-score, precision, recall, and accuracy using multi-fold cross-validation for the four classes supine, prone, lateral left, and lateral right, as well as for the binary classes supine vs. non-supine. For the generalized classifier, we could achieve an accuracy of 82.7% for a balanced test set. The personalized models for one male and one female user showed a higher accuracy, namely 95% and 92%. For the binary classifier, the personalized classifiers (male F1-score: 0.97, female F1-score: 0.94) outperformed the generalized classifiers (F1-score: 0.91). Similar to related work, our machine-learning model demonstrated superior performance compared to the three traditional approaches we implemented. Our results show that robust body position classification is possible using small-scale unobtrusive textile bedding sensors, pathing the way for future closed-loop interventions.

A highly sensitive pressure sensor based on Ag-graphene-PDMS film and its applications

The fast progress in artificial intelligence has increased the need for wearable electronics. Herein, a piezoresistive pressure sensor consisting of three layers has been proposed. The soft sensing film has been fabricated by filling PDMS (polydimethylsiloxane) with Ag-graphene by a simple mixing method, which possesses low cost and excellent sensing properties, including high sensitivity, high conductivity, and quick response to different pressures. Furthermore, the characterizations were performed by using a scanning electron microscope to study the microstructure and surface morphologies of the Ag-graphene-PDMS film to explore its internal working mechanism. Moreover, the single sensor and sensor array were tested for many applications. The results showed that the fabricated pressure sensor effectively identified various human movements and distinguished pressures with different values and positions. As a result, this sensor has a wide range of applications, including smart wearable technologies and soft robotics.

Fabrication of a Cost-effective Piezoresistive Pressure Sensor Based on PVC/Reduced Graphene Oxide (rGO) Composite

Fabrication of a Cost-effective Piezoresistive Pressure Sensor Based on PVC/Reduced Graphene Oxide (rGO) Composite

Capacitive Pressure Sensors Based on Square‐Conical Arrays Fabricated by a Fabric‐Mould Strategy for Ultralow and Highly Sensitive Pressure Detection

AbstractFlexible pressure sensors are playing an emerging role in artificial intelligence and electronic skin. However, developing a high‐performance, flexible pressure sensor through a reusable and straightforward manufacturing approach still remains a challenge. In this study, a highly sensitive, flexible capacitive pressure sensor based on a fabric‐mould strategy is introduced. Custom square‐conical arrays with Au electrodes can feasibly be fabricated at scale by peeling them off the fabric mould. The fabricated pressure sensor exhibits a high sensitivity of 5.829 kPa−1 (0–0.444 kPa) and a rapid response/recovery time of 160/70 ms. Notably, the sensor has an ultralow detection limit of 0.24 Pa, showing great potential for extremely sensitive pressure detection applications, such as water leakage monitoring. Finite element analysis, grounded on 3D‐scanning reconstruction, reveals that the enhanced sensing performance can be attributed to the contact surface of the square‐conical arrays. Moreover, the pressure sensors can accurately identify human physiological information, as well as the spatial distribution and shape of objects, further highlighting the promise for wearable electronic devices. This work not only offers a new approach for large‐scale fabrication of micro‐structures at low cost but also provides a new insight into the optimization of structures for sensitive pressure sensors.

Flexible, highly sensitive and reliable piezocapacitive pressure sensor with honeycomb-like microarchitecture fabricated using filament-processed mold

Highly sensitive flexible pressure sensors have been extensively studied due to their promising applications in many fields. Various sensing mechanisms have been proposed to convert pressure into a readable electrical signal, among which piezocapacitive presents advantages due to its simple structure and convenient integration. The modification of the dielectric layer composing these sensors is a common strategy to improve their sensing performance. In this paper, we propose the fabrication of a novel capacitive-based flexible pressure sensor with honeycomb-like microarchitecture by using femtosecond laser filament based far-field technique. The fabricated flexible sensing device is assembled face-to-face with two layers of micro-structured polydimethylsiloxane thin films that is duplicated from laser filament-processed silicon mold. The as-prepared flexible sensor features excellent sensing performance with high reliability, and enables detection of multi-modal signals, including pressure, proximity, and bending. Owing to the advantages mentioned above, the obtained flexible pressure sensor can be attached on non-planar human skin to monitor the physiological signals as well as joint deformation during exercise, revealing it great application potential in cutting-edge fields, such as robotic tactility.

Microring structure for flexible polymer waveguide-based optical pressure sensing.

Flexible pressure sensors provide a promising platform for artificial smart skins, and photonic devices provide a new technique to fabricate pressure sensors. Here, we present a flexible waveguide-based optical pressure sensor based on a microring structure. The waveguide-based optical pressure sensor is based on a five-cascade microring array structure with a size of 1500 µm × 500 µm and uses the change in output power to linearly characterize the change in pressure acting on the device. The results show that the device has a sensing range of 0-60 kPa with a sensitivity of 23.14 µW/kPa, as well as the ability to detect pulse signals, swallowing, hand gestures, etc. The waveguide-based pressure sensors offer the advantages of good output linearity, high integration density and easy-to-build arrays.

Reliable and Scalable Piezoresistive Sensors with an MXene/MoS2 Hierarchical Nanostructure for Health Signals Monitoring.

The increased popularity of wearable electronic devices has led to a greater need for advanced sensors. However, fabricating pressure sensors that are flexible, highly sensitive, robust, and compatible with large-scale fabrication technology is challenging. This work investigates a piezoresistive sensor constructed from an MXene/MoS2 hierarchical nanostructure, which is obtained through an easy and inexpensive fabrication process. The sensor exhibits a high sensitivity of 0.42 kPa-1 (0-1.5 kPa), rapid response (∼36 ms), and remarkable mechanical durability (∼10,000 cycles at 13 kPa). The sensor has been demonstrated to be successful in detecting human motion, speech recognition, and physiological signals, particularly in analyzing human pulse. These data can be used to alert and identify irregularities in human health. Additionally, the sensing units are able to construct sensor arrays of various sizes and configurations, enabling pressure distribution imaging in a variety of application scenarios. This research proposes a cost-effective and scalable approach to fabricating piezoresistive sensors and sensor arrays, which can be utilized for monitoring human health and for use in human-machine interfaces.

Mold-Free Manufacturing of Highly Sensitive And Fast Response Pressure Sensors Through High-Resolution 3d Printing And Conformal Oxidative Chemical Vapor Deposition Polymers.

In this work, w e showcase a new manufacturing paradigm to exclude conventional mold-dependent manufacturing of pressure sensors, which typically requires a series of complex and expensive patterning processes. Our mold-free manufacturing leverages high-resolution 3D printed multiscale microstructures as substrate and a gas-phase conformal polymer coating technique to complete the mold-free sensing platform. The array of dome and spike structures with a controlled spike density of a 3D-printed substrate ensures a large contact surface with pressures applied and extended linearity in a wider pressure range. For uniform coating of sensing elements on the microstructured surface, oxidative chemical vapor deposition is employed to deposit a highly conformal and conductive sensing element, poly(3,4-ethylenedioxythiophene) at low temperatures (< 60 °C). The fabricated pressure sensor reacts sensitively to various ranges of pressures (up to 185 kPa-1 ) depending on the density of the multiscale features and shows an ultra-fast response time (∼36 μs). The mechanism investigations through the finite element analysis identify the effect of the multiscale structure on the figure-of-merit sensing performance. Our unique findings are expected to be of significant relevance to the technology that requires higher sensing capability, scalability, and facile adjustment of a sensor geometry in a cost-effective manufacturing manner. This article is protected by copyright. All rights reserved.