Pressure Sensor Based on a Lumpily Pyramidal Vertical Graphene Film with a Broad Sensing Range and High Sensitivity

Manipulator with Integrated Flexible Tactile Sensing Arrays for Kiwifruit Ripeness and Size Classification

Fruit grading for ripeness and size is an essential process in the supply chain. Incorrect grading can easily lead to spoiled and degraded fruits entering the market, reducing consumers' confidence in purchasing. At the same time, it is easy to cause the fruit supply chain to reduce profits, unreasonable resource allocation, and related practitioners' income. The current mainstream machine vision grading and manual grading in the production line have dilemmas such as susceptibility to environmental interference, inconsistent grading standards, high cost, and labor shortage. To overcome these problems, this study proposes an integrated flexible tactile sensing array (3 × 4) manipulator for efficient, stable, low-cost, and accurate ripeness and size grading of kiwifruit. The flexible sensing manipulator grasps the kiwifruit, detects the hardness of the kiwifruit by relying on tactile sensing, and determines the ripeness level based on the hardness. The size of the kiwifruit is also differentiated according to whether there is a significant change in the resistance of the topmost sensing unit of the flexible pressure sensor array. The 0, 1, 2, 3, 4, and 5 anomalies that may occur in actual production were tested and combined with machine learning KNN, SVM, and RF algorithms for data modeling and grading. The results show that the lowest accuracy of 0, 1, 2, 3, 4, and 5 possible outliers is 86.67% (KNN), 95.83% (SVM), and 92.5% (RF), respectively. KNN has the lowest classification effect, and SVM has the best. This study overcomes the drawbacks of inefficient destructive detection and unstable manual detection and makes up for the vulnerability of single machine vision to interference from environmental factors. This study can alleviate the challenges caused by fruit wastage and promote the sustainable production and consumption of the fruit industry chain.

Ultrahighly Sensitive Flexible Pressure Sensors with Dual-Mode Response Based on Monolayer Films of Calcium Niobate Nanosheets

Flexible pressure sensors present enormous potential for applications in health monitoring, human-machine interfacing, and electronic skins (e-skin). However, at the cost of flexibility, the design of flexible pressure sensors has been facing the trade off between high sensitivity and wide sensing range. Herein, we propose a sandwiched structure composed of monolayer films of calcium niobate nanosheets to endow the device with both ultrahigh sensitivity and a wide sensing range. Tunable contact between the two electrodes of the pressure sensor through the gaps in the insulative monolayer film and precise thickness modulation of the monolayer films at the nanoscale result in an ultrahigh sensitivity and wide sensing range of the sensors. By virtue of these two traits, the pressure sensor distinguishes itself with unprecedented performances of ultrahigh sensitivity (6.43 × 104 kPa-1), a wide sensing range (1.94-60.00 kPa), a fast response time (<165 ms), and reliable repeatability. In addition, the sensor has a sensing mechanism transition from capacitive mode to piezoresistive mode from low pressure to high pressure. The sensors demonstrates the ability for motion detection of the human body. This work sheds light on the development of highly sensitive flexible pressure sensors.

Highly sensitive, wide-pressure and low-frequency characterized pressure sensor based on piezoresistive-piezoelectric coupling effects in porous wood

Lightweight and highly compressible materials have received considerable attention in flexible pressure sensing devices. In this study, a series of porous woods (PWs) are produced by chemical removal of lignin and hemicellulose from natural wood by tuning treatment time from 0 to 15 h and extra oxidation through H₂O₂. The prepared PWs with apparent densities varying from 95.9 to 46.16 mg/cm³ tend to form a wave-shaped interwoven structure with improved compressibility (up to 91.89 % strain under 100 kPa). The sensor assembled from PW with treatment time of 12 h (PW-12) exhibits the optimal piezoresistive-piezoelectric coupling sensing properties. For the piezoresistive properties, it has high stress sensitivity of 15.14 kPa^-1, covering a wide linear working pressure range of 0.06-100 kPa. For its piezoelectric potential, PW-12 shows a sensitivity of 0.443 V·kPa^-1 with ultralow frequency detection as low as 0.0028 Hz, and good cyclability over 60,000 cycles under 0.41 Hz. The nature-derived all-wood pressure sensor shows obvious superiority in the flexibility for power supply requirement. More importantly, it presents fully decoupled signals without cross-talks in the dual-sensing functionality. Sensor like this is capable of monitoring various dynamic human motions, making it an extremely promising candidate for the next generation artificial intelligence products.

Wearable Pressure Sensor Using Porous Natural Polymer Hydrogel Elastomers with High Sensitivity over a Wide Sensing Range

Wearable pressure sensors capable of quantifying full-range human dynamic motionare are pivotal in wearable electronics and human activity monitoring. Since wearable pressure sensors directly or indirectly contact skin, selecting flexible soft and skin-friendly materials is important. Wearable pressure sensors with natural polymer-based hydrogels are extensively explored to enable safe contact with skin. Despite recent advances, most natural polymer-based hydrogel sensors suffer from low sensitivity at high-pressure ranges. Here, by using commercially available rosin particles as sacrificial templates, a cost-effective wide-range porous locust bean gum-based hydrogel pressure sensor is constructed. Due to the three-dimensional macroporous structure of the hydrogel, the constructed sensor exhibits high sensitivities (12.7, 5.0, and 3.2 kPa^-1 under 0.1-20, 20-50, and 50-100 kPa) under a wide range of pressure. The sensor also offers a fast response time (263 ms) and good durability over 500 loading/unloading cycles. In addition, the sensor is successfully applied for monitoring human dynamic motion. This work provides a low-cost and easy fabrication strategy for fabricating high-performance natural polymer-based hydrogel piezoresistive sensors with a wide response range and high sensitivity.