Sensor Array Research Articles

Disposable paper-based sensor array for detection of orange juice adulteration

Disposable paper-based sensor array for detection of orange juice adulteration

A General Strategy for Food Traceability and Authentication Based on Assembly-Tunable Fluorescence Sensor Arrays.

Food traceability and authentication systems play an important role in ensuring food quality and safety. Current techniques mainly rely on direct measurement by instrumental analysis, which is usually designed for one or a group of specific foods, not available for various food categories. To develop a general strategy for food identification and discrimination, a novel method based on fluorescence sensor arrays is proposed, composed of supramolecular assemblies regulated by non-covalent interactions as an information conversion system. The stimuli-responsiveness and tunability of supramolecular assemblies provided an excellent platform for interacting with various molecules in different foods. In this work, five sensor arrays constructed by supramolecular assemblies composed of pyrene derivatives and perylene derivatives are designed and prepared. Assembly behavior and sensing mechanisms are investigated systematically by spectroscopy techniques. The traceability and authentication effects on several kinds of food from different origins or grades are evaluated and verified by linear discriminant analysis (LDA). It is confirmed that the cross-reactive signals from different sensor units encompassing all molecular interactions can generate a unique fingerprint pattern for each food and can be used for traceability and authentication toward universal food categories with 100% accuracy.

Developing a Chemiresistive Gas Sensor Array for Simultaneous Detection of Ammonia and Carbon Dioxide Gases.

Chemiresistive polymer-based sensors are promising platforms for monitoring various gases and volatile organic compounds. While they offer appealing attributes, such as ease of fabrication, flexibility, and cost-effectiveness, most of these sensors have a nearly identical response to cross-reactive gases, such as ammonia (NH3) and carbon dioxide (CO2). Aiming to address the shortcomings of chemiresistive polymer-based sensors in selectivity and simultaneous measurements of cross-reactive gases, a chemiresistive sensor array was developed consisting of components sensitive to carbon dioxide and ammonia as well as a control segment to provide the baseline. The designed system demonstrated a wide detection range for both ammonia (ranging from 0.05 to 1000 ppm) and carbon dioxide (ranging from 103 to 106 ppm) at both room and low temperatures (e.g., 4 °C). Our results also demonstrate the ability of this sensor array for the simultaneous detection of carbon dioxide and ammonia selectively in the presence of other gases and volatile organic compounds. Finally, the array was used to monitor CO2/NH3 in real food samples to demonstrate the potential for real-world applications.

Deep ocean hydrographic variability estimated from distributed geodetic sensor arrays off northern Chile

Observations of spatio-temporal variability of the deep ocean are rare and little is known about occurrence of deep ocean mesoscale dynamics. Here, we make use of 2.5 years of time series data from three distributed sensor arrays, which acquired high-resolution temperature, pressure and sound speed data of the bottom layer offshore northern Chile. Estimating salinity and density from the direct observations enable access to the full spectrum of hydrographic variability from a multi-hourly to annual time scale and with average inter-station distances of less than 1 km. Analyses revealed interannual warming over the continental slope of 0.002 °C yr−1–0.003 °C yr−1, and could trace periodic hydrographic anomalies, likely related to coastal-trapped waves, as far as to the lower continental slope. A concurrent change in the shape of the warm anomalies and the rate of deep-sea warming that occurs with the crossing of the deep-sea trench suggests that the abyssal part of the eastern boundary current system off Chile does not extend past the deep sea trench. Furthermore, the comparison of anomaly timing and shape in between stations implies southwards flow over the mid to lower continental slope, centred closer to the trench.

Low-Frequency Environmental Magnetic Noise Elimination Based on a Neural Network Algorithm for TMR Sensor Arrays

Low-Frequency Environmental Magnetic Noise Elimination Based on a Neural Network Algorithm for TMR Sensor Arrays

Flexible Tactile Sensor Arrays With Capacitive and Resistive Dual-Mode Transduction

Flexible Tactile Sensor Arrays With Capacitive and Resistive Dual-Mode Transduction

Multifunctional Robotic Surgical Forceps With Tactile Sensor Array for Tissue Palpation and Clamping Status Detection

Multifunctional Robotic Surgical Forceps With Tactile Sensor Array for Tissue Palpation and Clamping Status Detection

Surface Crack Size Estimation Based on Quantification and Decoupling of Magnetic Flux Leakage (MFL) Signals of Circular Array Sensors

Surface Crack Size Estimation Based on Quantification and Decoupling of Magnetic Flux Leakage (MFL) Signals of Circular Array Sensors

Construction and Application of Nanozyme Sensor Arrays.

Compared with traditional "lock-key mode" biosensors, a sensor array consists of a series of sensing elements based on intermolecular interactions (typically hydrogen bonds, van der Waals forces, and electrostatic interactions). At the same time, sensor arrays also have the advantages of fast response, high sensitivity, low energy consumption, low cost, rich output signals, and imageability, which have attracted widespread attention from researchers. Nanozymes are nanomaterials which own enzyme-like properties. Because of the adjustable activity, high stability, and cost effectiveness of nanozymes, they are potential candidates for construction of sensor arrays to output different signals from analytes through the chemoresponse of colorants, which solves the shortcomings of traditional sensors that they cannot support multiple detection and lack universality. Recently, a sensor array based on nanozymes as nonspecific recognition receptors has attracted much more attention from researchers and has been applied to precise recognition of proteins, bacteria, and heavy metals. In this perspective, attention is given to nanozymes and the regulation of their enzyme-like activity. Particularly, the building principles and methods for sensor arrays based on nanozymes are analyzed, and the applications are summarized. Finally, the approaches to overcome the challenges and perspectives are also presented and analyzed for facilitating further research and development of nanozyme sensor arrays. This perspective should be helpful for gaining insight into research ideas within the field of nanozyme sensor arrays.

Injectable 2D Material-Based Sensor Array for Minimally Invasive Neural Implants.

Intracranial implants for diagnosis and treatment of brain diseases have been developed over the past few decades. However, the platform of conventional implantable devices still relies on invasive probes and bulky sensors in conjunction with large-area craniotomy and provides only limited biometric information. Here, we report an implantable multi-modal sensor array that can be injected through a small hole in the skull and inherently spread out for conformal contact with the cortical surface. The injectable sensor array, composed of graphene multi-channel electrodes for neural recording and electrical stimulation and MoS2-based sensors for monitoring intracranial temperature and pressure, was designed based on a mesh structure whose elasticrestoringforce enables the contracted device to spread out. We demonstrated that the sensor array injected into a rabbit's head can detect epileptic discharges on the surface of the cortex and mitigate it by electrical stimulation while monitoring both intracranial temperature and pressure. This method providesgoodpotentialfor implanting a variety of functional devices via minimally invasive surgery. This article is protected by copyright. All rights reserved.

On-Chip Annealing Using Embedded Micro-Heater for Highly Sensitive and Selective Gas Detection.

The demand for gas sensing systems that enable fast and precise gas recognition is growing rapidly. However, substantial challenges arise from the complex fabrication process of sensor arrays, time-consuming data transmission to an external processor, and high energy consumption in multi-stage data processing. In this study, a gas sensing system using on-chip annealing for fast and power-efficient gas detection is proposed. By utilizing a micro-heater embedded in the gas sensor, the sensing material of adjacent sensors in the same substrate can be easily varied without further fabrication steps. The response to oxidizing gas is constrained in metal oxide (MOX) sensing material with small grain sizes, as the depletion width of grain cannot extend beyond the grain size during the gas reaction. On the other hand, the response to reducing gases and humidity, which decrease the depletion width, is less affected by grain sizes. A readout circuit integrating a differential amplifier and dual FET-type gas sensors effectively emphasizes the response to oxidizing gases by canceling the response to reducing gases and humidity. The selective on-chip annealing method is applicable to various MOX sensing materials, demonstrating its potential for application in commercial fields due to its simplicity and expandability.

A feature extractor for temporal data of electronic nose based on parallel long short-term memory network in flavor discrimination of Chinese vinegars

Volatile flavor is a key indicator of food quality which can directly affect consumer preference and purchase intention. Electronic nose is considered as a promising intelligent sensory analysis tool for food flavor assessment, however, extracting effective features from the gas sensor array is still a major challenge, which largely determines the performance of subsequent classifiers. Here, a parallel long short-term memory (LSTM) network is proposed as a feature extractor for automatically extracting features from the whole time series of sensor responses in flavor discrimination of five Chinese vinegars. The network was trained by the temporal data from the sensor array and yielded different feature patterns corresponding to different vinegars, which were then fed to other conventional classifiers for pattern recognition. We also evaluated the influence of the extracted feature dimension that is related to the dimension of the hidden state of the LSTM layer on the classification performance. The results indicate that a larger dimension of extracted feature is unnecessary for promoting classification accuracy, instead, the optimum dimension 4 of the hidden state gives the highest accuracy of 95.8% in this application under the softmax evaluator. Moreover, much higher accuracies were obtained when combined with other sophisticated classifiers such as support vector machine. The results demonstrate that the proposed network is competent to extract features directly and automatically from the temporal data of the electronic nose.

UV‐A/B High‐Sensitivity Organic Photodetectors Containing Butterfly‐Shaped Furan‐Fused BN‐Dihydropyrene with Push‐Pull Electron “Wings” toward Image Sensor

AbstractReplacement of C─C unit with its isoelectronic B─N unit in aromatics provides a new class of molecules with appealing properties. Herein, Five novel butterfly‐shaped furan‐fused bis‐BN dihydropyrenes (FBN) derivatives are synthesized with different push‐pull electron “wings”. These compounds exhibit prominent UV‐A/B absorption, high energy levels, and p‐type characteristics. Thanks to the side‐chain engineering and BN dipole manipulation, their intramolecular dipole moments and intermolecular stacking mode are effectively regulated to improve intra‐ and inter‐molecular charge transfer, thus achieving high hole mobilities. Five FBN‐X compounds are doped with PC71BM as heterojunction photosensitive layers to fabricate solution‐processed high performance organic photodetectors (OPDs), which exhibit self‐powered effect and high sensitivity to UV‐A/B. Especially, the FBN‐CN‐based device presents a high detectivity up to 1.72 × 1012 Jones, a peak external quantum efficiency of 19.1%, and an extremely low dark current density of 8.90 × 10−10 A cm−2 under 320 nm at 0 V. To the best of authors knowledge, it is the first report of photodiode‐type UV‐OPDs containing BN‐doped polycyclic aromatic hydrocarbons as active layer to date. And the optimal device shows a significant advantage over the reported 300–380 nm UV‐OPDs. In addition, a 10 × 10 array of organic image sensor is successfully demonstrated, which showcases excellent low‐light imaging capability.

A Suspended, 3D Morphing Sensory System for Robots to Feel and Protect.

Artificial sensory systems with synergistic touch and pain perception hold substantial promise for environment interaction and human-robot communication. However, the realization of biological skin-like functional integration of sensors with sensitive touch and pain perception still remains a challenge. Here, a concept is proposed of suspended electronic skins enabling 3D deformation-mechanical contact interactions for achieving synergetic ultrasensitive touch and adjustable pain perception. The suspended sensory system can sensitively capture tiny touch stimuli as low as 0.02Pa and actively perceive pain response with reliable 5200 cycles via 3D deformation and mechanical contact mechanism, respectively. Based on the touch-pain effect, a visualized feedback demo with miniaturized sensor arrays on artificial fingers is rationally designed to give a pain perception mapping on sharp surfaces. Furthermore, the capability is shown of the suspended electronic skin serving as a safe human-robot communication interface from active and passive view through a feedback control system, demonstrating potential in bionic electronics and intelligent robotics.

Quasi-distributed optical fiber hydrogen leakage detecting system based on bus chain topology structure

Micro-mirror optical fiber hydrogen sensors have the advantages of compact structure and fast demodulation speed. All-optical sensor networks consisting of micro-mirror optical fiber hydrogen sensors are essentially necessary across the hydrogen value chain. A bus chain topology structure hydrogen leakage detecting system based on micro-mirror sensors is proposed and experimentally demonstrated. A compensating optical path with constant power supply is introduced, and the power dissipation scheme is theoretically and experimentally proposed by designating the splitting ratios of the splitters array. By constructing such a network with twenty micro-mirror hydrogen sensors, the system has been experimentally verified with good repeatability and stability under different concentrations of hydrogen. By employing this bus chain topology strategy, a quasi-distributed optical fiber hydrogen leakage detection system with micro-mirror hydrogen sensors array is realized. It will provide a promising solution with high feasibility on multi-point leakage detecting in hydrogen infrastructures.

Detecting Smell/Gas-Source Direction Using Output Voltage Characteristics of a CMOS Smell Sensor

Various organisms, such as dogs and moths, can locate their prey and mates by sensing their smells. Following this manner, if an engineering device with the capability to detect a smell or gas source is realized, it can have a wide range of potential applications, such as searching for landmines, locating gas leaks, and rapid detection of fire. A previous study on the estimation of smell and gas-flow direction successfully detected the smell/gas-source direction in low-wind-velocity environments using a semiconductor gas sensor array. However, some problems are generally associated with the use of semiconductor gas sensors due to the use of heaters. This study aimed to detect the location of a smell/gas source using an integrated CMOS smell sensor array, which operates at room temperature without a heater. The experiment showed that under ideal conditions, the order of gas responses and concentration gradient of the gas enabled the estimation of the direction of the smell/gas-source location on one side of the sensor.

RFX-mod2 diagnostic capability enhancements for the exploration of multi-magnetic-configurations

Abstract The RFX-mod2 device, the upgraded version of the previous RFX-mod with a modified magnetic boundary, is presently under realization and will start to be operated in 2025. Significant upgrades of the diagnostic capabilities have been proposed and are under development. These include a largely increased number of in-vessel magnetic and electrostatic sensors, a new fast reciprocating manipulator for the exploration of the edge plasma in a wide range of experimental conditions, the improved Thomson scattering and soft X-ray diagnostics system for a detailed determination of the behavior of the electron temperature profile, new dedicated systems for the space and time resolved analysis of X-ray spectra and neutron rate, a reflectometric diagnostic for real-time determination of plasma position, two diagnostics devoted to the imaging of light impurities and influxes behavior along with arrays of halo current sensors. These diagnostic upgrades will be accompanied by a significant effort to improve the control of the electron density and of the impurity influxes by means of proper treatment of plasma facing components with in-vessel fixed electrodes distributed over the first wall. The described advancements will allow a deeper understanding of physics phenomena in the wide variety of magnetic configurations, including the tokamak, the reversed-field pinch and the Ultra-low q, which can be produced in RFX-mod2 thanks to its flexibility and unique MHD control capabilities.

Method for measuring non-stationary motion attitude based on MEMS-IMU array data fusion and adaptive filtering

The error characteristics of a typical commercial MEMS-IMU were analyzed. Using 15 ICM-42688 sensors, a 3*5 MEMS-IMU array was designed, and a weighted data fusion method based on Allan variance for the MEMS-IMU array was proposed. This effectively reduces the random measurement errors of the MEMS-IMU, providing a data foundation for the precise measurement of motion and attitude of robots, vehicles, aircraft, and other systems under low-cost conditions. The text describes a measurement method for non-stationary motion attitudes of sports vehicles based on adaptive Kalman-Mahony. Specifically, it first uses adaptive Kalman filter on array sensor data to calculate the measurement noise in real-time and adaptively adjust the filtering gain. Then, it determines the compensation coefficient of the accelerometer to the gyroscope angular velocity based on the motion state of the vehicle, and solves the attitude through complementary filtering to obtain the motion attitude quaternion. Finally, it converts it into the roll angle, pitch angle, and yaw angle of the sports vehicle. Experimental results show that the proposed MEMS-IMU array weighted data fusion method based on Allan variance has significant advantages over traditional single MEMS-IUM methods and traditional average weighting methods in reducing sensor angle random walk and zero drift instability. The proposed adaptive Kalman-Mahony attitude measurement method also shows a significant improvement in the accuracy of non-stationary motion attitude measurement compared to traditional methods.

Design of an enhanced spatial resolution indoor plantar strain and gait analysis setup for biomedical applications

In the recent years, measurement of plantar strain and gait analysis has gained huge attention and plays a pivotal role in monitoring posture related ailments or Diabetic Foot Ulcer (DFU). Fibre Bragg Grating Arrays (closely spaced FBGs), another category of optical sensors, are employed in this study to understand the strain and gait of human foot. These arrays offer critical advantages such as enhanced sensitivity, data acquisition, multiplexing abilities, and sensor location effect compensation. For experimentation, five arrays were distributed among different regions (Upper, Medial, and Heel) of foot and their strain patterns for six volunteers (three male and three female) were recorded for eighty seconds. The data was analysed in two ways, Combined (data of array sensors were averaged to target the whole area) and Individual (for independent analysis of each sensor in array). Incoherent transitions and strain patterns of FBGs within the same arrays observed in individual analysis, explains enhanced resolution capabilities of the arrays. Strain mapping of sensor behaviour also confirmed the identification of various forms of gait i.e., Heel Strike, Flat Foot, Heel Off, and Zero Contact. The average standard deviation values for the arrays was reported below 0.16.

Fully Integrated Multiplexed Wristwatch for Real-Time Monitoring of Electrolyte Ions in Sweat.

Considerable progress has already been made in sweat sensors based on electrochemical methods to realize real-time monitoring of biomarkers. However, realizing long-term monitoring of multiple targets at the atomic level remains extremely challenging, in terms of designing stable solid contact (SC) interfaces and fully integrating multiple modules for large-scale applications of sweat sensors. Herein, a fully integrated wristwatch was designed using mass-manufactured sensor arrays based on hierarchical multilayer-pore cross-linked N-doped porous carbon coated by reduced graphene oxide (NPCs@rGO-950) microspheres with high hydrophobicity as core SC, and highly selective monitoring simultaneously for K+, Na+, and Ca2+ ions in human sweat was achieved, exhibiting near-Nernst responses almost without forming an interfacial water layer. Combined with computed tomography, solid-solid interface potential diffusion simulation results reveal extremely low interface diffusion potential and high interface capacitance (598 μF), ensuring the excellent potential stability, reversibility, repeatability, and selectivity of sensor arrays. The developed highly integrated-multiplexed wristwatch with multiple modules, including SC, sensor array, microfluidic chip, signal transduction, signal processing, and data visualization, achieved reliable real-time monitoring for K+, Na+, and Ca2+ ion concentrations in sweat. Ingenious material design, scalable sensor fabrication, and electrical integration of multimodule wearables lay the foundation for developing reliable sweat-sensing systems for health monitoring.