Sensor Layer Research Articles

Microsphere-Structured Protein Hydrogel Dielectrics for Capacitive Wearable Sensors.

The desire for healthy living has created a crucial need for portable flexible health-monitoring devices based on biomaterials. Toward this end, we report a microsphere-structured hydrogel that uses bovine serum albumin (BSA) as a dielectric layer for capacitive pressure sensors. We developed a theoretical model that describes how stacking dielectric layers of spheres affects the performance of capacitive sensors. We also prepared a prototype sensor featuring the unique microsphere structure to create capacitive sensors with high sensitivity (360.91 strain sensitivity), excellent cyclical stability, and a long service life (over 5000 stretching-compression cycles). Furthermore, the design of the hydrogel sensor allows for easy integration into fabrics to create devices such as smart wristbands, which can collect a diverse range of health data. Thus, BSA-hydrogel-based sensors not only provide safe wearable devices but also advance the performance of high-sensitivity capacitive sensors.

A blockchain-machine learning ecosystem for IoT-Based remote health monitoring of diabetic patients

Diabetes poses a global health challenge, demanding continuous monitoring and expert care for effective management. Conventional monitoring methods lack real-time insights and secure data-sharing capabilities, necessitating innovative solutions that leverage emerging technologies. Existing centralized monitoring systems often entail risks such as data breaches and single points of failure, emphasizing the necessity for a secure, decentralized approach that integrates the Internet of Things (IoT), blockchain, and machine learning for efficient and secure diabetes management. This paper introduces a decentralized, blockchain-based framework for remote diabetes monitoring, IoT sensors, machine learning models, and decentralized applications (DApps). The proposed framework comprises five layers: the IoT Sensor Layer, which collects real-time health data from patients; the Blockchain Layer, leveraging smart contracts on the Ethereum blockchain for secure data sharing and transactions; the machine learning Layer, analyzing patient data to detect diabetes; and the DApps Layer, facilitating interactions between patients, doctors, and hospitals. For intelligent decision-making regarding diabetes based on data collected from different sensors, nine machine learning algorithms, including logistic regression, K-nearest neighbors (KNN), support vector machine (SVM), Decision Tree, Random Forest, AdaBoost, stochastic gradient boosting (SGD), and Naive Bayes, were trained and tested on the PIMA dataset. Based on the performance evaluation parameters such as accuracy, recall, F1-score, and the area under the curve (AUC), it was found that the AdaBoost model achieved the highest predictive accuracy of 92.64%, followed by the Decision Tree with an accuracy of 92.21% in diabetes classification.

Получение и обработка акустических откликов волн Лэмба в датчиках водных растворов базовых вкусов

In this work, the total acoustic wave losses in 128°Y-LiNbO3 wafers during liquid application due to radiation emission of waves into the liquid medium, as well as its viscosity, conductivity, density and dielectric constant of the liquid analyte are measured. Solutions with 5 basic flavors, widely used for calibration and reference creation in liquid media testing, were selected as test liquids. The measurements were performed in the range of 30...60 MHz. After the measurements, the experimental data were presented in the form of polar histograms, from the comparison of areas and shapes of which the flavor of a particular liquid was determined. Then, a principal component analysis (PCA) method was applied to the same experimental results to describe linear elastic wave deformation processes based on experimental data containing known values of physical wave measurements for different types of liquid media, which was previously used to identify gases and predict the properties of various substances from the linear response of a normal acoustic-electronic wave. In this paper, a comparative analysis of the results obtained using polar histograms and the standard PCA classification method is performed. The advantages of the latter are demonstrated. The results of this study are useful both for the development of acoustic sensors without sensor layers and for the application of machine learning methods to data in other types of sensors.

Characterization of a Food‐Safe Colorimetric Indicator Based on Black Rice Anthocyanin/PET Films for Visual Analysis of Fish Spoilage

ABSTRACTThe safety of food products is of prime importance for consumers and manufacturers. Many means can be used to validate a food product's safety before it is consumed. This study is about the preparation, characterization and evaluation of a generally recognized as safe (GRAS) sensitive colorimetric sensor that detects volatile gases (TVB‐N) resulting from fish spoilage, thus indicating the pH variation of packaged fish products. This is performed by coating a thin layer of ink sensors on the surface of the supporting matrix (corona‐treated PET). Various visual pH indicators were prepared based on black rice anthocyanin as an FDA‐approved dye. Black rice, which contains more than 80% cyanidin‐3‐glucoside, is the most prevalent anthocyanin component. Because of its low toxicity and high concentration, it can be utilized as a natural food colourant. pH indicators based on black rice can show distinct colours in various pH: from red (low pH) to violet (4–6) and deep purple/blue (6–7), blue (7–9) to yellowish/light brown (9–13) throughout the acid–base reaction by the analyte. The ink formulation was prepared by incorporating a binder system (PVOH‐PEG) for higher surface wettability, a crosslinking agent (citric acid) for higher adhesion, an antifoaming agent (natural vanillin) and acetic acid as a pH fixing agent. Corona treatments affected substrate surface chemistry in this study. The samples with thermal treatment passed the ASTM D3330 tape test, the 8000 passages for dry sponge and the 25 passages for wet sponge through the abrasion method. Anthocyanin concentration in formulated ink based on calculation by UV–vis spectra is 0.240 mg/100 g. Sensitivity tests towards TVB‐N gases were carried out at a temperature of 4°C to evaluate the performance of colorimetric films with formulated ink along with thermal treatment (temperature: 165°C, time: 5 min) using the volatile gases emitted by the fish sample inside the package.

Fabrication of half-metallic Co2FeAlxSi1–x thin film with small magneto-crystalline anisotropy constant K1

A tunnel magnetoresistance (TMR) sensor is a highly sensitive magnetic sensor workable at room temperature. To achieve smaller magnetic field detection, both a high TMR ratio and small magnetic anisotropy of the free layer are required. In this study, we developed single crystalline Co-based Heusler alloy Co2FeAlxSi1-x films as the free layer of TMR sensors and systematically investigated their crystalline and magnetic properties. The magnetic tunnel junction (MTJ) with these alloys is a promising device for highly sensitive TMR sensors due to their half-metallicity. We evaluated the B2 and L21 ordering parameters SB2 and SL21. SB2 was above 80 % for all the samples and SL21 was 48 % at a maximum, which indicates that all the samples exhibit half-metallicity. In addition, we evaluated their first magneto-crystalline anisotropy constant K1 from magnetization curves. K1 changed from positive to negative as Al component x increases and K1 was about 1200 erg/cc at x = 0.33. These results indicate that Co2FeAlxSi1-x films around x = 0.33 have a good candidate for the free layer of TMR sensors because of their half-metallicity and small magnetic anisotropy.

Synthesis of PDMS Chain Structure with Introduced Dynamic Covalent Bonding for High‐Performance Rehealable Tactile Sensor Application

AbstractIn addressing the increasing demand for wearable sensing systems, the performance and lifespan of such devices must be improved by enhancing their sensitivity and healing capabilities. The present work introduces an innovative method for synthesizing a healable disulfide bond contained in a polydimethylsiloxane network (PDMS−SS) that incorporates ionic salts, which is designed to serve as a highly effective dielectric layer for capacitive tactile sensors. Within the polymer network structure, the cross‐linking agent pentaerythritol tetrakis 3‐mercaptopropionate (PTKPM) forms reversible disulfide bonds while simultaneously increasing polymer softness and the dielectric constant. The incorporation of dioctyl sulfosuccinate sodium salt (DOSS) significantly improves the capacitance and sensing properties by forming an electrical double‐layer through interactions between the electrode charge and salt ions at the contact interface. The developed polymer material‐based tactile sensor shows a strong response signal at low pressure (0.1 kPa) and maintains high sensitivity (0.175 kPa−1) over a wide pressure range (0.1–10 kPa). It also maintains the same sensitivity over 10 000 repeated applications of external pressure and is easily self‐healed against mechanical deformation due to the dynamic disulfide covalent bonding, restoring ≈95% of its detection capacity.

A low-latency graph computer to identify metastable particles at the Large Hadron Collider for real-time analysis of potential dark matter signatures

Image recognition is a pervasive task in many information-processing environments. We present a solution to a difficult pattern recognition problem that lies at the heart of experimental particle physics. Future experiments with very high-intensity beams will produce a spray of thousands of particles in each beam-target or beam-beam collision. Recognizing the trajectories of these particles as they traverse layers of electronic sensors is a massive image recognition task that has never been accomplished in real time. We present a real-time processing solution that is implemented in a commercial field-programmable gate array using high-level synthesis. It is an unsupervised learning algorithm that uses techniques of graph computing. A prime application is the low-latency analysis of dark-matter signatures involving metastable charged particles that manifest as disappearing tracks.

Single-layer Compton camera based on a 1 mm thick pixelated CDTE detectors

Compton camera is a novel γ-camera paradigm that relies upon the kinematics of Compton scattering for image reconstruction. A Conventional Compton camera uses two layers of sensors - the Absorber and the Scatterer. This work reports the proof of concept of a single-layer Compton camera (SLCC) where simultaneous Compton pairs events are registered in a single High-Z semiconductor sensor. The Hybrid pixel detector (HPD) is 1 mm thick, 256 x 256 square pixels with 55 μm pixel pitch CdTe sensor bonded to a Timepix3 readout ASIC. The superior spectroscopic imaging and fast timing capabilities of the Timepix3 readout ASIC coupled with a microscopic and highly pixelated CdTe enable simultaneous event detection of multi-energies occurring at multiple positions. The concept was exemplified by measuring the 122 KeV γ-ray emitted from a 57Co radioisotope source at two positions. Data were captured in the Timepix3 data-driven mode with the KATHERINE readout system via Gigabyte Ethernet data transfer. A bespoke Compton kinematics criterion algorithm implemented in Python 3 IDE was used for data analysis and Compton’s image reconstruction. Numerous events (5.2 million) were captured for 30-minute acquisitions. However, due to the thin nature of CdTe, fewer events (≈ 0.01 %) met the Compton event selection criteria. Nevertheless, the algorithm accurately pinpointed the radioisotope’s location, demonstrating proof of concept of the SLCC system.

Resistive flexible strain sensor based on AgNWs-Gr-PDMS for wearable electronics

In order to obtain a flexible strain sensor with higher sensitivity, a resistive flexible strain sensor based on the AgNWs-graphene-PDMS sensitive layer is prepared in this paper. This paper presents the preparation of a flexible sensitive layer, the preparation and encapsulation of the flexible strain sensor, and the performance tests of the sensor prepared with AgNWs-graphene (AgNWs-Gr) mixtures at different concentrations. The test results indicate that the prepared sensor has a wide detection range with a maximum stretchable length of 118%. The flexible strain sensor prepared with the AgNWs-Gr mixture at a concentration of 5% has the highest sensitivity and the maximum strain sensitivity of up to 236. It also has good repeatability, stability, and rapid response, and it has been tested for practical applications. The results show that the flexible strain sensor has a broad application prospect in fields such as wearable devices and intelligent robots.

Microstructured Porous Capacitive Bio-pressure Sensor Using Droplet-based Microfluidics.

Devices that mimic the functions of human skin are known as "electronic skin," and they must have characteristics like high sensitivity, a wide dynamic range, high spatial homogeneity, cheap cost, wide area easy processing, and the ability to distinguish between diverse external inputs. This study introduces a novel approach, termed microfluidic droplet-based emulsion self-assembly (DMESA), for fabricating 3D microstructured elastomer layers using polydimethylsiloxane (PDMS). The method aims to produce accurate capacitive pressure sensors suitable for electronic skin (e-skin) applications. The DMESA method facilitates the creation of uniform-sized spherical micropores dispersed across a significant area without requiring a template, ensuring excellent spatial homogeneity. Micropore size adjustment, ranging from 100 to 600 μm, allows for customization of pressure sensor sensitivity. The active layer of the capacitive pressure sensor is formed by the three-dimensional elastomer itself. Experimental results demonstrate the outstanding performance of the DMESA approach. It offers simplicity in processing, the ability to adjust performance parameters, excellent spatial homogeneity, and the capability to differentiate varied inputs. Capacitive pressure sensors fabricated using this method exhibit high sensitivity and dynamic amplitude, making them promising candidates for various e-skin applications. The DMESA method presents a highly promising solution for fabricating 3D microstructured elastomer layers for capacitive pressure sensors in e-skin technology. Its simplicity, performance adjustability, spatial homogeneity, and sensitivity to different inputs make it suitable for a wide range of electronic skin applications.

Highly sensitive and wide-range iontronic pressure sensors with a wheat awn-like hierarchical structure

Flexible pressure sensors with high sensitivity and wide sensing range are highly desired in e-skins and wearable electronics. However, there is always a trade-off between high sensitivity and broad sensing range for most flexible pressure sensors. Herein, an artificial wheat awn-like hierarchical structure is designed onto the dielectric layer of the iontronic pressure sensor, realizing both high sensitivity and broad working range. The sensor is constructed by sandwiching a wheat awn-like polyvinyl alcohol/H3PO4 dielectric layer between two transparent electrodes of silver nanowires/thermoplastic polyurethane/ionic liquid. The obtained sensor exhibits a high precision of 1 Pa, a high sensitivity of 47.65 kPa−1 (1–200 Pa), a wide measurement range from 1 Pa to 238 kPa, short response/recovery time of 13 ms/12 ms, outstanding stability over 6000 cycles, as well as good transparency. Considering these excellent properties, the sensor shows promising potential in health monitoring, human–computer interaction, wearable electronics, etc.

Structural and optical properties of Eu3+-doped sol–gel silica–soda glasses

Rare earths (REs) incorporated in glasses, mostly in the form of RE3+ ions, have several applications such as lasers and optical amplifiers, spectral conversion layers for solar cells, light emitters and sensors. In this context, both the composition and the structural properties of the glass, as well as the dopant concentration play an important role in determining the optical properties and the efficiency of the system. Usually, the concentration of REs is small, below 1 at%, to avoid clustering and optical quenching. In this paper, we report the case of sol–gel Eu-doped silica–soda glass films. The addition of soda to silica can reduce RE clustering and precipitation, according to molecular dynamic simulations, but brings structural instabilities to the network. Here, sodium was varied from 10 to 30 at% and Eu from 0 to 8 at%. It was shown that Eu plays a significant role in the stabilization of the matrix, improving the transparency, the refractive index and the thickness of the films. The increase of Eu concentration provides a decrease of site symmetry and an increase of quantum efficiency (QY), reaching 71% for the highest 8 at% Eu doping, with remarkable absence of concentration quenching.

Perovskite QDs embedded in polymer as a wavelength-shifting layer for UV-sensitized silicon sensors

Detection of UV radiation is becoming increasingly important for many applications. Here we present novel UV sensor construction on the basis of standard Si detector modification. Wavelength shifting mechanism is achieved by the luminescence effect of perovskite quantum dots embedded in polymer layers. We comprehensively characterize these composite materials, various sensor modification routes and the optical properties of UV-enhanced visible sensors. Modified S1227-16 BG silicon photodiodes and S13360-1375 CS MPPC photodetectors with the enhanced UV response are successively manufactured.

Linear 3D piezo-elasticity theory for static and free vibration analysis of piezoelectric/GOP/CNTs panels submerged in fluid

The objective of this study is to analyze the bending and free vibration analysis of a new type of smart hybrid FG composite plate integrated with piezoelectric layers that are submerged in fluid. The proposed composites for some layers are carbon nanotubes (CNTs) and for some other are graphene oxide powder (GOP), along with two layers of piezoelectric sensors and actuators. Furthermore, two distinct combinations, namely GOP/CNTs/GOP and CNTs/GOP/CNTs, are analyzed. To capture the structural response of the system, exact linear three-dimensional piezoelasticity theory is employed to derive a semi-analytic solution for composite plates of arbitrary thickness, thereby avoiding simplifications in constitutive relations. The computation of fluid interaction components is performed using the Rayleigh integral method, and the coupling of structural and fluid interactions in the equations is addressed without imposing constraints on fluid density or assuming a far-field approximation. Parametric studies are carried out for the first time to investigate the impact of dimension ratios, reinforced distributions, and weight fractions of nanofiller on the natural frequency and static behaviour of the novel hybrid submerged smart composites.

Hydrogen-Bond Acidic Materials in Acoustic Wave Sensors for Nerve Chemical Warfare Agents' Detection.

The latest trends in the field of the on-site detection of chemical warfare agents (CWAs) involve increasing the availability of point detectors to enhance the operational awareness of commanders and soldiers. Among the intensively developed concepts aimed at meeting these requirements, wearable detectors, gas analyzers as equipment for micro- and mini-class unmanned aerial vehicles (UAVs), and distributed sensor networks can be mentioned. One of the analytical techniques well suited for use in this field is surface acoustic wave sensors, which can be utilized to construct lightweight, inexpensive, and undemanding gas analyzers for detecting CWAs. This review focuses on the intensively researched and developed variant of this technique, utilizing absorptive sensor layers dedicated for nerve CWAs' detection. The paper describes the mechanism of the specific interaction occurring between the target analyte and the sensing layer, which serves as the foundation for their selective detection. The main section of this paper includes a chronological review of individual achievements in the field, largely based on the peer-reviewed scientific literature dating back to the mid-1980s to the present day. The final section presents conclusions regarding the prospects for the development of this analytical technique in the targeted application.

Sensitivity of ZnO Film-Based X-ray Sensors: A Comprehensive Study on the Effect of Thickness of ZnO Layer.

For all types of photosensors, efficient absorption of photons of particular interest is very essential. We report the effect of thickness of the ZnO layer in ZnO film-based X-ray sensors. A set of five samples Z1, Z2, Z3, Z4, and Z5 is developed by varying the thickness of the ZnO layer between 10 and 73 μm. The dark I-V characteristics of the sensors show a "pseudorectifying" type nature. A quantitative analysis of the dark currents reveals that the dark I-V characteristics are affected by space charge limited current (SCLC) due to intrinsic defects present in the ZnO films. The effect of the SCLC is prominent in the thicker films in comparison to the thinner ones. The sensors show high signal-to-noise (S/N) ratio below 5.0 V bias voltage. The S/N ratio is found to increase with the thickness of the ZnO layer due to efficient absorption of X-ray photons. The photoresponse characteristics of the sensors against dose rate are sublinear between 0.015 and 0.234 Gy/s. The photoresponse time of the sensors are found to be nearly 1 s. The sensitivities of Z1, Z2, Z3, Z4, and Z5 sensors at 4.5 V bias voltage for 0.234 Gy/s dose rate are estimated to be 55.51, 337.08, 312.01, 152.81, and 103.52 μC/Gy cm3, respectively. The sensitivity of the device is found to increase with increase in thickness of the ZnO layer and reaches an optimum level for the thickness of about 19-26 μm. Beyond this range, the sensitivity is found to decrease due to the Schubweg effect.

Expanding the applications of the wear-resistant titanium aluminum nitride thin-film to include temperature sensing

This study investigates an approach to temperature sensing by integrating Titanium Aluminum Nitride (TiAlN), originally engineered for wear and corrosion applications, as a temperature sensor within a multilayered thin film system. A nitride multilayer system was developed by physical vapor deposition (PVD) using a single four-target magnetron sputtering chamber; intermediate vacuum interruption steps were employed for masking procedures. The multilayer architecture design aimed to provide the sensor layer with mechanical protection and electrical shielding. Structural and electrical characterization of the TiAlN single layer revealed semiconductor behavior and stable electrical resistance up to 750 °C, with minimal signal stabilization requirements. Despite the higher Al content, the TiAlN temperature sensor exhibited a cubic crystal structure characterized by diffuse nanolayers, resulting from a two-fold rotational deposition and target configuration. A detailed examination of the multilayer system cross-section containing the TiAlN sensor was conducted using scanning transmission electron microscopy (STEM). The analysis revealed its columnar morphology with the presence of typical PVD growth defects, including voids and droplets. While the presence of these defects may impact the electrical characteristics of the sensor, the selected experimental conditions effectively maintained the structural integrity of the multilayer system despite the vacuum interruptions caused by masking procedures. Validation experiments confirmed the functionality of the multilayer system for temperature measurements up to 400 °C. The signal acquisition system addressed room temperature resistance variations and low sensitivity (thermistor coefficient ∼100 K), resulting in a measured error of approximately 6%. This study demonstrates promising results of TiAlN as a temperature sensor within a multilayered system, expanding its range of potential applications.

A flexible bimodal self-powered optoelectronic skin for comprehensive perception of multiplexed sensoring signals

Multi-modal electronics skin that mimics collaborative operation of natural skin establishes a substantial foundation for next-generation smart healthcare, biomimetic science and related interdisciplinary fields. However, the power consumption of multi-channels and the decoupling complexity of fused-information that determine the effectiveness of the system still remain enormous challenge. Here, a bimodel self-powered optoelectronic fusion system with a vertical integration structure to achieve mechanical and illumination perception is reported, enabling simultaneous monitoring of human motion signal and environmental illumination. This device comprises a photo-conductive layer of MAPbI3-PVA and a teflon (PTFE) friction layer of TENG-based sensor, characterizing the mechanical and illuminance information in the form of pulse electrical signals and continuous resistance variation curves, respectively. This bimodel sensor exhibits the highest photoelectric responsivity of 64 mA/W and saturated output power of 156 μW/cm2 within the visible illumination range. Moreover, the environmental and mechanical stability of the device have been significantly improved, which is attributed to the inherent flexibility and hydrophilicity of PVA wrapped in perovskite grains. Finally, A 3×3 bimodel array is attached onto the volunteer's cervical vertebra for classifying motion posture and ambient illuminance by monitoring the surface tension distribution under different lighting conditions, validating the feasibility and promotion potential for application scenarios.

Sintesis polianilin (PANi) dengan metode polimerisasi interfasial sebagai bahan dasar pembuatan sensor gas amonia (NH3)

One of the main components in IoT-based devices is sensors. Polyaniline is a conductive polymer that has great potential to be developed as an active layer for chemical sensors because it has high sensitivity, is easy to synthesize and its electrical conductivity can be adjusted. This study aims to synthesize and characterize polyaniline using the interfacial polymerization method. In this study, polyaniline was synthesized by varying the aniline concentration of 2, 3, and 5 M, then its functional groups were characterized using FTIR and its conductivity and sensitivity were measured with an LCR meter. The result shows that polyaniline is in the form of emeraldine salt which is characterized by the formation of absorption bands at concentrations of 2, 3, and 5 M, respectively, 1,141.86 cm-1, 1,139 cm-1 and 1,139.93 cm-1. The highest conductivity was obtained at a concentration of 2 M, namely 4.9x10-5 and a sensitivity of 82.8% for an ammonia concentration of 100 ppm. So it can be concluded that the polyaniline obtained is a form of semiconducting emeraldine salt.

Active vibration control of rotating smart bidirectional FGPTC subjected to internal mechanical shock

This study considers the active vibration control of a sandwich truncated cone, whose intermediate layer is made of bidirectional functionally graded (FG) porous material bonded with integrated piezoelectric actuator and sensor layers on its outer and inner surfaces. The material properties of the bidirectional functionally graded porous truncated cone (FGPTC), with even and uneven porosity distributions along the length and thickness directions, are changed using a power law function. The governing motion equations utilize the two-dimensional (2D) axisymmetric theory of elasticity rather than simple shell theories. The solving of the governing motion equations is accomplished through the utilization of graded finite element and Newmark methods. The study investigates the impact of dimensions, parameters, and porosity types on transient response behavior, including the semi-vertex angle and the ratio of truncated cone length to outer radius. Furthermore, the effects of power index, porosity volume fractions, rotational velocities, and boundary conditions are examined. Active vibration control (AVC) of the piezoelectric FGPTC is achieved by employing a closed-loop control algorithm based on velocity feedback. Several numerical simulations are conducted to evaluate the effectiveness of the proposed active vibration control system in reducing structural vibrations. The results demonstrate significant reductions in vibration amplitudes and improved structural stability achieved through the active control approach.