Sensor Architecture Research Articles

Fe3O4-Cu-BTC/MWCNTs modified electrodes for real-time chlorine monitoring in aqueous solution.

Aefficient sensor is presentedfor detecting free chlorine in water by decorating glassy carbon electrodes (GCE) via multi-walled carbon nanotubes (MWCNTs) and Fe3O4-Cu-BTC composite. After the characterization of prepared materials by field emission scanning electron microscopy (FE-SEM), energy-dispersive X-ray spectroscopy (EDX), X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FT-IR) techniques, and N2 adsorption-desorption isotherm, the electrochemical properties of Fe3O4-Cu-BTC/MWCNTs/GC-modified electrode were assessed with cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS). CV and chronoamperometry measurement in phosphate buffer solution with pH 7.0 proved the capability of the designed sensor to detect free chlorine. With amperometric detection, the modified electrode exhibits a linear responseinthe 0.1to400.0ppm range towards free chlorine with a detection limit (LOD) (S/N = 3) of 0.0044ppm, sufficient to control swimming pool water. To assay the practicability of the designed sensor in real situations, interferences of common ions and dissolved oxygen were tested on free chlorine determination and showed admirable selectivity. The proposed sensor also provides satisfactory results of free chlorine measurement in different real samples of swimming pool waters. The results of this work affirmed that MOF composite could be a promising material in the architecture of free chlorine electrochemical sensors in aqueous media.

Inductive Power Transfer Coil Misalignment Perception and Correction for Wirelessly Recharging Underground Sensors.

Field implementations of fully underground sensor networks face many practical challenges that have limited their overall adoption. Power management is a commonly cited issue, as operators are required to either repeatedly excavate batteries for recharging or develop complex underground power infrastructures. Prior works have proposed wireless inductive power transfer (IPT) as a potential solution to these power management issues, but misalignment is a persistent issue in IPT systems, particularly in applications involving moving vehicles or obscured (e.g., underground) coils. This paper presents an automated methodology to sense misalignments and align IPT coils using robotic actuators and sequential Monte Carlo methods. The misalignment of a Class EF inverter-driven IPT system was modeled by tracking changes as its coils move apart laterally and distally. These models were integrated with particle filters to estimate the location of a hidden coil in 3D, given a sequence of sensor measurements. During laboratory tests on a Cartesian robot, these algorithms aligned the IPT system within 1 cm (0.025 coil diameters) of peak lateral alignment. On average, the alignment algorithms required less than four sensor measurements for localization. After laboratory testing, this approach was implemented with an agricultural sensor platform at the Utah Agricultural Experiment Station in Kaysville, Utah. In this implementation, a buried sensor platform was successfully charged using an aboveground, vehicle-mounted transmitter. Overall, this work contributes to the field of underground sensor networks by successfully integrating a self-aligning wireless power delivery system with existing agricultural infrastructure. Furthermore, the alignment strategy presented in this work accomplishes coil misalignment correction without the need for complex sensor or coil architectures.

Advancements in carbon nanotube-based sensors for human motion detection

ABSTRACT Carbon nanotube (CNT)-based sensors are revolutionizing human motion detection through their unique combination of flexibility, sensitivity, and durability. This review examines the transformative impact of these sensors across healthcare, sports science, and wearable technology. Recent breakthroughs in hierarchical sensor architectures and hybrid materials have achieved unprecedented performance, with sensitivity exceeding conventional sensors by orders of magnitude and response times in milliseconds. These advances have enabled applications ranging from rehabilitation monitoring to high-precision athletic performance analysis. The integration of artificial intelligence with CNT sensors is opening new possibilities in personalized healthcare and human-machine interfaces. While challenges remain in manufacturing scalability and long-term stability, emerging developments in self-powered systems and biocompatible designs point toward widespread adoption in next-generation wearable devices. This review synthesizes current progress and identifies promising directions for future innovation in CNT-based motion sensing technology, highlighting its potential to transform how we monitor and understand human movement.

Advances in flexible ionic thermal sensors: present and perspectives.

Ionic thermal sensors (ITSs) represent a promising frontier in sensing technology, offering unique advantages over conventional electronic sensors. Comprising a polymer matrix and electrolyte, these sensors possess inherent flexibility, stretchability, and biocompatibility, allowing them to establish stable and intimate contact with soft surfaces without inducing mechanical or thermal stress. Through an ion migration/dissociation mechanism similar to biosensing, ITSs ensure low impedance contact and high sensitivity, especially in physiological monitoring applications. This review provides a comprehensive overview of ionic thermal sensing mechanisms, contrasting them with their electronic counterparts. Additionally, it explores the intricacy of the sensor architecture, detailing the roles of active sensing elements, stretchable electrodes, and flexible substrates. The decoupled sensing mechanisms for skin-inspired multimodal sensors are also introduced based on several representative examples. The latest applications of ITS are categorized into ionic skin (i-skin), healthcare, spatial thermal perception, and environment detection, regarding their materials, structures, and operation modes. Finally, the perspectives of ITS research are presented, emphasizing the significance of standardized sensing parameters and emerging requirements for practical applications.

Innovative mechanical sensors architectures and their physics applications

Innovative mechanical sensors architectures and their physics applications

Robust framework for modelling long range dToF SPAD Lidar performance.

Time-of-flight Lidars based on single-photon avalanche diode (SPAD) detector arrays are emerging as a strong candidate technology for long range three-dimensional imaging in challenging environmental conditions. However, reaching this bound requires the existence of an unbiased estimator, which does not necessarily exist for data acquired by realistic SPAD-based Lidar systems. Here, we extend our existing SPAD Lidar modelling framework to include a novel metric, which we term the 'Binomial Separation Criterion', as a means of quantifying whether a depth estimation algorithm will reach the Cramér-Rao bound (CRB). This enables us to evaluate the performance of SPAD Lidar systems over a significantly larger state space range than previously, i.e., evaluation in scenarios where the total number of measured photons and peak signal-to-noise ratio change by an order of magnitude. We validate this new approach against data acquired from two separate depth imaging systems, one operating at 532 nm and one at 1550 nm wavelengths, measuring targets at a range of 1.4 km. We present strong agreements between the outputs of our framework and the experimental results across different operating wavelengths, spatial resolutions, target types, and sensor architectures. We expect this framework to serve as a highly versatile tool with wide-ranging applicability to the SPAD Lidar community.

A highly sensitive dual-core PCF-SPR sensor based on ITO and Au for detecting refractive index and temperature

Abstract Sensors have been instrumental in driving technological progress and enhancing quality of life by delivering precise data and enabling intelligent responses across a multitude of disciplines. In alignment with the advancement of technology and the demands of both industrial production and everyday life, a dual-core PCF-SPR sensor was developed. The sensor, based on D-type photonic crystal fiber and incorporating ITO and Au, was designed for the simultaneous detection of refractive index and temperature. Research results demonstrate that by using the finite element method, the maximum sensitivity of the structure in the refractive index detection range of 1.33-1.39 reached 18,100 nm/RIU, and the maximum sensitivity in the temperature detection range of 10 °C-50 °C reached －12.3 nm/°C. The refractive index and temperature detection channels operate independently of each other. This sensor architecture enables simultaneous dual-parameter measurement of refractive index and temperature, is lightweight and highly sensitive, and possesses potential applications in cancer cell detection and tsunami prevention.

Advanced Nested Coaxial Thin-Film ZnO Nanostructures Synthesized by Atomic Layer Deposition for Improved Sensing Performance

We report a new synthesis method for multiple-walled nested thin-film nanostructures by combining hydrothermal growth methods with atomic layer deposition (ALD) thin-film technology and sacrificial films, thereby increasing the surface-to-volume ratio to improve the sensing performance of novel ZnO gas sensors. Single-crystal ZnO nanorods serve as the core of the nanostructure assembly and were synthesized hydrothermally on fine-grained ALD ZnO seed films. Subsequently, the ZnO core nanotubes were coated with alternating sacrificial coaxial 3D wrap-around ALD Al2O3 films and ALD ZnO films. Basically, the center nanorod was coated with an ALD 3D wrap-around Al2O3 sacrificial layer to realize a nested coaxial ZnO thin-film nanotube. To increase the surface-to-volume ratio of the nested multiple-film nanostructure, both the front and backside of the nested coaxial ZnO films must be exposed by selectively removing the intermittent Al2O3 sacrificial films. The selective removal of the sacrificial films exposes the front and backside of the free-standing ZnO films for interaction with target gases during sensing operation while steadily increasing the surface-to-volume ratio. The sensing response of the novel ZnO gas sensor architecture with nested nanotubes achieved a maximum 150% enhancement at low temperature compared to a conventional ZnO nanorod sensor.

Broadband cavity-enhanced optical flux monitoring

This work describes a new type of sensor for growth process monitoring named broadband cavity-enhanced optical flux monitoring sensor (BBCE-OFM). Like existing optical flux monitoring (OFM) solutions, it relies on absorption spectroscopy. However, the implementation of an optical cavity reduces the measurement uncertainty, enabling efficient operation even at very low growth rates. Using the BBCE-OFM sensor mounted in our solid-source oxide molecular beam epitaxy reactor, we achieved an uncertainty of ±2% on the measurement of Sr and Ti growth rates in SrTiO3 at around 1 Ml/min, to be compared to the ±16% obtained in the same conditions using a conventional OFM setup. Furthermore, our sensor architecture, based on an echelle monochromator and LEDs replacing the hollow cathode lamps used in standard OFM sensors, is more robust against drift.

Electroanalysis of Statin Drugs: A Review on the Electrochemical Sensor Architectures Ranging from Classical to Modern Systems.

An overview of the latest advances in the design of electrochemical sensor architectures dedicated to the determination of drugs from the statin class is presented in this review. Statins are drugs widely consumed for cholesterol control, and their determination in different matrices through the application of electroanalysis is growing considering advantages such as operational simplicity, lower cost and ease of sample preparation. Within the context of statins, electrochemical sensor architectures can be subdivided into conventional/classical electrodes such as glassy carbon electrodes, carbon paste electrodes, pencil graphite electrodes, boron-doped diamond electrodes and metallic electrodes, and more modern electrode systems, including the screen-printed electrodes and 3D-printed electrodes. Thus, different aspects related to the preparation of these electrochemical sensors and analytical performance are presented, also reflecting advances in terms of designs of new architectures and possible improvements not previously reviewed. Analyzed samples, advantages and disadvantages of different implemented sensor's modification strategies and perspectives for the electroanalysis of statins are also included throughout the work.

DESIGN AND FABRICATION OF SHAPE MORPHING MAGNETO-IMPEDANCE MAGNETIC SENSOR

The magnetoimpedance (MI) effect is characterized by the alteration in the impedance of soft magnetic materials when subjected to a magnetic field while a high-frequency alternating current flows through them. In this study, we engineered two distinct sensor architectures utilizing amorphous FeCSi magnetic ribbon: a single-bar structure with the dimension of 10 mm × 90 μm × 20 μm and a meander structure consisting of 13 parallel single bars. These structures were miniaturized through advanced techniques combining laser engraving and chemical etching. The magnetic analysis reveals that the meander structure exhibits a pronounced dependency on the angle θ between the magnetic field and the sensor orientation, enhancing its soft magnetic properties by up to fivefold compared to the single-bar design. This enhancement might be attributed to a reduction in the demagnetization effect and shape anisotropy energy within the meander sensor. Furthermore, the analysis of the MI effect indicates that the resonance frequency remains unaffected by external magnetic fields for both sensor types. Notably, the meander sensor demonstrates exceptional MI ratio values exceeding 82%, representing a remarkable 24-fold increase over the 3.5% observed in the single-bar sensor. Additionally, the isotropy - quantified as the MI ratio's dependence on angle θ, and magnetic field sensitivity are significantly improved in the meander configuration. These advancements in soft magnetic and physical properties are correlated to the domain structure of the sensor, particularly its transverse magnetic permeability, as evidenced by micromagnetic simulations conducted using Mumax3. With its superior MI ratio, isotropy, and heightened magnetic field sensitivity, the meander-type magnetic field sensor presents substantial potential for applications across diverse fields, ranging from biological systems to specialized practical missions.

An 11-bit two-step column-shared ADC based on Flash/SS architecture for CMOS image sensor

Traditional single-slope analog-to-digital converter (SS ADC) faces a speed limitation that constrains the exposure speed of CMOS image sensors (CIS). To enhance the conversion speed of SS ADCs used in high frame rate CIS, a two-step column-shared ADC based on Flash/SS architecture is proposed. The ADC design approach is based on the concepts of time compression and multi-column sharing. On one hand, a Flash ADC and differential ramps are introduced while two comparators are multiplexed to enhance the conversion speed. On the other hand, a multi-column shared design is employed in some circuits to reduce the average area and power consumption per column. Under a design environment of 256 × 256 pixel resolution, the simulation results show that the row time of ADC is 5.4μs, the column-level average power consumption is 129.5 μW, and the FoMa is 527 fJ/step. Compared to the conventional 11-bit two-step SS ADC, the proposed ADC not only optimizes quantization speed but also simplifies the redundant calibration structure.

Spiking Neural Network Pressure Sensor.

Von Neumann architecture requires information to be encoded as numerical values. For that reason, artificial neural networks running on computers require the data coming from sensors to be discretized. Other network architectures that more closely mimic biological neural networks (e.g., spiking neural networks) can be simulated on von Neumann architecture, but more important, they can also be executed on dedicated electrical circuits having orders of magnitude less power consumption. Unfortunately, input signal conditioning and encoding are usually not supported by such circuits, so a separate module consisting of an analog-to-digital converter, encoder, and transmitter is required. The aim of this article is to propose a sensor architecture, the output signal of which can be directly connected to the input of a spiking neural network. We demonstrate that the output signal is a valid spike source for the Izhikevich model neurons, ensuring the proper operation of a number of neurocomputational features. The advantages are clear: much lower power consumption, smaller area, and a less complex electronic circuit. The main disadvantage is that sensor characteristics somehow limit the parameters of applicable spiking neurons. The proposed architecture is illustrated by a case study involving a capacitive pressure sensor circuit, which is compatible with most of the neurocomputational properties of the Izhikevich neuron model. The sensor itself is characterized by very low power consumption: it draws only 3.49 μA at 3.3 V.

Design of photonic crystals for nanokelvin-resolution thermometry

High-resolution thermometry is key for the development of calorimeters, bolometers, and high-stability light sources, as well as for probing dissipation and transport in microelectronics and quantum devices. Achieving nanokelvin-level temperature resolution at room temperature requires using large optical cavities, which are unsuitable for microscale integration. Here we computationally design a one-dimensional photonic crystal Band Edge Thermometer that achieves significant temperature sensitivity by combining: (i) the abrupt variation in optical properties of a direct bandgap semiconductor at the band edge, and (ii) a large quality factor in a resonant photonic structure. Two devices are designed which are constructed from GaAs/AlAs and GaN/AlN multilayer structures. The optimal sensor design features an extremely large thermoreflectance coefficient of 60.6 K−1 and a thermal time constant of 1.1 µs, with a sensor thickness of only 6.7 µm. The projected thermometry noise floor is 84 nK.Hz-½ for the GaAs/AlAs sensor and 35 nK.Hz-½ for the GaN/AlN sensor. The designed sensor architecture is expected to enable a broad range of applications in microcalorimetry and bolometry where a high temperature resolution combined with microscale sensor footprint is required.

Performance Evaluation of Refractive Index Biosensor in THz Regime for Clinical Applications: A Simulation Approach

In this manuscript, a novel innovative HC-PCF sensor model in THz regime is introduced integrated with an optimization approach. The suggested sensor architecture provides crucial advantages precise identification of healthy and ill tissues in healthcare industry. The HC-PCF, meticulously constructed with specific dimensions, significantly increases the sensor sensitivity and specificity to 99.37% and 99.75% respectively. Healthcare industries are at the core of investigations and are undoubtedly crucial to modernize the prognosis procedures. It is a discipline that is continually expanding and searching for new approaches to raise the standard for efficacy, sensitivity, and accuracy. Recently, THz PCF has emerged with incredible potential in all the areas of biomedical applications. The importance in using THz sensors in this research is to detect the ill tissues, an important component in the categorizing diabetes. The integrated sensor architecture provides higher level of sensitivity, with a confinement loss of 0.05 in 0.23 s processing time for a RI range of 1.28–1.39. This research highlights the capability of combining PCF with optimization to improvise the healthcare industry, offering an economical and efficient diagnostic solution across the fields.

An efficient cluster head selection in WSNs using transient search optimization (TSO) algorithm

SummaryIn this manuscript, a nature‐inspired optimization method, named transient search optimization (TSO), is proposed. Energy‐based monetary custom is a serious issue on the wireless sensor network (WSN). Here, the network clustering is an effectual technique to reduce node energy depletion and increased network lifetime. The proposed method aims to improve the efficiency of sensor nodes (SNs) by reducing their detachment, minimizing energy transmission, and protecting excessive energy stored in the nodes. This approach helps decrease delays, reduce traffic flow, and optimize network performance. The execution is implemented on the NS2 software. The experimental outcomes exhibit that the proposed system performs better based on two wireless sensor architectures, such as 50 nodes and 100 nodes. The parameter produces 52.24%, 54.38%, and 56.37% better network lifetime; 44.71%, 46.24%, and 49.45% higher alive node; and 39.26%, 36.26%, and 28.65% lesser dead SNs compared with existing techniques like multi‐objective cluster head (CH)–based energy‐aware optimized routing approach in wireless sensor network (MOCH‐ORR‐WSN), energy effective CH selection with improved sparrow search algorithm in WSN (ECH‐ISS‐WSN), and energy effectual cluster basis routing protocol under butterfly optimization along ant colony optimization algorithms for WSN (EEC‐BOA‐ACO‐WSN).

4D-STEM and Eels Analysis of Complex C-Based Sensor Architectures

Transforming high-carbon precursors into open-porous carbon foams and coatings via thermal processes is gaining attention as a sustainable method for various applications, including catalysis, energy utilization, and sensing [1]. In this research, we adopt a one-step laser patterning approach to selectively pyrolyze doctor-bladed ink coatings on flexible PET substrates, thereby producing highly porous, intricately designed CO2 sensor structures with a thickness of about 50 µm. Our ink formulation includes glucose as a pore-forming agent and adenine as a nitrogen source to enhance sensing capabilities. Laser processing in an oxygen-rich setting results in flexible, highly porous sensor heterostructures characterized by distinct areas enriched with nitrogen and oxygen functionalities. The laser intensity’s attenuation with depth leads to the development of a distinctly porous graphitic surface layer (serving as the electrical transducer layer) and a denser nitrogen-enriched lower sensor layer, linked by a narrow transitional region [2]. To understand the formation and functionality of these sensors, we conducted an in-depth TEM analysis of cross-sections of the complete device, prepared through ultramicrotomy cross-sectioning. STEM-EELS elemental distribution maps distinctly show the chemical composition differences between the upper and lower layers of the sensor. Principal component analysis was utilized to separate the complex sensor structures into their constituent crystalline and amorphous carbon and nitrogen-containing phases. 4D-STEM analysis exposed the arrangement of the crystalline graphitic phase and the orientation of graphite basal planes adjacent to the pores of the open-porous sensor. Analyzing these structural parameters is essential for understanding the electrical performance of the sensor, as depicted in Figure 1 [3]. Figure 1: A (top)) SEM micrograph of sensor embedded in epoxy, (bottom) depth-dependent thermal laser intensity attenuation; B (left)) HA ADF-STEM micrograph showing different sensor layers, (middle) STEM-EELS nitrogen distribution map, (right) PCA bond analysis, C) HRTEM images of sensor from transducer (top) and sensor (bottom) layers with SAED image of respective ROIs (inset); D) 4D-STEM analysis depicting misalignment angle between graphitic carbon basal plane normal relative to the pore surface normalReferences[1] M. Hepp, et al. npj Flexible Electronics 6, 1-9 (2022)[2] H. Wang, et al. Advanced Functional Materials 32, 2207406 (2022)[3] C. Ophus, et al. Microscopy and Microanalysis 28, 390-403 (2022) Acknowledgements: We acknowledge use of the DFG-funded Micro-and Nanoanalytics Facility (MNaF) at the University of Siegen (INST 221/131-1). Figure 1

Highly‐Sensitive and High Operating Range Fully‐Printed Humidity Sensors Based on BiFeO3/BiOCl Heterojunctions

AbstractFully‐printed humidity sensors based on BiFeO3/BiOCl heterojunctions fabricated using a two‐step process with serigraphic printing are reported. Most importantly, this unique sensor architecture provides a broader relative humidity sensing range compared to pristine BFO sensors due to a synergistic effect between dense networks of BiOCl nanosheets synthetized atop BFO powders. With surface‐to‐weight ratios reaching 7.75 m2 g−1, these heterostructures increase the sensitivity and operating range of BFO‐based humidity sensors. While previously reported BFO humidity sensors only detect relative humidities above 30%, The BFO/BiOCl heterojunctions can measure relative humidities as low as 15% due to their increased surface area. Optimal growth and packing of the BiOCl nanosheet/BFO powder heterostructure are achieved by tuning the loading of the BFO powder and simultaneously forming the BiOCl sheets by chemical etching and annealing of the BFO powder. Excellent performance of optimized sensors including tracking and monitoring different types of breathing are demonstrated while mounted on an oxygen mask.

A Review of Sensor Fusion Techniques

Sensor fusion involves combining data from multiple sources, resulting in more detailed and reliable results. Sensor fusion techniques play an important role in many application areas for industries such as defense, automotive, military and healthcare. Sensor fusion techniques, which include various approaches, have been examined independently of the sector, and a broader review has been performed. In addition to covering the advantages and challenges of different sensor fusion techniques in-depth, this work also provides a comprehensive classification of sensor fusion algorithms, techniques, and architectures. This comprehensive classification aims to guide researchers in making choices according to their needs by providing an understanding of sensor fusion techniques and algorithms. Additionally, when evaluating the future potential of sensor fusion, the focus is on how fusion techniques may evolve with increasing complexity and diversity. This study provides an in-depth analysis of the existing literature, contributing to the advancement of research in sensor fusion and the development of more effective systems.

High Sensitivity and High Throughput Magnetic Flow CMOS Cytometers With 2D Oscillator Array and Inter-Sensor Spectrogram Cross-Correlation.

In the paper, we present an integrated flow cytometer with a 2D array of magnetic sensors based on dual-frequency oscillators in a 65-nm CMOS process, with the chip packaged with microfluidic controls. The sensor architecture and the presented array signal processing allows uninhibited flow of the sample for high throughput without the need for hydrodynamic focusing to a single sensor. To overcome the challenge of sensitivity and specificity that comes as a trade off with high throughout, we perform two levels of signal processing. First, utilizing the fact that a magnetically tagged cell is expected to excite sequentially an array of sensors in a time-delayed fashion, we perform inter-site cross-correlation of the sensor spectrograms that allows us to suppress the probability of false detection drastically, allowing theoretical sensitivity reaching towards sub-ppM levels that is needed for rare cell or circulating tumor cell detection. In addition, we implement two distinct methods to suppress correlated low frequency drifts of singular sensors-one with an on-chip sensor reference and one that utilizes the frequency dependence of the susceptibility of super-paramagnetic magnetic beads that we deploy as tags. We demonstrate these techniques on a 7 ×7 sensor array in 65 nm CMOS technology packaged with microfluidics with magnetically tagged dielectric particles and cultu lymphoma cancer cells.