Search Results (737)

Thermal management is an area of study in electronics focused on managing temperature to improve reliability and efficiency. When temperatures are too high, cooling systems are activated to prevent overheating, which can lead to reliability issues. To monitor the temperatures, sensors are often placed on-chip near hotspot locations. These sensors should be very small to allow them to be placed among compact, high-activity circuits. Often, they are connected to a central control circuit located far away from the hot spot locations where more area is available. This paper proposes sensing units for a novel temperature sensing architecture in the TSMC 180 nm process. This architecture functions by approximating the current through the sensing unit at a reference voltage, which is used to approximate the temperature in the digital back end using fitting functions. Sensing units are selected based on how well its temperature–current relationship can be modeled, sensing unit area, and power consumption. Many sensing units will be experimented with at different reference voltages. These temperature–current curves will be modeled with various fitting functions. The sensing unit selected is a diode-connected p-type MOSFET (Metal Oxide Semiconductor Field Effect Transistor) with a size of W = 400 nm, L = 180 nm. This sensing unit is exceptionally small compared to existing work because it does not rely on multiple devices at the sensing unit location to generate a PTAT or IPTAT signal like most work in this area. The temperature–current relationship of this device can also be modeled using a 2nd order polynomial, requiring a minimal number of trim temperatures. Its temperature error is small, and the power consumption is low. The range of currents for this sensing unit could be reasonably made on an IDAC. Full article

Gas sensors are considered a highly effective non-destructive technique for monitoring the quality and safety of food materials. These intelligent sensors can detect volatile profiles emitted by food products, providing valuable information on the changes occurring within the food. Gas sensors have garnered significant interest for their numerous advantages in the development of food safety monitoring systems. The adaptable characteristics of gas sensors make them ideal for integration into production lines, while the flexibility of certain sensor types allows for incorporation into packaging materials. Various types of gas sensors have been developed for their distinct properties and are utilized in a wide range of applications. Metal-oxide semiconductors and optical sensors are widely studied for their potential use as gas sensors in food quality assessments due to their ability to provide visual indicators to consumers. The advancement of new nanomaterials and their integration with advanced data acquisition techniques is expected to enhance the performance and utility of sensors in sustainable practices within the food supply chain. Full article

The early detection of liver cirrhosis (LC) is crucial due to its high morbidity and mortality in advanced stages. Reliable, non-invasive diagnostic tools are essential for timely intervention. Exhaled human breath, reflecting metabolic changes, offers significant potential for disease diagnosis. This paper focuses on the emerging role of sensor array-based volatile organic compounds (VOCs) analysis of exhaled breath, particularly using electronic nose (e-nose) technology to differentiate LC patients from healthy controls (HCs). This study included 55 participants: 27 LC patients and 28 HCs. Sensor’s measurement data were analyzed using machine learning techniques, such as principal component analysis (PCA), discriminant function analysis (DFA), and support vector machines (SVMs) that were utilized to uncover meaningful patterns and facilitate accurate classification of sensor-derived information. The diagnostic accuracy was thoroughly assessed through receiver operating characteristic (ROC) curve analysis, with specific emphasis on assessing sensitivity and specificity metrics. The e-nose effectively distinguished LC from HC, with PCA explaining 92.50% variance and SVMs achieving 100% classification accuracy. This study demonstrates the significant potential of e-nose technology towards VOCs analysis in exhaled breath, as a valuable tool for LC diagnosis. It also explores feature extraction methods and suitable algorithms for effectively distinguishing between LC patients and controls. This research provides a foundation for advancing breath-based diagnostic technologies for early detection and monitoring of liver cirrhosis. Full article

Resistive gas sensors have attracted significant attention due to their simple architecture, low cost, and ease of integration, with widespread applications in environmental monitoring, industrial safety, and healthcare diagnostics. This review provides a comprehensive overview of recent advances in resistive gas sensors, focusing on their fundamental working mechanisms, sensing material design, device architecture optimization, and intelligent system integration. These sensors primarily operate based on changes in electrical resistance induced by interactions between gas molecules and sensing materials, including physical adsorption, charge transfer, and surface redox reactions. In terms of materials, metal oxide semiconductors, conductive polymers, carbon-based nanomaterials, and their composites have demonstrated enhanced sensitivity and selectivity through strategies such as doping, surface functionalization, and heterojunction engineering, while also enabling reduced operating temperatures. Device-level innovations—such as microheater integration, self-heated nanowires, and multi-sensor arrays—have further improved response speed and energy efficiency. Moreover, the incorporation of artificial intelligence (AI) and Internet of Things (IoT) technologies has significantly advanced signal processing, pattern recognition, and long-term operational stability. Machine learning (ML) algorithms have enabled intelligent design of novel sensing materials, optimized multi-gas identification, and enhanced data reliability in complex environments. These synergistic developments are driving resistive gas sensors toward low-power, highly integrated, and multifunctional platforms, particularly in emerging applications such as wearable electronics, breath diagnostics, and smart city infrastructure. This review concludes with a perspective on future research directions, emphasizing the importance of improving material stability, interference resistance, standardized fabrication, and intelligent system integration for large-scale practical deployment. Full article

Image quality in high-resolution digital single-lens reflex (DSLR) systems is degraded by Complementary Metal-Oxide-Semiconductor (CMOS) sensor noise and optical imperfections. Sensor noise becomes pronounced under high-ISO (International Organization for Standardization) settings, while optical aberrations such as blur and chromatic fringing distort the signal. Optical and sensor-level noise are distinct and hard to separate, but prior studies suggest that improving optical fidelity can suppress or mask sensor noise. Upon this understanding, we introduce a framework that utilizes densely interpolated Point Spread Functions (PSFs) to recover high-fidelity images. The process begins by simulating Gaussian-based PSFs as pixel-wise chromatic and spatial distortions derived from real degraded images. These PSFs are then encoded into a latent space to enhance their features and used to generate refined PSFs via similarity-weighted interpolation at each target position. The interpolated PSFs are applied through Wiener filtering, followed by residual correction, to restore images with improved structural fidelity and perceptual quality. We compare our method—based on pixel-wise, physical correction, and densely interpolated PSF at pre-processing—with post-processing networks, including deformable convolutional neural networks (CNNs) that enhance image quality without modeling degradation. Evaluations on DIV2K and RealSR-V3 confirm that our strategy not only enhances structural restoration but also more effectively suppresses sensor-induced artifacts, demonstrating the benefit of explicit physical priors for perceptual fidelity. Full article

A technique has been proposed and experimentally tested for measuring the hydrogen concentration in an inert atmosphere within a closed system. This method utilizes a metal-oxide-semiconductor field-effect capacity-type (MOSFEC) sensor under harsh conditions such as exposure to inert gases, pressure fluctuations, and varying temperatures. The measurement is performed during the thermal decomposition of metal hydrides in a liquid sodium environment. The developed measurement technique for determining hydrogen concentration released from metal hydride samples in a system with a closed gas path is cost-effective compared to standardized, resource-intensive open-volume flow measurement methods. The use of the developed MOSFEC sensor technique allows for rapid and efficient investigation of the in situ real-time dynamics of gas release from various metal hydride materials differing in their hydrogen content within a small closed volume. Additionally, this approach enables precise determination of the specific gas release temperatures. Full article

Seafood, especially marine fish, is highly prone to spoilage during processing, transportation, and storage. It releases pungent trimethylamine (TMA) gas, which severely affects food quality and safety. Metal–oxide–semiconductor (MOS) gas sensors for TMA detection offer a rapid, convenient, and accurate method for assessing fish freshness. Indium oxide (In₂O₃) has shown potential as an effective sensing material for the detection of TMA. In this work, one-dimensional In₂O₃ nanowires with different grain sizes and levels of crystallinity were synthetized using the electrospinning technique and underwent different thermal calcination processes. Gas-sensing tests showed that the In₂O₃–3 °C/min–500 °C gas sensor exhibited an outstanding performance, including a high response (R_a/R_g = 47.0) to 100 ppm TMA, a short response time (6 s), a low limit of detection (LOD, 0.0392 ppm), and an excellent long-term stability. Furthermore, the sensor showed promising experimental results in monitoring the freshness of Larimichthys crocea (L. crocea). By analyzing the relationship between the grain size and crystallinity of the In₂O₃ samples, a mechanism for the enhanced gas-sensing performance was proposed. This work provides a novel strategy for designing and fabricating gas sensors for TMA detection and highlights their potential for broad applications in real-time fish freshness monitoring. Full article

This paper focuses on the analysis of a new modulation method based on the reverse conduction of metal–oxide–semiconductor field-effect transistors (MOSFETs) for a three-phase voltage-feed full-bridge converter with two-switched transistors. The implementation of the proposed method allows efficient converter performance during regenerative braking of a brushless DC machine. It does not require any additional components such as power switches, sensors, and high-performance microcontrollers. Previously known classical modulation methods were characterised by significantly lower efficiency of the converter due to diode conduction. The operating principle of the modified modulation method is clearly explained in detail with mathematical and simulation analyses presented. The theoretical results obtained were verified experimentally, demonstrating that the maximum efficiency of the converter increased from 88% (for classical modulation) to 95% with the new modulation strategy. The developed solution is dedicated to electric vehicles and enables effective regenerative braking even at low speeds. Full article

Embedded differential temperature sensors can be utilized to monitor the power consumption of circuits, taking advantage of the inherent on-chip electrothermal coupling. Potential applications range from hardware security to linearity, gain/bandwidth calibration, defect-oriented testing, and compensation for circuit aging effects. This paper introduces the use of on-chip differential temperature sensors as part of a wireless Internet of Things system. A new low-power differential temperature sensor circuit with chopped cascode transistors and switched-capacitor integration is described. This design approach leverages chopper stabilization in combination with a switched-capacitor integrator that acts as a low-pass filter such that the circuit provides offset and low-frequency noise mitigation. Simulation results of the proposed differential temperature sensor in a 65 nm complementary metal-oxide-semiconductor (CMOS) process show a sensitivity of $33.18\mathrm{V}{/}^{°}\mathrm{C}$ within a linear range of $\pm 36.5{\mathrm{m}}^{°}\mathrm{C}$ and an integrated output noise of $0.862{\mathrm{mV}}_{\mathrm{rms}}$ (from 1 to 441.7 Hz) with an overall power consumption of $0.187\mathrm{mW}$. Considering a figure of merit that involves sensitivity, linear range, noise, and power, the new temperature sensor topology demonstrates a significant improvement compared to state-of-the-art differential temperature sensors for on-chip monitoring of power dissipation. Full article

The importance and challenges of ethylene detection based on combustion-type low-cost commercial sensors for agricultural and industrial applications are well-established. This work summarizes the significant progress in ethylene detection based on an innovative Gas Metal Oxide Semiconductor (GMOS) sensor and a new catalytic composition of metallic nanoparticles. The paper presents a study on ethylene and ethanol sensing using a miniature catalytic sensor fabricated by Complementary Metal Oxide Semiconductor–Silicon-on-Insulator–Micro-Electro-Mechanical System (CMOS-SOI-MEMS) technology. The GMOS performance with bimetallic palladium–platinum (Pd-Pt) and monometallic palladium (Pd) and platinum (Pt) catalysts is compared. The synergetic effect of the Pd-Pt catalyst is observed, which is expressed in the shift of combustion reaction ignition to lower catalyst temperatures as well as increased sensitivity compared to monometallic components. The optimal catalysts and their temperature regimes for low and high ethylene concentrations are chosen, resulting in lower power consumption by the sensor. Full article

The measurement of humidity is of great significance for precision instruments, semiconductor integrated circuits, and element manufacturing factories. The oxygen-containing groups and noble metals in graphene-based sensing materials can significantly influence their humidity-sensing performance. Herein, 1,3,5-benzenetricarboxylic acid-functionalized reduced graphene oxide (H3BTC-rGO) loaded with Ag nanocluster nanocomposites (H3BTC-rGO/Ag) was synthesized via a facile one-step reduction method. The H3BTC-rGO/Ag-based sensor exhibited excellent humidity-sensing performance, including a higher sensitivity of 88.9% and a faster response/recovery time of 9 s/16 s towards 50% RH than those of other GO-, rGO-, and H3BTC-rGO-based sensors. The proposed humidity sensor was tested in the range of 0% to 100% RH and showed excellent sensitivity even at a low relative humidity of 0–10% or a high relative humidity of 90–100%. In addition, the H3BTC-rGO/Ag-based sensor had excellent selectivity, reliable repeatability, and good stability over 30 days under different relative humidities. Compared with H3BTC-rGO-200, the H3BTC-rGO/Ag-0.25-based sensor exhibited a low hysteresis of less than ±5% RH. The high performance was ascribed to the high density of the carboxyl groups and good conductivity of H3BTC-rGO, as well as the catalytic role of the Ag nanoclusters, resulting in high water adsorption rates. The potential applications of the H3BTC-rGO/Ag-based humidity sensor in human exhalation monitoring are also discussed. This work provides a reference for the application of graphene-based flexible sensors in monitoring very wet and dry environments. Full article

The refractive index is an important optical property of materials which can be used to understand the composition of materials. Therefore, refractive index sensing plays a vital role in biological diagnosis and therapy, material analysis, (bio)chemical sensing, and environmental monitoring. Conventional optical refractive index sensors based on optical fibers and ridge waveguides have relatively large sizes of a few millimeters, making them unsuitable for on-chip integration. Photonic crystals (PCs) have been used to significantly improve the compactness of refractive index sensors for on-chip integration. However, PC structures suffer from defect-introduced strong scattering, resulting in low transmittance, particularly at sharp bends. Valley photonic crystals (VPCs) can realize defect-immune unidirectional transmission of topological edge states, effectively reducing the scattering loss and increasing the transmittance. However, optical refractive index sensors based on VPC structures have not been demonstrated. This paper proposes a refractive index sensor based on a VPC Mach–Zehnder interferometer (MZI) structure with a high forward transmittance of 0.91 and a sensitivity of 1534%/RIU at the sensing wavelength of λ = 1533.97 nm within the index range from 1.0 to 2.0, which is higher than most demonstrated optical refractive index sensors in the field. The sensor has an ultracompact footprint of 9.26 μm × 7.99 μm. The design can be fabricated by complementary metal–oxide semiconductor (CMOS) fabrication technologies. Therefore, it will find broad applications in biology, material science, and medical science. Full article

We propose a complementary metal-oxide-semiconductor (CMOS) image sensor (CIS) that performs edge mask computation and detection during the analog-to-digital (A/D) conversion process to output 1-bit edge images. By utilizing the characteristics of the edge that can obtain a 1-bit image, the edge mask and thresholding operations are performed simultaneously during the A/D conversion process, thereby reducing memory capacity along with a high number of frames per second (FPS). Additionally, by implementing a 1-bit analog-to-digital converter (ADC) instead of a high-resolution ADC and counter through the 1-bit edge data obtained from the edge mask operation, both static and dynamic power consumption are reduced. The proposed CIS, fabricated with a one-poly six-metal CIS process with a 4T-active pixel sensor, has a core area of 2.546 mm $\times$ 1.923 mm in a chip area of 2.558 mm × 4.3 mm. The total power consumption is 1.52 mW at 23 FPS, with power supplies of 2.8 V and 1.5 V for the analog domain and 1.5 V for the digital domain. Full article

Electrospinning techniques have been widely applied in diverse applications, such as biocompatible membranes, energy storage systems, and triboelectric nanogenerators (TENGs), with the capability to incorporate other functional materials to achieve specific purposes. Recently, gas sensors incorporating doped semiconducting materials fabricated by electrospinning have been extensively investigated. TENGs, functioning as self-powered energy sources, have been utilized to drive gas sensors without external power supplies. Herein, a self-powered triboelectric ethanol sensor (TEES) is fabricated by integrating a TENG and an ethanol gas sensor into a single device. The proposed TEES exhibits a significantly improved response time and lower detection limit compared to published integrated triboelectric sensors. The device achieves an open-circuit voltage of 51.24 V at 800 rpm and a maximum short-circuit current of 7.94 μA at 800 rpm. Owing to the non-contact freestanding operating mode, the TEES shows no significant degradation after 240,000 operational cycles. Compared with previous studies that integrated TENGs and ethanol sensors, the proposed TEES demonstrated a marked improvement in sensing performance, with a faster response time (6 s at 1000 ppm) and a lower limit of detection (10 ppm). Furthermore, ethanol detection is enabled by modulating the gate terminal of an IRF840 metal-oxide semiconductor field-effect transistor (MOSFET), which controls the illumination of a light-emitting diode (LED). The LED is extinguished when the electrical output decreases below the setting value, allowing for the discrimination of intoxicated states. These results suggest that the TEES provides a promising platform for self-powered, high-performance ethanol sensing. Full article

This study explored the oxygen-sensing mechanism of CeO₂ modified with TiO₂ via high-energy ball milling at different speeds. Different characterization techniques were employed to investigate the obtained materials. Quantitative surface analysis by X-ray photoelectron spectroscopy was conducted to elucidate their sensitivity mechanisms and assess the impact of the introduction of TiO₂. A comparable concentration of oxygen vacancies was found in the samples milled at 350 and 450 rpm. Electrical measurements conducted at temperatures lower than required for semiconductor gas sensors revealed the higher sensitivity of these two samples in comparison to pure CeO₂ at an oxygen concentration above 10%. In contrast, the samples derived from precursors milled at the highest speed exhibited the lowest sensitivity. This may be linked to a slight decrease in the vacancy concentration and the presence of a differentially charged carbon-containing phase. Eventually, the C 1s line provided significant insight into the surface characteristics of the materials. The uniform and non-uniform charging found for pure TiO₂ and CeO₂, respectively, along with the high charging of CeO₂, suggest that TiO₂ promotes the contact between the sensing layer and the overlayer. Sensor testing showed the significantly lower resistance of mixed oxides in comparison to CeO₂, which increases the utility of metal oxide-based sensors. Full article