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The human body's temperature is one of the most important vital markers due to its ability to detect various diseases early. Accurate measurement of this parameter has received considerable interest in the healthcare sector. We present a novel study on the optimization of a temperature sensor based on silver interdigitated electrodes (IDEs) and carbon-sensing film. The sensor was developed on a flexible Kapton thin film first by inkjet printing the silver IDEs, followed by screen printing a sensing film made of carbon black. The IDE finger spacing and width of the carbon film were both optimized, which considerably improved the sensor's sensitivity throughout a wide temperature range that fully covers the temperature of human skin. The optimized sensor demonstrated an acceptable temperature coefficient of resistance (TCR) of 3.93 × 10−3 °C−1 for temperature sensing between 25 °C and 50 °C. The proposed sensor was tested on the human body to measure the temperature of various body parts, such as the forehead, neck, and palm. The sensor showed a consistent and reproducible temperature reading with a quick response and recovery time, exhibiting adequate capability to sense skin temperatures. This wearable sensor has the potential to be employed in a variety of applications, such as soft robotics, epidermal electronics, and soft human–machine interfaces. [ABSTRACT FROM AUTHOR]

The rapid growth in wearable biosensing devices is driven by the strong desire to monitor the human health data and to predict the symptoms of chronic diseases at an early stage. Different sensors are developed for continuous monitoring of various biomarkers through wearable and implantable sensing patches. Temperature sensor has proved to be an important physiological parameter amongst the various wearable biosensing patches. This paper highlights the recent progresses made in printing of functional nanomaterials for developing wearable temperature sensors on polymeric substrates. A special focus is given to the advanced functional nanomaterials as well as their deposition through printing technologies. The geometric resolutions, shape, physical and electrical characteristics as well as sensing properties using different materials are compared and summarized. Wearability is the main concern of these newly developed sensors, which is summarized by discussing representative examples. Finally, the challenges concerning the stability, repeatability, reliability, sensitivity, linearity, ageing, and large-scale manufacturing are discussed with future outlook of the wearable systems. [ABSTRACT FROM AUTHOR]

In this article, we report a wafer-level packaged Pirani vacuum gauge using the proprietary InvenSense CMOS MEMS technology. The micro Pirani vacuum gauge features three serpentine-shaped molybdenum thermistors on the suspended silicon-on-insulator (SOI) bridges, while the wiring gap of each serpentine-shaped silicon microbridge is 1.6 ${ {\mu }}\text{m}$. For the vacuum range of $5\times 10^{-{4}}$ –760 Torr, the CMOS MEMS Pirani gauge configured with a constant temperature interface circuit achieves a sensitivity of 0.414 V/Torr in a very fine vacuum regime, while its heating power is less than 21.3 mW. Moreover, the measured output of the micro Pirani gauge shows good agreement with a semi-empirical model, while the model predicts that the proposed Pirani gauge can measure a vacuum pressure as low as $2.6\times 10^{-{4}}$ Torr. The performance achieved by this Pirani vacuum gauge combined with its high level of integration makes it a promising Internet of Things (IoT) sensing node for vacuum monitoring in the industry. [ABSTRACT FROM AUTHOR]

Hydrogen sulfide (H2S) presents many hazardous traits such as corrosive, explosive, toxic, and flammable. It is slightly denser than air, and a mixture of H2S and air can be volatile. Therefore, a reliable and robust measurement system is required to effectively detect and quantify H2S in many applications, such as oil and gas industries. There are several methods available in the literature to quantify H2S in fuel gases; however, only a few are available in case of air samples. Furthermore, array-based sensors are more reliable in the detection of volatile organic compounds (VOCs); however, sensor arrays are more expensive and challenging to produce. To overcome the limitations of producing physical sensor arrays, this article proposes a concept of virtual sensing that enables to augment a single sensing platform into a virtual array, thus, increasing the detection accuracy at no extra cost of producing a large physical sensors array. The merits of the proposed system are as follows: 1) a virtual sensing concept is combined with a physical sensing platform to enhance the proposed model’s estimation power in quantifying H2S in air samples; 2) a new feature extraction method based on fractional derivatives is proposed to further enhance the model’s learning capabilities; 3) an array of four gas sensors is fabricated in the in-house foundry to record and analyze the signature of H2S at various concentration levels; 4) a shallow neural network (NN) model is trained and tested on the recorded data, and based on the NN’s input–output relation, a mathematical model is presented for the quantification of H2S; and 5) the proposed model is a highly sensitive and reliable H2S gas sensing scheme with the ability to detect the gas instantaneously. The proposed gas quantification model has the advantages of being low cost, easy to implement, and fast operation compared with the analytical solutions. Furthermore, it is extensively tested and validated using real gas data. [ABSTRACT FROM AUTHOR]

Both bacterial viability and concentration are significant metrics for bacterial detection. Existing miniaturized and cost-effective single-mode sensor, pH or optical, can only be skilled at detecting single information viability or concentration. This paper presents an inverter-based CMOS ion-sensitive-field-effect-transistor (ISFET) sensor array, featuring bacterial pH detection which is an indicator of viability. The proposed design realizes pH detection using the native passivation layer of CMOS process as a sensing layer and configuring an inverter-based front-end as a capacitive feedback amplifier. This sensor array is assisted by temperature sensing and optical detection which reveals bacterial concentration. The optical detection is enabled using the leakage current of a reset switch as a response to a light source. While in reset mode, the inverter-based amplifier works as a temperature sensor that could help to reduce temperature influences on pH and optical detection. All the functionalities are realized using one single inverter-based amplifier, resulting in a compact pixel structure and largely relaxed design complexity for the sensor system. Fabricated in 0.18 μm standard CMOS process, the proposed CMOS sensor array system achieves an amplified pH sensitivity of 221 mV/pH, an improved sensor resolution of 0.03 pH through systematic noise optimization, a linear optical response, and a maximum temperature error of 0.69° C. The sensing capabilities of the proposed design are demonstrated through on-chip Escherichia coli (E. coli) detection. This study may be extended to a rapid and cost-effective platform that renders multiple information of bacterial samples. [ABSTRACT FROM AUTHOR]

This paper presents an ultra-high-frequency (UHF) passive sense tag for electrical grid and substation thermal monitoring, with emphasis on the tag system optimization and the design of a low power embedded temperature sensor. The designed tag achieves a sensitivity of $-$ 12.3 dBm under active temperature monitoring operation, which is the state of the art among existing UHF passive temperature sense tag products. The sensing inaccuracy of the tag is $\pm$ 2.5 $^{\circ }$ C (3 $\sigma$) from $-$ 25 to 120 $^{\circ }$ C after a low-cost wireless single-point trim. An antimetal ceramic-packaged tag was tested by attaching to a ring main unit in the substation and complete tag system demonstrated robust wireless operation with a sensing distance of 3.5 m. The combination of batteryless and wireless operation, high sensitivity, wide sensing range, and small incident-power-dependent error ($\pm$ 0.2 $^{\circ }$ C) makes this tag suitable for the target applications. [ABSTRACT FROM AUTHOR]

Leveraging More-than-Moore technology, we demonstrate an integrated CMOS MEMS flow sensor via a very compact system on chip (SoC) that can sense the bidirectional N2 gas flow. Our SoC features a very low-noise instrumentation amplifier that is implemented on a CMOS wafer and serves as a readout integrated circuit for a thermoresistive micro-calorimetric flow sensor which is fabricated on a MEMS wafer. A compact heterogeneous integration is achieved by combining the two wafers via the proprietary InvenSense AlN process. The measured sensitivity of our CMOS MEMS flow sensor is 98 mV/sccm which is three times better than the state-of-the-art counterpart. The flow range measured by our SoC is from −26 to 26 m/s (from −50 to 50 sccm). Moreover, the pulsed heater operation makes this proposed SoC flow sensor a very low power (<9 mW) and, thus, a promising candidate for the Internet-of-Things applications in smart home/green buildings. [ABSTRACT FROM AUTHOR]

This brief presents a 0.9- $\mu \text{W}$ duty-cycle-modulated temperature sensor with a sub- $\mu \text{A}$ peak current for energy harvester- or micro-battery-powered systems. A compact sensing frontend is proposed to achieve low power, together with various device-level leakage and nonlinearity compensation techniques adopted to minimize the sensor error. In addition, a current-starved multivibrator which provides inherent clamping voltages is used for duty cycle modulation for overall energy savings. The sensor designed in 0.18- $\mu \text{m}$ CMOS process achieves a resolution figure of merit of 10.6 pJ $\cdot \text{K}^{2}$ , which is among the most energy-efficient designs to date. Trimmed at 30 °C, the sensor achieves ±0.85 °C precision from −30 °C to 120 °C. The maximum supply sensitivity is 0.7 °C/V for a 1.6–2 V supply. [ABSTRACT FROM AUTHOR]

This paper presents the development of a wireless low power reconfigurable self-calibrated multi-sensing platform for gas sensing applications. The proposed electronic nose (EN) system monitors gas temperatures, concentrations, and mixtures wirelessly using the radio-frequency identification (RFID) technology. The EN takes the form of a set of gas and temperature sensors and multiple pattern recognition algorithms implemented on the Zynq system on chip (SoC) platform. The gas and temperature sensors are integrated on a semi-passive RFID tag to reduce the consumed power. Various gas sensors are tested, including an in-house fabricated $4\times 4$ SnO2based sensor and seven commercial Figaro sensors. The data is transmitted to the Zynq based processing unit using a RFID reader, where it is processed using multiple pattern recognition algorithms for dimensionality reduction and classification. Multiple algorithms are explored for optimum performance, including principal component analysis (PCA) and linear discriminant analysis (LDA) for dimensionality reduction while decision tree (DT) and k-nearest neighbors (KNN) are assessed for classification purpose. Different gases are targeted at diverse concentration, including carbon monoxide (CO), ethanol (C2H6O), carbon dioxide (CO2), propane (C3H8), ammonia (NH3), and hydrogen (H2). An accuracy of 100% is achieved in many cases with an overall accuracy above 90% in most scenarios. Finally, the hardware/software heterogeneous solution to implementation PCA, LDA, DT, and KNN on the Zynq SoC shows promising results in terms of resources usage, power consumption, and processing time. [ABSTRACT FROM PUBLISHER]

Gas sensors based on semiconductor–metal–oxide nanomaterial have recently emerged due to their advantages of offering large surface to volume ratio. Unfortunately, these sensors are vulnerable to environmental humidity and lack of selectivity when exposed to common gases in air. In this letter, a novel morphology of ZnO nanomaterial is proposed for fabricating NO2 gas sensor through our customized vapor trapping chemical vapor deposition process. By operating the fabricated gas sensors at the room temperature, high sensing performance, including a large output response of 11.06 and a short response/recovery time of 107/124 s, is achieved for 20-ppm NO2. Moreover, the sensor response remains stable under humid environment up to 76%RH. In addition, the extensive experimental results indicate that our fabricated NO2 gas sensors exhibit high selectivities of 61.7, 42.8, and 54.4 dB for different target gases of H2, CH2O, and C6H6, respectively. These features will enable the mass fabrication of miniaturized, cost-effective, and highly robust gas sensor suitable for real-life application. [ABSTRACT FROM PUBLISHER]

This paper presents a system-on-chip passive RFID tag with an embedded temperature sensor for the EPC Gen-2 protocol in the 900-MHz UHF frequency band. A dual-path clock generator is proposed to support both applications with either very accurate link frequency or very low power consumption. On-chip temperature sensing is accomplished with a time-readout scheme to reduce the power consumption. Moreover, a gain-compensation technique is proposed to reduce the temperature sensing error due to process variations by using the same bandgap reference of the tag to generate bias currents for both the current-to-digital converter and the clock generator of the sensor. Also integrated is a 128-bit one-time-programmable (OTP) memory array based on gate-oxide antifuse without extra mask steps. Fabricated in a standard 0.18-\mum CMOS process with analog options, the 1.1-mm^2 tag chip is bonded onto an antenna using flip-chip technology to realize a complete tag inlay, which is successfully demonstrated and evaluated in real-time wireless communications with commercial RFID readers. The tag inlay achieves a sensitivity of -\6 dBm and a sensing inaccuracy of \pm\0.8^\circC (3 \sigma inaccuracy) over operating temperature range from -\20^\circC to 30^\circC with one-point calibration. [ABSTRACT FROM PUBLISHER]