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This is the fourth part of a study presenting a miniature, combustion-type gas sensor (dubbed GMOS) based on a novel thermal sensor (dubbed TMOS). The TMOS is a micromachined CMOS-SOI transistor, which acts as the sensing element and is integrated with a catalytic reaction plate, where ignition of the gas takes place. The GMOS measures the temperature change due to a combustion exothermic reaction. The controlling parameters of the sensor are the ignition temperature applied to the catalytic layer and the increased temperature of the hotplate due to the released power of the combustion reaction. The solid-state device applies electrical parameters, which are related to the thermal parameters. The heating is applied by Joule heating with a resistor underneath the catalytic layer while the signal is monitored by the change in voltage of the TMOS sensor. Voltage, like temperature, is an intensive parameter, and one always measures changes in such parameters relative to a reference point. The reference point for both parameters (temperature and voltage) is the blind sensor, without any catalytic layer and hence where no reaction takes place. The present paper focuses on the study of the effect of humidity upon performance. In real life, the sensors are exposed to environmental parameters, where humidity plays a significant role. Humidity is high in storage rooms of fruits and vegetables, in refrigerators, in silos, in fields as well as in homes and cars. This study is significant and innovative since it extends our understanding of the performance of the GMOS, as well as pellistor sensors in general, in the presence of humidity. The three main challenges in simulating the performance are (i) how to define the operating temperature based on the input parameters of the heater voltage in the presence of humidity; (ii) how to measure the dynamics of the temperature increase during cyclic operation at a given duty cycle; and (iii) how to model the correlation between the operating temperature and the sensing response in the presence of humidity. Due to the complexity of the 3D analysis of packaged GMOS, and the many aspects of humidity simultanoesuly affecting performane, advanced simulation software is applied, incorporating computational fluid dynamics (CFD). The simulation and experimental data of this study show that the GMOS sensor can operate in the presence of high humidity.

A stochastic model for characterizing the conversion gain of Active Pixel Complementary metal-oxide-semiconductor (CMOS) image sensors (APS), assuming stationary conditions was recently presented in this journal. In this study, we extend the stochastic approach to non-stationary conditions. Non-stationary conditions occur in gated imaging applications. This new stochastic model, which is based on fundamental physical considerations, enlightens us with new insights into gated CMOS imaging, regardless of the sensor. The Signal-to-Noise Ratio (SNR) is simulated, allowing optimized performance. The conversion gain should be determined under stationary conditions.

This study presents an original approach on how to generate a radiator with an emissivity less than one by using a conventional blackbody and a screen with a defined area density of holes. This is needed for the calibration of infrared (IR) radiometry, which is a very useful form of temperature measurement in industrial, scientific, and medical applications. One of the major sources of errors in IR radiometry is the emissivity of the surface being measured. Emissivity is a physically well-defined parameter, but in real experiments, it may be influenced by many factors: surface texture, spectral properties, oxidation, and aging of surfaces. While commercial blackbodies are prevalent, the much-needed grey bodies with a known emissivity are unavailable. This work describes a methodology for how to calibrate radiometers in the lab or in the factory or FAB using the "screen approach" and a novel thermal sensor dubbed Digital TMOS. The fundamental physics required to appreciate the reported methodology is reviewed. The linearity in emissivity of the Digital TMOS is demonstrated. The study describes in detail how to obtain the perforated screen as well as how to do the calibration.

The need to achieve digital gas sensing technology, namely, a technology to sense and transmit gas-enabled digital media, has been recognized as highly challenging. This challenge has motivated the authors to focus on complementary metal oxide semiconductor silicon on insulator micro electro-mechanical system (CMOS-SOI-MEMS) technologies, and the result is a new pellistor-like sensor, dubbed GMOS, with integrated signal processing. In this study, we describe the performance of such sensors for the selective detection of mixtures of gases. The novel key ideas of this study are: (i) the use of the GMOS for gas sensing; (ii) applying the Kalman filter to improve the signal-to-noise ratio; (iii) adding artificial intelligence (AI) with tiny edge approach.

This is the third part of the paper presenting a miniature, combustion-type gas sensor (dubbed GMOS) based on a novel thermal sensor (dubbed TMOS). The TMOS is a micromachined CMOS-SOI transistor, which acts as the sensing element and is integrated with a catalytic reaction plate, where ignition of the gas takes place. The first part was focused on the chemical and technological aspects of the sensor. In Part 2, the emphasis was on the physical aspects of the reaction micro-hot plate on which the catalytic layer is deposited. The present study focuses on applying several advanced simulation tools, which extend our understanding of the GMOS performance, as well as pellistor sensors in general. The three main challenges in simulating the performance are: (i) how to define the operating temperature based on the input parameters; (ii) how to measure the dynamics of the temperature increase during cyclic operation at a given duty cycle; (iii) how to model the correlation between the operating temperature and the sensing response. The simulated and analytical models and measured results are shown to be in good agreement.

A stochastic model for characterizing the conversion gain of Active Pixel Complementary metal-oxide-semiconductor (CMOS) image sensors (APS) with at least four transistors is presented. This model, based on the fundamental principles of electronic noise, may provide a reliable calibration of the gain conversion, which is one of the most important parameters of CMOS Image Sensor pixels. The new model revisits the "gold standard" ratio method of the measured variance of the shot noise to the mean value. The model assumes that shot noise is the dominant noise source of the pixel. The microscopic random time-dependent voltage of any shot noise electron charging the junction capacitance C of the sensing node may have either an exponential form or a step form. In the former case, a factor of 1/2 appears in the variance to the mean value, namely, q/2C is obtained. In the latter case, the well-established ratio q/C remains, where q is the electron charge. This correction factor affects the parameters that are based on the conversion gain, such as quantum efficiency and noise. The model has been successfully tested for advanced image sensors with six transistors fabricated in a commercial FAB, applying a CMOS 180 nm technology node with four metals. The stochastic modeling is corroborated by measurements of the quantum efficiency and simulations with advanced software (Lumerical).

A novel uncooled thermal sensor based on a suspended transistor, fabricated in standard CMOS-SOI process, and released by dry etching, dubbed Digital TMOS, has been developed. Using the transistor as the sensing element has advantages in terms of internal gain, low power, low-cost technology, and high temperature sensitivity. A two channel radiometer, based on the new nano-metric CMOS-SOI-NEMS Technology, enables remote temperature sensing as well as emissivity sensing of the forehead and body temperatures of people, with high accuracy and high resolution. Body temperature is an indicator of human physiological activity and health, especially in pediatrics, surgery, and general emergency departments. This was already recognized in past pandemics such as SARS, EBOLA, and Chicken Flu. Nowadays, with the spread of COVID-19, forehead temperature measurements are used widely to screen people for the illness. Measuring the temperature of the forehead using remote sensing is safe and convenient and there are a large number of available commercial instruments, but studies show that the measurements are not accurate. The surface emissivity of an object has the most significant effect on the measured temperature by IR remote sensing. This work describes the achievements towards high-performance, low-cost, low power, mobile radiometry, to rapidly screen for fever to identify victims of the coronavirus (COVID-19). The main two aspects of the innovation of this study are the use of the new thermal sensor for measurements and the extensive modeling of this sensor.

There is an ongoing effort to fabricate miniature, low-cost, and sensitive thermal sensors for domestic and industrial uses. This paper presents a miniature thermal sensor (dubbed TMOS) that is fabricated in advanced CMOS FABs, where the micromachined CMOS-SOI transistor, implemented with a 130-nm technology node, acts as a sensing element. This study puts emphasis on the study of electromagnetic absorption via the vacuum-packaged TMOS and how to optimize it. The regular CMOS transistor is transformed to a high-performance sensor by the micro- or nano-machining process that releases it from the silicon substrate by wafer-level processing and vacuum packaging. Since the TMOS is processed in a CMOS-SOI FAB and is comprised of multiple thin layers that follow strict FAB design rules, the absorbed electromagnetic radiation cannot be modeled accurately and a simulation tool is required. This paper presents modeling and simulations based on the LUMERICAL software package of the vacuum-packaged TMOS. A very high absorption coefficient may be achieved by understanding the physics, as well as the role of each layer.

This is a second part of the paper presenting a miniature, combustion-type gas sensor (dubbed GMOS) based on a novel thermal sensor (dubbed TMOS). The TMOS is a micromachined CMOS-SOI transistor, which acts as the sensing element and is integrated with a catalytic reaction plate, where ignition of the gas takes place. Part 1 focused on the chemical and technological aspects of the sensor. In part 2, the emphasis is on the physical aspects of the reaction micro-hot plate on which the catalytic layer is deposited. The three main challenges in designing the hot plate are addressed: (i) How to design a hot plate operating in air, with a low thermal conductivity; (ii) how to measure the temperature of the hot plate during operation; (iii) how to reduce the total consumed power during operation. Reported simulated as well as analytical models and measured results are in good agreement., Competing Interests: The authors declare no conflict of interest.

There is an ongoing effort to fabricate miniature, low cost, sensitive, and selective gas sensors for domestic and industrial uses. This paper presents a miniature combustion-type gas sensor (GMOS) based on a thermal sensor, where a micromachined CMOS-SOI transistor integrated with a catalytic reaction plate acts as a sensing element. This study emphasizes GMOS performance modeling, technological aspects, and sensing-selectivity issues. Two deposition techniques of a Pt catalytic layer suitable for wafer-level processing were compared, magnetron sputtering and nanoparticle inkjet printing. Both techniques have been useful for the fabrication of GMOS sensor, with good sensitivity to ethanol and acetone in the air. However, a printed Pt nanoparticle catalyst provides almost twice as much sensitivity as compared to that of the sputtered catalyst. Moreover, sensing selectivity in the ethanol/acetone gas mixture was demonstrated for the GMOS with a Pt nanoparticle catalyst. These advantages of GMOS allow for the fabrication of a low-cost gas sensor that requires a low power, and make it a promising technology for future smartphones, wearables, and Internet of Things (IoT) applications., Competing Interests: The authors declare no conflict of interest.

This paper investigates the concepts, performance and limitations of temperature sensing circuits realized in complementary metal-oxide-semiconductor (CMOS) silicon on insulator (SOI) technology. It is shown that the MOSFET threshold voltage ( V t ) can be used to accurately measure the chip local temperature by using a V t extractor circuit. Furthermore, the circuit's performance is compared to standard circuits used to generate an accurate output current or voltage proportional to the absolute temperature, i.e., proportional-to-absolute temperature (PTAT), in terms of linearity, sensitivity, power consumption, speed, accuracy and calibration needs. It is shown that the V t extractor circuit is a better solution to determine the temperature of low power, analog and mixed-signal designs due to its accuracy, low power consumption and no need for calibration. The circuit has been designed using 1 µm partially depleted (PD) CMOS-SOI technology, and demonstrates a measurement inaccuracy of ±1.5 K across 300 K⁻500 K temperature range while consuming only 30 µW during operation.

This paper reviews and compares the thermal and noise characterization of CMOS (complementary metal-oxide-semiconductor) SOI (Silicon on insulator) transistors and lateral diodes used as temperature and thermal sensors. DC analysis of the measured sensors and the experimental results in a broad (300 K up to 550 K) temperature range are presented. It is shown that both sensors require small chip area, have low power consumption, and exhibit linearity and high sensitivity over the entire temperature range. However, the diode's sensitivity to temperature variations in CMOS-SOI technology is highly dependent on the diode's perimeter; hence, a careful calibration for each fabrication process is needed. In contrast, the short thermal time constant of the electrons in the transistor's channel enables measuring the instantaneous heating of the channel and to determine the local true temperature of the transistor. This allows accurate "on-line" temperature sensing while no additional calibration is needed. In addition, the noise measurements indicate that the diode's small area and perimeter causes a high 1/ f noise in all measured bias currents. This is a severe drawback for the sensor accuracy when using the sensor as a thermal sensor; hence, CMOS-SOI transistors are a better choice for temperature sensing., Competing Interests: The authors declare no conflict of interest.