In this paper, we present a CMOS hybrid magnetic field sensor for real-time motor speed monitoring for smart energy-efficient autonomous systems. The sensor system consists of a micro Hall effect sensor (μHES) and a micro search coil magnetometer (μSCM) using TSMC 0.18μm 1P6M CMOS process with a die size of 1.5×2mm ² . The hybrid sensor is realized completely by the CMOS process without post-processing. A wide range of rotation speed can be measured by the presented passive μSCM without signal amplification (> 600 rpm) and the combination of the μSCM and μHES on the same chip allows the low rotation speed range measurement (<600 rpm). Furthermore, the μSCM has zero offset and very low-temperature dependency. The magnetic field of a permanent magnet on the rotating shaft of the motor is measured by the μSCM and the μHES to determine the rotation speed. The sensitivity of the μHES (at 5V bias voltage) and the μSCM inside a uniform magnetic field are 113.6 μV/mT and 11.3 μV/mT at 1 Hz without amplification, respectively. The noise equivalent magnetic induction of the μSCM was calculated and verified experimentally by utilizing a zero-drift instrumentation amplifier. Furthermore, a simplified equivalent circuit model for the μSCM is presented and verified experimentally. According to the equivalent circuit model, the linear frequency response region of the μSCM is up to 20 kHz, which suits the controlling motors in smart autonomous systems and other low-frequency applications.

This paper experimentally investigates the size-dependent effective Young's modulus $\left(E_{\mathit{eff}}\right)$ of aluminum (Al) clamped-clamped microbeams using the electrostatic pull-in instability technique. This study presents an experimental characterization of the so-called “length scale parameter” in couple stress theory and surface elasticity. $E_{\mathit{eff}}$ is retrieved from the measured pull-in voltage, of the clamped-clamped beams with different dimensions, via an electromechanically coupled equation. Measurement results show a strong size dependence of $E_{\mathit{eff}}$ for the Al beams in small sizes. The Young's modulus increases monotonously as the beams become thinner. The experimental observations are consistent with the published modeling results of the size effects, in which couple stress theory and surface elasticity theory are taken into consideration. The presented experimental method has substantial advantages such as precise adjustable magnitude of the non-contacting force and a lower cost over the other approaches used for characterization of micro-/nanoelectromechanical systems. This simple and reproducible method can be extended for characterization of various materials with different sizes and boundary conditions.

In this paper, a new analytical method to achieve the maximum signal-to-noise ratio (SNR) of a micro search coil magnetometer (µSCM) is presented. A planar spiral inductor was utilized to miniaturize conventional bulky search coil magnetometers. First, dimensional analysis was applied to identify three dimensionless parameters for the µSCM’s key performance indices (sensitivity (S_e), noise, and SNR). The effect of the parameters on the µSCM’s performance was carefully investigated, and a novel 4D nomogram was developed. Furthermore, an SNR analysis considering noise sources of a low-noise amplifier was performed. By combining the results from the nomogram and the effect of the noise sources from the amplifier circuit, optimum values for the dimensionless parameters were calculated. According to the calculation results, the dominant noise source varied with an increase in the track width ratio to the outer diameter. Seven different samples were fabricated by a single-mask lithography process. The sensitivity of 1612 mV/mT was demonstrated at a 50 Hz input magnetic field, which was better than the previous µSCM (S_e = 6.5 mV/mT) by more than 2 orders of magnitude. Finally, one of the fabricated µSCMs was employed to measure the online power consumption of a personal computer while different types of software were running.

Human thermal comfort is highly influenced by environmental parameters such as temperature, relative humidity (RH), and air velocity in addition to personal factors. The available sensors to measure these environmental parameters are stand-alone and can be very bulky and expensive, especially the air velocity sensor. Therefore, it is a challenge to measure human thermal comfort in smart buildings and most of the buildings utilize only temperature sensor to control the indoor climate. This work integrates multienvironmental sensors (temperature, humidity, and air velocity) on a single chip using low-cost CMOS-compatible MEMS technology. The multisensor chip (MSC) is successfully packaged and tested in experimental setups to characterize the temperature, humidity, and air velocity sensors integrated into it. The experimental results indicated that the air velocity sensor consumed low power (0.75 mW) while still achieving a much higher sensitivity of 123.8 mV/(m/s). Besides, the MSC’s RH sensor achieved an average sensitivity of 15.17 fF/%RH and covered the 7% to 82 % RH range, whereas the temperature sensor demonstrated a sensitivity of 25.2 mV/ $^{\circ}$ C during testing, covering a temperature range of 3 $^{\circ}$ C to 53 $^{\circ}$ C. Furthermore, the crosstalk study concluded that because of the low power operation of the air velocity sensor, a very negligible heat is transferred to the substrate. The overall chip temperature increases only by 0.1 $^{\circ}$ C due to the operation of the multisensors. This is quite low compared to the reported MSCs, where the chips’ temperature raised by 2 $^{\circ}$ C to 10 $^{\circ}$ C affecting the performance of the individual sensors located on the same chip. The results suggested that the developed MSC is promising for measuring environmental parameters in smart buildings in the Internet of Things (IoT) era.

This letter highlights a significant advancement in the miniaturization of conventional variable reluctance sensors (VRSs) using an optimized micromachined spiral coil and a cylindrical magnet. The primary objective is to create low-cost, high-performance micro-VRSs (µVRS) that can measure the position, speed, and proximity of ferrous components. The sensitivity of the µVRS was optimized through theoretical analysis, aiming to achieve a minimum noise equivalent magnetic induction (NEMI). The fabrication of the µVRS involved using a cost-effective single-mask lithography process to create a planar spiral inductor on a silicon wafer. Once the fabrication was complete, the µVRS was wire-bonded to a printed circuit board (PCB). The cylindrical magnet was then affixed to the backside of the PCB, resulting in a passive µVRS. The presented µVRS successfully measured the position and rotation speed of an iron gear around the shaft of a stepper motor with high accuracy. The high sensitivity of the µVRS enabled the generation of an output electrical signal of sufficient magnitude, which could be measured using an oscilloscope or a commercial analog-to-digital converter. The distinguishing feature of the presented µVRS is its complete passivity, as it operates without any power source, unlike semiconductor-based magnetic field sensors, such as Hall effect sensors, commonly used in position and speed sensors. The passive nature, robustness, low-temperature dependency, and small size of the presented µVRS make it particularly suitable for smart energy-efficient buildings and smart manufacturing to reduce carbon footprint in the era of AIoT.