Abstract

Structural engineering plays an essential role in designing, improving, and optimizing an electromechanical system, instinctively affecting its performance. In this study, design optimization, finite element analysis, and experimental evaluation of capacitive pressure sensors were conducted. The air pressure sensing application was demonstrated to characterize different sensors, which include a combination of multiple rectangular cantilevers and diaphragms (square and circular-shaped). After the design improvement, we found that the square and circular diaphragms each with two trapezoidal cantilevers exhibited highest sensitivity to air pressure monitoring among the different investigated designs which combine the square and circular diaphragms with cantilevers. These designs were then selected for further analysis for acoustic pressure monitoring. The sensors were fabricated using the doit-yourself technique with household materials such as post-it paper, posted tape, and foil. Our approach offers an alternative to the conventional cleanroom fabrication technique and uses easily available materials to fabricate affordable sensors. Therefore, this is the first step toward the development of democratized and sustainable electronic devices that are affordable and available to everyone on the internet. Index Terms—Capacitive sensing, air pressure sensing, acoustic pressure sensing, paper electronics, democratized electronics, affordable electronics, structural engineering.

Abstract

Viscosity measurement has wide ranging applications from oil industry to pharmaceutical industry. However, measuring viscosity in real-time is not a facile process. This paper provides an elaborate mathematical model and study of viscosity measurement in real-time using pressure sensors. For a given flowrate, a change in liquid viscosity gives rise to a change in pressure difference across a particular section of the pipe. Hence, by recording the pressure change, viscosity can be calculated dynamically. A mathematical model as well as a finite element analysis model has been presented to determine viscosity from flowrate and pressure difference. A set of pressure sensors can be placed at a fixed distance from each other to get the real- time pressure change, while flowrate can be obtained using a flowmeter. For the finite element analysis, the pressure sensors were placed 60 mm away from each other. The radius of the pipe was 19 mm. A mixture of water and glycerol, with different ratios, was used to provide variable viscosity. Index Terms—Viscosity, Flowrate, Microfluidic channel, Pressure sensor, Real-time measurement

Abstract

In recent years, semi-transparent building-integrated photovoltaics (BIPV) technology has attracted attention for its renewable energy utilization. This research aims to develop a methodology for assessing the energy-saving potential of semi-transparent photovoltaic (STPV) window, which has a complex relationship with daylighting and air conditioning (AC) electricity consumption. A case study has been developed for the composite climate of Hyderabad, India. The study examines four commercially available single and double pane STPV windows and similar non-photovoltaic windows. For evaluation, an automated parametric simulation tool was developed to compute the net electricity consumption (NEC) for a representative model building with different window systems, and several window-to-wall ratios (WWR) and orientations. The result shows benefit in adopting the STPV window system across all directions …

Abstract

The technological advancements in healthcare mon- itoring devices, automation, consumer electronics, and soft robotics have resulted in extensive research in flexible pressure, force, and tactile sensors. Piezoresistive sensors are the most widely used flexible pressure sensors due to their low-cost fabrication, high flexibility and simple data-acquisition circuits. In this paper, we report the bending response of a velostat- based flexible pressure sensor by examining its reliability when subjected to repeated mechanical stress. The observed deviation in output voltage was 0.95% for 15 mm, 0.95% for 20 mm, 0.97% for 25 mm, and 2.2% for 30 mm bending radii, for 150 bending cycles, with respect to the flat position. We present a two-parameter (a, b) calibration for the pressure sensor with a fixed bias resistance in the readout circuit. This model can be used to further minimize the deviation due to bending cycles. The results obtained from the experimental research have shown a practical possibility of implementing velostat-based sensors for both static and dynamic flexible systems. Index Terms—Reliability; piezoresistive; pressure sensor; me- chanical stress; velostat

Abstract

Microelectromechanical systems (MEMS) are small-scale devices capable of producing motion using electrical energy as input. In this work, we present the determination of thermal and mechanical properties of SU-8, which is an emerging structural material for MEMS applications. We have experimentally calculated the coefficient of thermal expansion (CTE), thermal conductivity, and specific heat capacity of SU-8 as 29.68 ppm °C−1, 0.17 , and 1.6 , respectively. We observe a non-linear relationship between the input power with the displacement achieved by an SU-8-based thermal actuator because of the hyperelastic behavior of the material. The non-linearity in the experimental results has been explained using the two-parameter Mooney–Rivlin model. With our experimental data, we found the parameters for the uniaxial tensile stress, as Pa and Pa

Abstract

In recent years, the popularity of weight training has increased significantly. However, incorrect technique or physical form while performing an exercise can not only slow down progress but also cause serious injuries. Deadlift is a famous weight training exercise, which if done incorrectly, can lead to chronic back pain. In this paper, we present a wearable pressure sensor system that checks the posture of the user while performing deadlift. The suit employs a set of flexible pressure sensors, made using velostat (piezoresistive) material, to get the amount of bending for specific muscles. We have developed an algorithm to process the data in real-time so that feedback about incorrect posture can be provided to the user immediately. The algorithm has been configured using data from a single subject, however, it provides accurate classification for multiple subjects in the same weight class, thus eliminating the need for subject-wise configuration. The algorithm classifies a repetition (rep) of the exercise into a good rep or bad rep with an overall accuracy of 95.5%, across three subjects. With some enhancements, the system can also be configured to classify reps of other exercises.

Abstract

The paper presents a low-cost method (no extra LDO, Op-amp) to increase the PSRR of composite pair based temperature sensor. Composite pair is a commonly used circuit to generate a linear PTAT voltage for a wide temperature range. A 180° phase shift, voltage biasing technique is introduced at the gate of the NMOS transistor to obtain a supply independent bias current in composite pair. The proposed technique thus achieves a high supply noise rejection. The circuit as a whole does not require additional circuitry, therefore it saves power and area. A 6μW Temperature sensor with 1mV/°c slope is designed in TSMC 180nm technology and achieves PSRR of -80dB. Post-layout simulation results show that the temperature sensor achieves inaccuracy of ±0.1°C from −55°C to 125°C, PSRR of −80dB at 105Hz and -70dB at 200kHz at 1V power supply, and the line regulation of 0.016%/V in a supply voltage range of 1V to 2.5V. Monte-Carlo simulation result for the output PSRR shows −80.56dB as the mean-value with a maximum deviation of ±1.5dB.

Abstract

The paper presents a sub-nW gate-leakage based voltage and current reference in a single circuit whose reference values are scalable and doesn’t incorporate start-up circuits or resistors in the architecture. The power consumption of the proposed circuit increases by only 2.1x in the temperature range of -55°C to 100°C, unlike conventional voltage/current references where the power consumption increases exponentially w.r.t temperature. Implemented in 90nm technology, the proposed voltage reference (current reference) achieves post-trim typical accuracy of 22ppm/°C(58ppm/°C) and worst-case accuracy of 71ppm/°C(78ppm/°C). Excellent line sensitivities of 0.029%/V and 0.059%/V are observed for voltage and current reference respectively, in a supply range of 1V - 3V. Without any start-up circuit, the observed 99% settling times for voltage and current reference are 1.92ms and 2.526ms respectively. The area occupied by the total circuit is 0.0015mm 2 , while the power consumption is 156pW at typical corner, 27°C and 1V supply.

Abstract

This brief proposes an ultra-low-power current ref- erence in TSMC 180nm technology. Temperature compensation is achieved by taking the ratio of compensated voltage and an on-chip resistance. This design uses the concept of the back- gate effect of critical MOSFET to generate complementary to absolute temperature (CTAT) voltage. The circuit works from a supply voltage of 0.55V and is designed for a reference current of 5.6nA. Furthermore, a pseudo-differential amplifier (PD-AMP) helps realize low line regulation of 0.022%/V in the supply range of 0.55 to 1.9V. An average temperature coefficient (TC) of 256.07ppm/◦C is achieved for mismatch and process variations in Monte-Carlo simulations for 1000 samples over a tempera- ture range of −30◦C to 70◦C. The circuit consumes only 9.5nW of power (at room temperature and minimum supply voltage), making it suitable for ultra-low-power biomedical applications. Index Terms—Peaking current reference, biomedical, sub- threshold region, DIBL, PD-AMP.

Abstract

The present description relates to a method based on artifi cial intelligence to implement a wide range of microelec tronic circuits that can adapt by themselves to the usage conditions ( e.g. loading changes ) , manufacturing variances or defects ( e.g. process variations , device parameter mis matches , device model inaccuracies or changes , etc. ) , as well as environmental conditions ( e.g. voltage , temperature , interference ) in order to negate all or part of their effects on the circuit performance characteristics and achieve a very tight set of specifications over the wide range of conditions . Each microelectronic circuit is represented by a neural network model whose behavior is a function of the actual input signals , the usage and environmental conditions . An attached AI engine will infer from the model , the input signals , the usage conditions and the environmental condi tions and create the adaptive changes required to modify the microelectronic circuit's behavior to negate all or part of their effects on the circuit performance characteristics and to achieve a very tight set of specifications .