This study introduces an experimental method for determining the parasitic reactive components that appear in a thermoelectric module (TEM). In most cases, a TEM is referred to by taking into account only the constant values of the internal electrical resistance, Seebeck coefficient and thermal conductivity. The current research is focused on determining the parasitic reactive elements, inductance and capacitance that appear in a TEM. These values are linked to the semiconductor geometry and manufacturing process. The experimental results will be used afterwards to build an accurate thermoelectric device model suitable for designing and simulating TEM-based applications.

A technique for implementing monolithic resistors with a desired temperature coefficient (TC) over a wide temperature range is introduced. A typical monolithic resistor consists of a core resistive layer terminated with contact layers on each end. In a typical process, there are core resistive layers that have TCs with opposite sign of that of the contacts. The authors propose to take advantage of this property and distribute a certain number of contacts across the core resistor to achieve a desired overall TC for monolithic resistors. This TC can be negative, zero or positive. The methodologies for designing such resistors are presented. As a proof-of-concept, several resistor structures have been designed and implemented in a 0.13 μm complementary metal-oxide semiconductor technology. The simulation and measurement results over the temperature range of 25–200°C confirm the validity of the proposed technique.

This study introduces a digitally controlled biquadratic filter operating in fully differential mode and realising voltage and transadmittance functions simultaneously. The proposed circuit is based on the active element namely, digitally current controlled differential voltage current conveyor and three passive components. The proposed circuit offers wide range and non-interactive digital control over filter parameters and also exhibits wide dynamic range. The fully differential nature is well justified by the high common mode rejection ratio of the proposed circuit. Non-ideal and parasitic analyses are performed and extensive simulations carried out to verify the proposed circuit.

A monolithic low-voltage H-bridge brushless DC (BLDC) vibration motor driver with an integrated high sensitivity Hall sensor has been presented in 0.18 μm high-voltage complementary metal-oxide semiconductor technology. To improve the motor start-up reliability, a full-on start mode is applied to realise a high-speed start sequence by shortening the start-up time. Meanwhile, an active start function is activated to prevent dead point phenomenon if the motor magnet pole sensed by the built-in Hall sensor does not change during the motor starting. This complete one-chip solution for driving the BLDC vibration motors provides significantly enhanced reliabilities, including thermal shutdown and under voltage lockout protection functions, and fully eliminates the need for any external components. The measured results show that the motor driver chip has a typical operating point of 2 mT and a typical releasing point of − 2 mT, showing a hysteresis magnetic property of 4 mT. The chip is very robust. It can operate well within a low supply voltage range of 2–4 V and can output a maximum of 300 mA peak current while the ambient temperature ranges from − 40 to 85°C.

On-chip thermal sensors are employed by dynamic thermal management (DTM) techniques to appropriately manage chip performance. However, the effectiveness of the DTM mechanisms is directly dependent on the number of placed sensors, which should be minimised, while guaranteeing accurate tracking of hot spots and full thermal characterisation. In this study, the authors propose a rigid sensor allocation and placement technique for determining the fewest number of thermal sensors and the optimal locations based on dual clustering. Initially, the authors utilise the dual clustering algorithm to devise method that can reduce the number of sensors to a great extent while satisfying an expected accuracy of hot spot temperature error. Then they identify an optimal physical location for each sensor such that the accuracy of full thermal characterisation is maximised. They also propose a flexible sensor computation technique which combines the measurements of the rigid sensors in an optimal way to precisely estimate the temperatures where no sensors are embedded, which can further improve the hot spots tracking resolution. Experimental results indicate the superiority of the authors techniques and confirm that their proposed methods are capable of accurately characterising the temperatures of microprocessors.