This work reports the development of arrays of infrared sensors (microbolometers) using a hydrogenated polymorphous silicon–germanium alloy (pm-Si_xGe_1-x:H). Basically, polymorphous semiconductors consist of an amorphous semiconductor matrix with embedded nanocrystals of about 2–3 nm. The pm-Si_xGe_1-x:H alloy studied has a high temperature coefficient of resistance (TCR) of 4.08%/K and conductivity of 1.5 × 10⁻⁵ S∙cm⁻¹. Deposition of thermosensing film was made by plasma-enhanced chemical vapor deposition (PECVD) at 200 °C, while the area of the devices is 50 × 50 μm² with a fill factor of 81%. Finally, an array of 19 × 20 microbolometers was packaged for electrical characterization. Voltage responsivity values were obtained in the range of 4 × 10⁴ V/W and detectivity around 2 × 10⁷ cm∙Hz^1/2/W with a polarization current of 70 μA at a chopper frequency of 30 Hz. A minimum value of 2 × 10⁻¹⁰ W/Hz^1/2 noise equivalent power was obtained at room temperature. In addition, it was found that all the tested devices responded to incident infrared radiation, proving that the structure and mechanical stability are excellent.

This research presents the design and implementation of an Internet of Things (IoT)-based solution to measure the percentage of Liquefied Petroleum Gas (LPG) inside domestic stationary tanks. The IoT-based sensor, in addition to displaying the percentage of the LPG level in the tank to the user through a mobile application (app), has the advantage of simultaneously sharing the acquired data with an LPG filling plant via the Internet. The design process and calculations for the selection of the electronic components of the IoT-based sensor are presented. The methodology for obtaining and calibrating the measurement of the tank filling percentage from the magnetic level measurement system is explained in detail. The operation of the developed software, and the communication protocols used are also explained so that the data can be queried both in the user’s app and on the gas company’s web platform safely. The use of the Clark and Wright savings algorithm is proposed to sufficiently optimize the distribution routes that tank trucks should follow when serving different home refill requests from customers located in different places in a city. The experimental results confirm the functionality and viability of the hardware and software developed. In addition, by having the precise location of the tank, the generation of optimized gas refill routes for thirty customers using the heuristic algorithm and a visualization of them on Google Maps is demonstrated. This can lead to competitive advantages for home gas distribution companies.

This work presents a hardware-based digital emulator capable of digitally driving a permanent magnet synchronous machine electronic setup. The aim of this work is to present a high-performance, cost-effective, and portable complementary solution when new paradigms of electronic drive design are generated, such as machine early failure detection, fault-tolerant drive, and high-performance control strategy implementations. In order to achieve the high performance required by the digital emulator, the electronic drive models (permanent-magnet synchronous machine, voltage-source inverter, motor-control strategy) are digitally described in Verilog hardware description language and implemented on a field programmable gate array (FPGA) digital platform using two approaches: parallel and sequential methods. The results obtained show the effectiveness of the digital emulator design, and the resources used by the solution presented can be implemented on a low-cost digital platform that reveals a cost-effective operation of the solution presented.

This work introduces the first four-quadrant CMOS analog multiplier circuit built entirely from digital inverter standard cells, without requiring any analog transistor-sizing methodologies. The multiplication operation is performed using a quadratic cancellation scheme in conjunction with a modified high-speed Nauta transconductor, which serves as summing point circuit. Consequently, the proposed multiplier achieves bandwidths of 2.2 GHz with x1 inverter cells and 3.8 GHz with x12 inverter cells, respectively. Additionally, the output offset issue is addressed by the same summing-point circuit. The power and silicon area consumption of both multipliers are 0.423 mW/( $7.6~\mu $ m $\times 14.73~\mu $ m) and 5.075 mW/( $17.8~\mu $ m $\times 14.73~\mu $ m), respectively. Mathematical modeling and post-layout transistor-level simulations using a TSMC 65 nm CMOS process, with a BSIM4 level 54 model, successfully validate the proposed multiplier. Finally, because the multiplication architecture is entirely composed of CMOS inverters (NOT gates), this circuit can be implemented and scaled for any advanced technology node that includes a digital standard-cell library.

In recent years, the digital emulation of power systems, such as induction machines, has increased, driven by advances in computational resources and the processing capabilities of digital platforms. These platforms offer a versatile approach to the design, analysis, and optimization of solutions in electric machine drive research. This work presents the design of an Induction Machine (IM) using a digital twin, simulating its performance and behavior under failure conditions using the DQ model. Additionally, this study presents the design and real-time digital emulation of an IM, incorporating a bearing-fault model. The implementation on an FPGA platform enables high-fidelity simulation and analysis of the machine’s performance under both healthy and faulty operating conditions. This approach introduces a distinctive and critical tool for pre-experimental validation, enabling the precise identification of key fault signatures and system responses under real-time conditions, a capability that is not explicitly addressed in existing studies. Quantitative results demonstrate that the digital model implementation is highly accurate in replicating the theoretical IM with a relative error below (<1%). Additionally, through frequency-domain analysis, the signatures of the injected fault can be observed.