Low-power System Research Articles

Hardware Implementation for Triaxial Contact-Force Estimation from Stress Tactile Sensor Arrays: An Efficient Design Approach.

This paper presents a contribution to the state of the art in the design of tactile sensing algorithms that take advantage of the characteristics of generalized sparse matrix-vector multiplication to reduce the area, power consumption, and data storage required for real-time hardware implementation. This work also addresses the challenge of implementing the hardware to execute multiaxial contact-force estimation algorithms from a normal stress tactile sensor array on a field-programmable gate-array development platform, employing a high-level description approach. This paper describes the hardware implementation of the proposed sparse algorithm and that of an algorithm previously reported in the literature, comparing the results of both hardware implementations with the software results already validated. The calculation of force vectors on the proposed hardware required an average time of 58.68 ms, with an estimation error of 12.6% for normal forces and 7.7% for tangential forces on a 10 × 10 taxel tactile sensor array. Some advantages of the developed hardware are that it does not require additional memory elements, achieves a 4× reduction in processing elements compared to a non-sparse implementation, and meets the requirements of being generalizable, scalable, and efficient, allowing an expansion of the applications of normal stress sensors in low-power tactile systems.

Enhanced recognition of bonding interface defects within CFRP-steel adhesive structures via thermal signals in low-power vibrothermography

Carbon fiber reinforced polymers (CFRP) have been used as one of the options to strengthen steel structures through adhesive bonding, particularly in specific applications where traditional strengthening methods may not be suitable. Therefore, it becomes crucial to perform inspections on the resulting CFRP-steel adhesive structures (CSAS) to ensure their structural integrity and safety. However, the distinct physical properties of CFRP, epoxy resin, and steel pose significant challenges to accurately inspecting bonding interface defects of such special hybrid engineering structures. To address these challenges, a new approach, streamlined one-dimensional convolutional denoising autoencoder-low-power vibrothermography (SOCDAE-LVT), is proposed in this study to enhance the recognition of bonding interface defects within CSAS. This approach utilizes thermal signals from low-power vibrothermography (LVT) to enhance the recognizability of CSAS bonding interface defects. A low-power vibrothermography inspection system was developed to acquire thermal signals on the surface of CSAS samples. A streamlined one-dimensional convolutional denoising autoencoder (SOCDAE) model was designed for robust representation extraction of the thermal signal at each pixel point. The study further investigated the impact of different types of added noise and signal pre-processing approaches on the performance of the SOCDAE-LVT, aiming to optimize its effectiveness. By comparing qualitatively and quantitatively with the state-of-the-art approaches, the results show that the proposed approach can better improve the recognizability of defects. The enhanced recognizability of bonding interface defects enables accurate assessment of the quality of CSAS, thereby contributing to the safety of such structures.

A charge trap–based MoSe2 device emulating bio-realistic synaptic functionalities

Abstract Synaptic devices based on two-dimensional (2D) materials are promising toward the development of high-performance and low-power neuromorphic systems. In this study, we report a single-channel, three-terminal-based nonvolatile and multistate device based on 2D MoSe2. The device operates on the principle of trapping and detrapping of electrons at the MoSe2/SiO2 interface, in response to an applied gate voltage, resulting in a nonvolatile modulation of the threshold voltage. The memory behavior is highly reproducible as verified for around 100 cycles of the gate voltage sweep. The multistate behavior of the MoSe2 device was exploited to demonstrate the characteristics of the biological synapse. The device exhibits various synaptic functions, such as potentiation, depression, spike rate–dependent plasticity, spike magnitude–dependent plasticity, and the ability to transition from short-term to long-term memory. The bio-realistic synaptic behavior of the MoSe2 device underscores its promising potential for neuromorphic hardware.

Reference frequency variance-based rapid identification method for vortex flow rate under mixed vibration interference

Pipeline systems in industrial applications may encounter strong mixed vibration interference, resulting in measurement errors of vortex flowmeters. Current research primarily addresses single types of vibration interference. Various signals output by vortex flow sensors under diverse operating conditions were analyzed to tackle the issue of mixed vibration interference. The amplitude and frequency characteristics of transient impact-type interferences were studied. The differences in frequency fluctuations between periodic interferences and periodic signals were investigated. Then, a method based on reference frequency variance was proposed to resist mixed vibration interference. The primary calculation load of this method arises from the execution of Fast Fourier Transform (FFT). To meet the instrument requirements of low-power consumption and real-time performance, a multipoint FFT method based on a low-power accelerator built-in microcontroller was proposed, which remarkably improved the calculation speed of multipoint FFT and conserved storage space. The reference frequency variance-based antimixed vibration interference algorithm was implemented in real time using a low-power vortex flowmeter system developed by our team, and an antimixed vibration interference gas flow verification experiment was conducted. The method can accurately identify vortex flow signals when the interference energy of the periodic type and the main mode energy of the transient impact surpasses the energy of the flow signal.

Mass-loaded suspended piezoelectric micromachined ultrasonic transducer array towards flexible stretchable electronics evaluation

We introduce a novel piezoelectric micromachined ultrasonic transducer (PMUT) with a mass-loaded suspended (MLSP) design, fabricated using sacrificial technique to advance the non-destructive testing (NDT) of flexible electronics. The MLSP features four trenches uniformly distributed at the membrane’s edge and a mass load atop the membrane. These trenches transform the PMUT into a suspended membrane, significantly enhancing its sensitivity and effective vibrational area. The mass load is strategically added to tune the frequency and further boost sensitivity, while maintaining the same size and frequency as traditional clamped PMUTs (CP). In practice, we designed and fabricated 11 MHz PMUT arrays with a cell diameter of 40 μm. Experiments demonstrated that MLSP’s displacement is 2.2 times that of CP, and its pulse-echo sensitivity is 2.1 times higher. Mechanical scanning-based imaging of internal electrodes in stretchable electronic models revealed that MLSP provides better image contrast, clarity, and more accurate defect detection compared to CP. These findings underscore the potential of this innovative PMUT design for advancing compact, low-power handheld ultrasound systems in the flexible electronics sector. This approach offers a viable solution to meet the escalating demands for non-destructive testing (NDT).

GaAs-based antenna-coupled field effect transistors as direct THz detectors across a wide frequency range from 0.2 to 29.8 THz

High-power coherent terahertz (THz) radiation from accelerator facilities such as free-electron lasers (FELs) is frequently used in pump-probe experiments where the pump or probe (or both) signals are intense THz pulses. Detectors for these applications have unique requirements that differ from those of low-power table-top systems. In this study, we demonstrate GaAs antenna-coupled field effect transistors (FETs) as a direct THz detector operating across a broad frequency spectrum ranging from 0.2 THz to 29.8 THz. At approximately 0.5 THz, the maximum current responsivity (ℜ I ) of 0.59 mA/W is observed, signifying a noise equivalent power (NEP) of 2.27 nW/√Hz. We report an empirical roll-off of f−3 for an antenna-coupled GaAs TeraFET detector. Still, NEP of 0.94 μW/√Hz and a current responsivity ℜ I = 1.7μA/W is observed at 29.8 THz, indicating that with sufficient power the FET can be used from sub-mm wave to beyond far-infrared frequency range. Current and voltage noise floor of the characterized TeraFET is 2.09 pA and 6.84 μV, respectively. This characteristic makes GaAs FETs more suitable for applications requiring higher frequencies, ultra-broadband capabilities and robustness in the THz domain, such as beam diagnostics and alignment at particle accelerators.

Design of Cascode Current Mirror Using CMOS Technology for Low Power Application

Background: Many applications, including biological applications, require a very high output impedance current mirror because they run at very low voltages. The circuit known as the current mirror applies the idea that two identical MOS transistors with the same gate-source voltage will have equal channel currents flowing through them. Objective: The objective of this study is to optimize the design to minimize power consumption while maintaining accurate current mirroring, which is crucial for low-power and energy-efficient electronic systems. Methods: This study is performed in Cadence Virtuoso using the gdpk45 technology node to construct a cascode current mirror, comparing simulation findings to other contemporary mirrors. Results: A significant improvement in power usage is shown compared to other current mirrors, and a small signal model analysis of the circuit, the design, and its mathematical model is investigated. Conclusion: Compared to the circuits that were previously designed, the output resistance values are substantially greater. The cascode current mirror that is suggested in this paper uses 48 μW of electricity, while the other cascode current mirror uses 74.186 μW.

Influence of cyclic ignition and steady-state operation on a 1–2 A barium tungsten hollow cathode

Booming low-power electric propulsion systems require 1–2 A hollow cathodes. Such cathodes are expected to go through more frequent ignitions in the low orbit, but the impact of cyclic ignitions on such 1–2 A barium tungsten hollow cathodes with a heater was not clear. In this study, a 12,638-cyclic ignition test and a 6,000 hour-long life test on two identical cathodes were carried out. The discharge voltage of the cathode and the erosion of the orifice after cyclic ignition were all larger than that of the cathode after stable operation. This indicated that the impact of cycle ignition on the discharge performance of a low current BaO-W cathode with a heater was higher than that of stable operation. The results of the ion energy distribution function measured during the ignition period indicated that the main reason for the orifice expansion was ion bombardment. Therefore, it was necessary to pay attention to the number of ignitions for the lifetime of this kind of cathode.

Image enhancement methods for inspection of planar and non-planar FRP structures using a noise-based microwave NDT inspection system

Microwave nondestructive testing (MNDT) includes inspection techniques that assess a particular material’s health status using low-power and contactless inspection systems. In near-field microwave inspections, imaging results are heavily influenced by the standoff distance parameter, i.e., the physical separation between the microwave sensor and the sample under test (SUT). Variations in the standoff distance during an inspection tend to cause defect masking of disbonds and delaminations in fiber-reinforced polymer (FRP) materials, causing defects to go undetected frequently. An MNDT near-field inspection system using noise waveforms is used to identify engineered internal defects within carbon fiber-reinforced polymer (CFRP) samples. Tactics utilizing Principal Component Analysis (PCA), Stacked Sparse Autoencoders (SSAEs), and an autoencoder network trained in a manner for anomaly detection are used to minimize the effects of standoff distance, reduce defect masking, and increase the ability to identify hidden defects. The samples tested are constructed to possess planar and non-planar geometries, such that the viability of the data-driven image enhancement and standoff distance correction methods are demonstrated with respect to a wide variety of in situ inspection applications.

Design and analysis of power decoupling based microinverter considering parasitic parameters

With fossil energy reducing year by year, more and more attention to the new energy sources greatly promotes the development of the distributed power generation system, especially the low-power photovoltaic system. However, the power injected into the single-phase grid is time-varying, an electrolytic capacitor with large bulk should be paralleled with PV to balance the input and output power ripple. But the electrolytic capacitor has a very short lifetime, which could shorten the whole inverter’s lifetime. In this paper, the operational principle of the power decoupling based microinverter considering parasitic parameters is proposed, in which a film capacitor with small capacitance value replaces the electrolytic capacitor to improve the lifetime of the inverter. Further, the operating mode of the transformer and the decoupling capability is analyzed, and obtains the reasons affecting the inverter steady-state performance. Finally, the simulation and experiment validation of the proposed microinverter have been accomplished. Base on the analysis method proposed in this paper, a more accurate device selection can be provided for industrial design.

Mobile Application Development for Prepaid Water Meter Based on LC Sensor

This study presents a novel low-cost and low-power prepaid water meter system that combines tokenization and LC sensors to monitor water consumption accurately with mobile application via Bluetooth Low Energy (BLE) connectivity compared to conventional meters. Water meters play a vital role in monitoring water usage in Indonesia. Postpaid billing methods that rely on manual data recording are a source of concern due to potential inaccuracies caused by human error. This study presents the development of a prepaid water meter system that integrates LC sensors, BLE connectivity, a tokenization mechanism, and a mobile application to address this issue. The system offers a cost-effective solution by utilizing BLE + Global System for Mobile (GSM) from the user’s mobile phone. Using the design thinking methodology, the mobile application for the prepaid water meter achieved a usability testing score of 80. The load testing results for the back-end server, conducted with a sample size of 515 users, revealed a back-end latency of 1.973 milliseconds and an error rate of 8.74%. Furthermore, the LC sensors integrated into the PWM device showed an average error rate of 1.33%. The power consumption during each work cycle was measured at 129 mA and each battery is expected to last six years. Overall, with simple LC sensors, this system can precisely measure water usage.

Comparative Analysis of Piezoelectric Transducers for Low-Power Systems: A Focus on Vibration Energy Harvesting

Comparative Analysis of Piezoelectric Transducers for Low-Power Systems: A Focus on Vibration Energy Harvesting

Simulation and Experimental Study on Heat Transfer Performance of Bionic Structure-Based Battery Liquid Cooling Plate

This study presents a bionic structure-based liquid cooling plate designed to address the heat generation characteristics of prismatic lithium-ion batteries. The size of the lithium-ion battery is 148 mm × 26 mm × 97 mm, the positive pole size is 20 mm × 20 mm × 3 mm, and the negative pole size is 22 mm × 20 mm × 3 mm. Experimental testing of the Li-ion battery’s heat generation model parameters, in conjunction with bionic structure and micro-channel features, has led to the development of this innovative cooling system. The traditional bionic liquid cooling plate’s structure is often singular; however, the flow path of the liquid cooling plate designed in this paper is based on the combination of the distribution of human blood vessel branches and the structure of insect wing veins. The external dimension of the liquid cooling plate is 152 mm × 100 mm × 6 mm (length × width × height). Utilizing numerical simulation and thermodynamic principles, we analyzed the heat transfer efficacy of the bionic liquid cooling module for power batteries. Specifically, we investigated the impact of varying coolant flow rates and the contact radius between flow channels on the thermal performance of the bionic battery modules. Our findings indicate that a liquid flow rate of 0.6 m/s achieves a stable maximum surface temperature and temperature differential across the bionic battery liquid cooling module, with a relatively low overall system power consumption, suggesting room for further enhancement of heat transfer performance. By augmenting the contact radius between flow channels, we observed an initial increase in the maximum surface temperature, temperature differential, and inlet–outlet pressure differential at a flow rate of 0.2 m/s. However, at flow rates equal to or exceeding 0.4 m/s, these parameters stabilized across different design Scenarios. Notably, the pump power consumption remained consistent across various scenarios and flow rates. This study’s outcomes offer valuable insights for the development of liquid-cooled battery thermal management systems that are energy-efficient and offer superior heat transfer capabilities.

Low-power adaptive sampling electronic nose system with a Radon transform-based convolutional neural network for optimized gas recognition

The electronic nose (E-nose) systems provide great promise in capturing information about the identity of gaseous chemical analytes as well as their temporal variation. However, the regular and dense sampling events of the E-nose often lead to a substantial amount of redundancy in the temporal structure, which in turn limits their application in efficiency-sensitive scenarios such as advanced robotics and the Internet of Things. Herein, we introduce a novel operating mechanism for E-noses, which dynamically adjusts the time interval of operation to reduce power consumption and information content through an adaptive sampling mechanism. Three strategic schemes with different operating principles are presented to implement this mechanism: the accurate scheme targets the optimized discrimination accuracy, the vague scheme is oriented toward power-sensitive scenarios, and the balanced scheme aims to balance cost and benefit. In order to ensure that the adaptively sampled inhomogeneous data can be compatible with each other, we further propose an algorithm based on the Radon transform that can convert non-uniform time series with timestamp information into the same size tensor. Finally, we designed a convolutional neural network-based classification model for gaseous chemical analytes, providing guidance on scheme and parameter selection with an accuracy of up to 99 % and power savings of up to 96 %. Overall, this work provides a novel solution to optimize temporal redundancy in E-nose systems and a generalized approach to the corresponding deep-learning data processing.

Quad-Band Rectifier Circuit Design for IoT Applications

In this work, a novel quad-band rectifier circuit is introduced for RF energy harvesting and Internet of Things (IoT) applications. The proposed rectifier operates in the Wi-Fi frequency band and can supply low-power sensors and systems used in IoT services. The circuit operates at 2.4, 3.5, 5, and 5.8 GHz. The proposed RF-to-DC rectifier is designed based on Delon theory and Greinacher topology on an RT/Duroid 5880 substrate. The results show that our proposed circuit can harvest RF energy from the environment, providing maximum power conversion efficiency (PCE) greater than 81% when the output load is 0.511 kΩ and the input power is 12 dBm. In this work, we provide a comprehensive design framework for an affordable RF-to-DC rectifier. Our circuit performs better than similar designs in the literature. This rectifier could be integrated into an IoT node to harvest RF energy, thereby proving a green energy source. The IoT node can operate at various frequencies.

A Low-Power, High-Resolution Analog Front-End Circuit for Carbon-Based SWIR Photodetector

Carbon nanotube field-effect transistors (CNT-FETs) have shown great promise in infrared image detection due to their high mobility, low cost, and compatibility with silicon-based technologies. This paper presents the design and simulation of a column-level analog front-end (AFE) circuit tailored for carbon-based short-wave infrared (SWIR) photodetectors. The AFE integrates a Capacitor Trans-impedance Amplifier (CTIA) for current-to-voltage conversion, coupled with Correlated Double Sampling (CDS) for noise reduction and operational amplifier offset suppression. A 10-bit/125 kHz Successive Approximation analog-to-digital converter (SAR ADC) completes the signal processing chain, achieving rail-to-rail input/output with minimized component count. Fabricated using 0.18 μm CMOS technology, the AFE demonstrates a high signal-to-noise ratio (SNR) of 59.27 dB and an Effective Number of Bits (ENOB) of 9.35, with a detectable current range from 500 pA to 100.5 nA and a total power consumption of 7.5 mW. These results confirm the suitability of the proposed AFE for high-precision, low-power SWIR detection systems, with potential applications in medical imaging, night vision, and autonomous driving systems.

Engineering wafer scale single-crystalline Si growth on epitaxial Gd2O3/Si(111) substrate using radio frequency sputtering for silicon on insulator application

Silicon on Insulator (SOI) technology has been the promising solution for the On-chip low-power mixed-signal systems. However, the traditional smart-cut method for SOI wafer fabrication is costly. Hence, in this work, we present an optimized methodology to fabricate a wafer scale single-crystalline Si on epitaxial Gd2O3/Si(111) substrate (SOXI) using a low-cost, high volume manufacturable (HVM)-friendly Radio Frequency magnetron sputtering technique for SOI application. The grown Si and Gd2O3 layers are physically characterized using high-resolution X-ray Diffraction and high-resolution Transmission Electron Microscopy (HRTEM). The Grazing Incidence X-ray Diffraction, Pole Figure, and HRTEM imaging confirm the formation of an epitaxial Top-Si layer on the epitaxial-Gd2O3/Si(111) substrate. Hence, we demonstrate a low-cost, HVM-friendly technique for the fabrication of SOXI wafers.

A Lightweight Visual Understanding System for Enhanced Assistance to the Visually Impaired Using an Embedded Platform

Visually impaired individuals often face significant challenges in navigating their environments due to limited access to visual information. To address this issue, a portable, cost-effective assistive tool is proposed to operate on a low-power embedded system such as the Jetson Nano. The novelty of this research lies in developing an efficient, lightweight video captioning model within constrained resources to ensure its compatibility with embedded platforms. This research aims to enhance the autonomy and accessibility of visually impaired people by providing audio descriptions of their surroundings through the processing of live-streaming videos. The proposed system utilizes two distinct lightweight deep learning modules: an object detection module based on the state-of-the-art YOLOv7 model, and a video captioning module that utilizes both the Video Swin Transformer and 2D-CNN for feature extraction, along with the Transformer network for caption generation. The goal of the object detection module is for providing real-time multiple object identification in the surrounding environment of the blind while the video captioning module is to provide detailed descriptions of the entire visual scenes and activities including objects, actions, and relationships between them. The user interacts via a headphone with the proposed system using a specific audio command to trigger the corresponding module even object detection or video captioning and receiving an audio description output for the visual contents. The system demonstrates satisfactory results, achieving inference speeds between 0.11 to 1.1 seconds for object detection and 0.91 to 1.85 seconds for video captioning, evaluated through both quantitative metrics and subjective assessments.

Ku-band 300 kW high power ferrite phase shifter.

Phase shifter (PS) is a key component of a phased array antenna (PAA) system, which controls the microwave phase and realizes the antenna beam forming and scanning. A ferrite PS (FPS) is a current-controlled PS that uses the ferrite's gyromagnetic properties to realize phase shifting. It has the advantages of short phase switching time, low microwave loss, and high reliability and, therefore, has been widely used in low-power PAA systems. However, the power handling capability of the traditional Ku-band FPS is only a few kW, prohibiting FPS from being used in high-power microwave (HPM) PAA systems. Spurred by this concern, this paper proposes a new dual-toroid FPS structure with an external magnetic excitation. By optimizing the PS configuration, improving the integration process, and enhancing the performance of ferrite materials, a single FPS in the Ku band has reached the power handling capability of more than 300 kW with an insertion loss of less than -1.2 dB, the phase shift range of 0°-360°, the width less than 11.5mm, and the ability of a one-dimensional array. The FPS has the potential to be used in the PAA of an HPM system, laying a foundation for the research of the HPM PAA system.

Low power techniques for internet of things implementation: A review

The motive of designing a low-power system is to have a long battery life. One can carefully apply low-power design techniques to achieve low power consumption with proper system functioning to increase battery life. One such system where many devices are generally battery-operated and connected to the internet is the Internet of Things (IoT). IoT devices are used widely to gather data to propel actions and transmit the data for data analysis, connectivity, and automation. So much research is focused on IoT communication and computation in IoT devices, which increases power consumption. This survey explores low-power design strategies used at the architectural level. Additionally, it highlights the IoT features that give opportunities to apply low-power design methodologies to achieve less power consumption in IoT. Low-power design techniques are critical for the efficient functioning of Internet of Things (IoT) applications, where devices often operate in resource-constrained environments with limited power sources like batteries. Many applications of IoT are noticed including the domains such as industry, environment, and society, which are highly power-consuming because of the features such as computation, communication, security, and fault tolerance. Researchers have already reported the usefulness of many such techniques including architecture-level low-power design techniques. Still, it is observed that the work carried out is inadequate regarding power consumption, and communication bandwidth bottlenecks. In the present work, a rigorous literature survey is carried out based on low-power design techniques to support sustainable growth of IoT applications across various domains and power optimization.