Low-power System Research Articles

Development of 17-4 PH Stainless Steel for Low-Power Selective Laser Sintering.

Selective laser sintering (SLS) is one of the prominent methods of polymer additive manufacturing (AM). A low-power laser source is used to directly melt and sinter polymer material into the desired shape. This study focuses on the utilization of the low-power laser SLS system to successfully manufacture metallic components through the development of a metal-polymer composite material. In this study, 17-4 PH stainless powders are used and mixed with polyoxymethylene (POM) and high-density polyethylene (HDPE) to prepare the composite powder material. The polymeric mixture is removed during the thermal degreasing process and subsequent sintering results in a solid metallic component. Sinterit Lisa with a 5 W, 808 nm laser source is used to fabricate the green part. For the printing parameters of 140 °C, laser power of 35.87 mJ/mm2, and layer thickness of 100 μm, the printed samples achieved a maximum density of 3.61 g/cm3 and a complete shape. After sintering at 1310 °C for 180 min, the tensile strength of the shrunk sample is 605.64 MPa, the hardness is HRC 14.8, the average shrinkage rate is 22%, and the density is 7.57 g/cm3, which can reach 97% of the theoretical density. This process allows the use of a wide range of particle sizes that the usual AM technologies have, making it a low-cost, low-energy-consumption, high-speed AM technology.

Seizure detection via reservoir computing in MoS2-based charge trap memory devices.

Neurological disorders are a substantial global health burden, affecting millions of people worldwide. A key challenge in developing effective treatments and preventive measures is the realization of low-power wearable systems with early detection capabilities. Traditional strategies rely on machine learning algorithms, but their computational demands often exceed what miniaturized systems can provide. Neuromorphic computing, inspired by the human brain, demonstrated capabilities of on-chip computing with low power consumption. In this context, bidimensional (2D) semiconductors hold notable promise, thanks to their unique electronic properties, atomic-scale thickness, and scalability, making them ideal for low-power applications. This work presents a neuromorphic reservoir computing system exploiting MoS2-based charge trap memories (CTMs) for processing of electrophysiological signals. Real-time seizures detection is achieved, thanks to the nonlinear integration of local-field potential (LFP) recorded from in vitro rodent models of ictogenesis. The results support MoS2-based CTMs for low-power biomedical devices in clinical diagnosis and treatment of epilepsy.

Low-power edge detection based on ferroelectric field-effect transistor

Edge detection is one of the most essential research hotspots in computer vision and has a wide variety of applications, such as image segmentation, target detection, and other high-level image processing technologies. However, efficient edge detection is difficult in a resource-constrained environment, especially edge-computing hardware. Here, we report a low-power edge detection hardware system based on HfO2-based ferroelectric field-effect transistor, which is one of the most potential non-volatile memories for energy-efficient computing. Different from the conventional edge detectors requiring sophisticated hardware for the complex operation such as convolution and gradient, the proposed edge detector is analogue-to-digital converter free and loaded into a multi-bit content addressable memory, which only needs one 4 × 4 ferroelectric field-effect transistor NAND array. The experimental results show that the proposed hardware system is able to achieve efficient image edge detection at low power consumption (~10 fJ/per operation), realizing no-accuracy-loss, low-power and analogue-to-digital-converter-free hardware system, providing a feasible solution for edge computing.

Design of a release-free piezo-optomechanical quantum transducer

Quantum transduction between microwave and optical photons offers the potential to merge the long-range connectivity of optical photons with the deterministic quantum operations of superconducting microwave qubits. A promising approach to achieving this uses an intermediary mechanical mode along with piezo-optomechanical interactions. Traditionally, these transducers are suspended to confine mechanical fields, but this complicates manufacturing and comes with the major challenge of poor thermal anchoring and a trade-off between noise and efficiency. To overcome these issues, we introduce the—to our knowledge—first design of a release-free electro-optomechanical quantum transducer. Our release-free, i.e., non-suspended, design leverages a silicon-on-sapphire platform. It combines release-free lithium niobate electromechanical crystals with silicon optomechanical crystals on a sapphire substrate, optimizing thermal anchoring and microwave and mechanical coherence. Despite departing from the traditional suspended transducer paradigm, our release-free design achieves coupling rates sufficient for quantum-level interactions between microwave photons, phonons, and optical photons. Unconventionally, it utilizes high-wavevector mechanical modes tightly confined to the chip surface. Beyond quantum science and engineering, this platform and its design principles could also propel low-power acousto-optic systems in integrated photonics.

Study on Electrical and Temperature Characteristics of β-Ga2O3-Based Diodes Controlled by Varying Anode Work Function.

This study systematically investigates the effects of anode metals (Ti/Au and Ni/Au) with different work functions on the electrical and temperature characteristics of β-Ga2O3-based Schottky barrier diodes (SBDs), junction barrier Schottky diodes (JBSDs) and P-N diodes (PNDs), utilizing Silvaco TCAD simulation software, device fabrication and comparative analysis. From the perspective of transport characteristics, it is observed that the SBD exhibits a lower turn-on voltage and a higher current density. Notably, the Von of the Ti/Au anode SBD is merely 0.2 V, which is the lowest recorded value in the existing literature. The Von and current trend of two types of PNDs are nearly consistent, confirming that the contact between Ti/Au or Ni/Au and NiOx is ohmic. A theoretical derivation reveals the basic principles of the different contact resistances and current variations. With the combination of SBD and PND, the Von, current density, and variation rate of the JBSD lie between those of the SBD and PND. In terms of temperature characteristics, all diodes can work well at 200 °C, with both current density and Von showing a decreasing trend as the temperature increases. Among them, the PND with a Ni/Au anode exhibits the best thermal stability, with reductions in Von and current density of 8.20% and 25.31%, respectively, while the SBD with a Ti/Au anode shows the poorest performance, with reductions of 98.56% and 30.73%. Finally, the reverse breakdown (BV) characteristics of all six devices are tested. The average BV values for the PND with Ti/Au and Ni/Au anodes reach 1575 V and 1550 V, respectively. Moreover, although the Von of the JBSD decreases to 0.24 V, its average BV is approximately 220 V. This work could provide valuable insights for the future application of β-Ga2O3-based diodes in high-power and low-power consumption systems.

CNFET-Based Energy-Efficient 4:2 Compressor for Multiplier Applications

Diverse applications in today’s digital era have a high demand for low-power, faster, and high-performance arithmetic circuits. In a multiplier, the power is the costliest part of carrying out partial products. A compressor type of adder is used for faster operation and has lesser power consumption. In this paper, a low-power, energy-efficient 4:2 compressor design has been presented. The proposed design is based on multi-threshold logic. A capacitive network has been used at the input side instead of resistors for better circuit operations. The CNFET-based network is used to design the same. Powers, delay, PDP, and EDP of the proposed design have been computed. It is observed that with 32[Formula: see text]nm CNFET technology it shows a maximum improvement in PDP and EDP of 69% and 70%, respectively. Moreover, extensive performance analyses against power supply, channel length, temperature, load, and operating frequency have been presented. Finally, the proposed compressor is applied to design Wallace’s multiplier which shows that it outperforms all other designs considered in this study. This indicates that the proposed compressor is quite useful for low-power VLSI circuits and systems applications.

Design of a Magnetically Coupled Resonant Implantable Medical Device Wireless Power Transmission System

This paper systematically describes the design and optimisation strategy of wireless charging technology for implantable medical devices. Starting from the theoretical basis of magnetically coupled resonant wireless power transmission (MCR-WPT), an efficient transmission circuit is designed and the resonant circuit characteristics are analysed. Meanwhile, the effects of the outer diameter, the number of turns of the transmitting coil and the turns spacing on the magnetic flux density and the AC internal resistance are obtained through the principle analysis. The coil parameters are adjusted through simulation experiments to improve the transmission efficiency. Then, the safety and stability of the device are ensured by temperature-power double closed-loop control. Then the closed-loop phase-shift control strategy is introduced to ensure that the system can output power stably in complex environments. In this paper, a low-power, safe and high-efficiency wireless energy transmission system is built, which provides a comprehensive and in-depth technical reference for the development of wireless power supply technology for implantable medical devices.

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.

SHM System for Composite Material Based on Lamb Waves and Using Machine Learning on Hardware.

There is extensive use of nondestructive test (NDT) inspections on aircraft, and many techniques nowadays exist to inspect failures and cracks in their structures. Moreover, NDT inspections are part of a more general structural health monitoring (SHM) system, where cutting-edge technologies are needed as powerful resources to achieve high performance. The high-performance aspects of SHM systems are response time, power consumption, and usability, which are difficult to achieve because of the system's complexity. Then, it is even more challenging to develop a real-time low-power SHM system. Today, the ideal process is for structural health information extraction to be completed on the flight; however, the defects and damage are quantitatively made offline and on the ground, and sometimes, the respective procedure test is applied later on the ground, after the flight. For this reason, the present paper introduces an FPGA-based intelligent SHM system that processes Lamb wave signals using piezoelectric sensors to detect, classify, and locate damage in composite structures. The system employs machine learning (ML), specifically support vector machines (SVM), to classify damage while addressing outlier challenges with the Mahalanobis distance during the classification phase. To process the complex Lamb wave signals, the system incorporates well-known signal processing (DSP) techniques, including power spectrum density (PSD), wavelet transform, and Principal Component Analysis (PCA), for noise reduction, feature extraction, and data compression. These techniques enable the system to handle material anisotropy and mitigate the effects of edge reflections and mode conversions. Damage is quantitatively evaluated with classification accuracies of 96.25% for internal defects and 97.5% for external defects, with localization achieved by associating receiver positions with damage occurrence. This robust system is validated through experiments and demonstrates its potential for real-time applications in aerospace composite structures, addressing challenges related to material complexity, outliers, and scalable hardware implementation for larger sensor networks.

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.

Controlling Flooding and Parameter Sensitivity in an Anion Exchange Membrane Fuel Cell Using a Triblock Copolymer Membrane and Matched Ionomers

While there has been much interest in the proton exchange membrane (PEM) fuel cell, its wide spread use has been restricted by cost, durability, fuel versatility issues, and the environmental consequences of using perfluorosulfonic acid polymers as the membrane and ionomer. This is primarily because catalyst based on Pt are nessecary in a PEM fuel cell on both the anode and the cathode and reactive oxygen species chemically degrade the cell. Alkaline catalysis in fuel cells has been demonstrated with non-precious metal catalysts, and a variety of fuels beyond H2 and methanol. Alkaline fuel cells (AFCs), based on aqueous solutions of KOH, have serious drawbacks associated with system complexity, low system power densities and carbonate formation. Anion exchange membrane (AEMs) fuel cells have a number of advantages over both PEM fuel cells and traditional AFCs. Great strides have been made in ionic conductivity and durability in AEMs and fuel cells with reduced precious metal loadings have been demonstrated. However, AEM fuel cells have significant water management issues, as water is both a reactant and a product leading to flooding and control issues.We have developed a triblock copolymer Poly (vinylbenzyl-N-methylpiperidinium carbonate)-b-polyethylene-b-poly(vinylbenzyl-N-methylpiperidinium carbonate)as a robust, high performance, durable, and scalable AEM. We have modified the block ratios and ion exchange capacity of this material to show excellent performance and durability in both electro-desalination and water electrolysis. Despite the materials potential, we have only occasionally tested it as a fuel cell membrane. We have now begun to throughly evaluated the material in 5 cm2 H2/O2 fuel cell. Initial experiments showed good potential performance but were hampered by severe flooding of the electrodes. We will present a materials approach to solving this problem by investigating various related ionomers in the electrodes. Both variations of the polymer used to fabricate the membrane and a random co-polymer derived from polymethylbutylene and poly(vinylbenzyl-N-methylpiperidinium) were investigated. The effect of loading and ionomer ion exchange capacity on the performance of the fuel cell and the relationship between these properties will be reported.

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.