Power Consumption Of Devices Research Articles

Sm, Pt asymmetric n- and p-type contacts in WSe2 phototransistor for high-performance broadband photodetection

The development of high-performance broadband photodetectors working at room temperature is still attractive. The Schottky barrier phototransistor based on asymmetric junction seems to be endowed with such potential—as photodetectors with low device power consumption and high photoresponse; however, it is rarely studied. Herein, a Sm–WSe2–Pt phototransistor with asymmetric metal contacts is constructed, and it is systematically investigated for their electronic and photoelectronic tunability via gate voltage, wavelength, and illumination power density. It was found that the tunable photogating process dominates the photoresponse mechanism, which allows for an excellent broadband photodetection from 300 to 1000 nm wavelength. In addition, the responsivity (R) and specific detectivity (D*) at 450 nm can reach 1723 A/W and 2.3 × 1013 Jones, respectively, while that of infrared illumination of 900 nm can reach 4.7 A/W and 3.1 × 1010 Jones, respectively. In addition, the device exhibits obvious photoresponse at zero bias, the R and D* can reach up to 27 mA/W and 8.5 × 1010 Jones, which realizes self-driven photodetection. This work provides an optimal option for realizing high-integrated, high-performance, low-power-consuming, and room-temperature-working broadband photodetectors.

Low Power Volatile and Nonvolatile Memristive Devices from 1D MoO2-MoS2 Core-Shell Heterostructures for Future Bio-Inspired Computing.

Memristors-based integrated circuits for emerging bio-inspired computing paradigms require an integrated approach utilizing both volatile and nonvolatile memristive devices. Here, an innovative architecture comprising of 1D CVD-grown core-shell heterostructures (CSHSs) of MoO2-MoS2 is employed as memristors manifesting both volatile switching (with high selectivity of 107 and steep slope of 0.6mVdecade-1) and nonvolatile switching phenomena (with Ion/Ioff ≈103 and switching speed of 60ns). In these CSHSs, the metallic core MoO2 with high current carrying capacity provides a conformal and immaculate interface with semiconducting MoS2 shells and therefore it acts as a bottom electrode for the memristors. The power consumption in volatile devices is as low as 50pW per set transition and 0.1fW in standby mode. Voltage-driven current spikes are observed for volatile devices while with nonvolatile memristors, key features of a biological synapse such as short/long-term plasticity and paired pulse facilitation are emulated suggesting their potential for the development of neuromorphic circuits. These CSHSs offer an unprecedented solution for the interfacial issues between metallic electrodes and the layered materials-based switching element with the prospects of developing smaller footprint memristive devices for future integrated circuits.

Effect of interface quality on spin Hall magnetoresistance in Pt/MgFe2O4 bilayers

We report on spin Hall magnetoresistance (SMR) in bilayers composed of Pt and magnetic insulator MgFe2O4 (MFO) with spinel structure. The Pt thickness dependence of the SMR reveals that annealing of the MFO surface before depositing the Pt layer is crucial for a large SMR with better interface quality. We also found that oxygen pressure during the MFO growth hardly affects the SMR, while it influences the magnetic property of the MFO film. Our findings provide important clues to further understanding the spin transport at interfaces containing magnetic insulators, facilitating development of low power consumption devices.

Formation and stability of emulsion in the presence of nano particles in the modified smart aqueous phase: Effect of ultrasonic, salt, and surfactant

Synergistic effects of nanoparticles (NPs) and smart water flooding are new methods for enhanced oil recovery (EOR). One of the vital issues, in this case, is the formation and stability of emulsion. Therefore, investigating the role and performance of NPs and ions during the processes of EOR, which are based on smart water injection and natural reservoir production, is of significant importance. Previous studies have investigated various factors (i.e., compounds present in oil and water) that affect emulsion stability mainly at ambient temperatures. In this research, the effect of various factors, including the effect of surfactants, salts, and NPs, on the dynamics and thermodynamics of this phenomenon, has been studied through the visual analysis of emulsion droplets under high pressure (HP) and high-temperature (HT) conditions. Based on the results obtained from the experiments, the rate of formation and stability of emulsions increases by increasing the pressure, and after a certain pressure level, it decreases. On the other hand, in general, the rate of emulsion stability follows a decreasing trend by increasing the system temperature. Additionally, in this study, three salts, namely MgCl2, CaCl2, and NaCl, and two surfactants, AOS (alpha olefin sulfonate) and CTAB (cetrimonium bromide), were used. After finding the optimal weight percentage of these salts and surfactants in the formation and emulsion stability, they were combined with nanoparticles of silica oxide in different volume percentages, and the effect of these nanoparticles on the emulsion stability was investigated. The effect of ultrasonication on solutions containing NPs was also investigated from the point of view of emulsion formation and stability. Based on the results obtained, as the power consumption of the ultrasonic device increases to form an emulsion, the rate of rotation for its separation will also increase.

On-chip silicon electro-optical modulator with ultra-high extinction ratio for fiber-optic distributed acoustic sensing

Ultra-high extinction ratio (ER) optical modulation is crucial for achieving high-performance fiber-optic distributed acoustic sensing (DAS) for various applications. Bulky acousto-optical modulators (AOM) as one of the key devices in DAS have been used for many years, but their relatively large volume and high power consumption are becoming the bottlenecks to hinder the development of ultra-compact and energy-efficient DAS systems that are highly demanded in practice. Here, an on-chip silicon electro-optical modulator (EOM) based on multiple coupled microrings is demonstrated with ultra-high ER of up to 68 dB while the device size and power consumption are only 260 × 185 μm2 and 3.6 mW, respectively, which are at least two orders of magnitude lower than those of a typical AOM. Such an on-chip EOM is successfully applied to DAS with an ultra-high sensitivity of −71.2 dB rad2/Hz (4 pε/√Hz) and a low spatial crosstalk noise of −68.1 dB rad2/Hz, which are very similar to those using an AOM. This work may pave the way for realization of next-generation ultra-compact DAS systems by integration of on-chip opto-electronic devices and modules with the capability of mass-production.

High-performance self-powered solar-blind ultraviolet photodetector based on a 4H-SiC/ZnGa2O4 heterojunction and its application in optical communication

With the urgent demand for low power consumption, environment-friendly, and portable devices, self-powered solar-blind ultraviolet (UV) photodetectors that only rely on built-in electric fields without external power sources have received extensive attention. In this paper, we have demonstrated a self-powered solar-blind UV photodetector based on a 4H-SiC/ZnGa2O4 heterojunction, along with its application in optical communication. At 0 V bias, the device exhibits a peak responsivity of 115 mA/W with an external quantum efficiency of 58.4% at 244 nm, a fast response speed with a rise/decay time of 18.36/16.15 ms, and a high UV-vis rejection ratio of 4.5 × 104, suggesting that the device has an excellent self-powered solar-blind UV photodetection performance. The exceptional performance of the photodetector is mainly attributed to the 4H-SiC/ZnGa2O4 type I heterojunction with a large conduction band offset (ΔEC = 0.99 eV) and a large valence band offset (ΔEV = 0.75 eV), which is determined by the x-ray photoelectron spectroscopy technique. Moreover, the solar-blind UV optical communication is realized by utilizing the 4H-SiC/ZnGa2O4 heterojunction device to receive signals modulated by the solar-blind UV light. This work provides an effective approach to realizing high-performance self-powered solar-blind UV photodetectors and their potential applications in optical communication.

Integer Programming Models for Task Scheduling and Resource Allocation in Mobile Cloud Computing

In traditional mobile cloud computing, user tasks are uploaded and processed on a cloud server over the Internet. Due to the recent rapid increase in the number of mobile users connected to the network, due to overload of the Internet communication channels, there are significant delays in the delivery of data processed on cloud servers to the user. Furthermore, it complicates the optimal scheduling of the tasks of many users on cloud servers and the delivery of results. Scheduling is an approach used to reduce the tasks execution time by ensuring a balanced distribution of user tasks on cloud servers. The goal of scheduling is to ensure selection of appropriate resources to handle tasks quickly, taking into account user requirements. Whereas the goal of cloud service providers is to provide users with the required resources through performing effective scheduling so that both the user and the service provider can benefit. The article proposes a scheduling model to reduce processing time, network latency, and power consumption of mobile devices through optimal task placement in the cloudlet network in a mobile cloud computing environment.

On the Use of Low-power Devices, Approximate Adders and Near-threshold Operation for Energy-efficient Multipliers

With the rising importance of power consumption in battery-powered devices, approximate computing techniques have emerged as a promising approach to strike a balance between exact computation and power savings, leading to improved delays. This paper investigates the combination of near-threshold operation and approximate adders to design power-efficient multipliers. We analyzed four multiplier architectures using 16 nm low-power and high-performance models. At the transistor level, three strategies for approximate full adders are explored, focusing on both partial product reduction and the final addition stage of the multipliers. Eleven test cases are thoroughly evaluated to identify the most suitable approximate circuit, considering the trade-offs among power, performance, and accuracy. The obtained results demonstrate a substantial reduction in power consumption at near-threshold operation. The replacement of exact full adders with the approximate copy strategy in the least significant bits of the multipliers leads to a reduction of up to 34.4% in power consumption and 19.2% in delay. The design-space exploration carried out in this study provides valuable insights for designers to choose the best approximate multiplier based on specific design requirements.

Advances in Triboelectric Nanogenerators for Sustainable and Renewable Energy: Working Mechanism, Tribo-Surface Structure, Energy Storage-Collection System, and Applications

Triboelectric nanogenerators (TENGs) are emerging as a form of sustainable and renewable technology for harvesting wasted mechanical energy in nature, such as motion, waves, wind, and vibrations. TENG devices generate electricity through the cyclic working principle of contact and separation of tribo-material couples. This technology is used in outstanding applications in energy generation, human care, medicinal, biomedical, and industrial applications. TENG devices can be applied in many practical applications, such as portable power, self-powered sensors, electronics, and electric consumption devices. With TENG energy technologies, significant energy issues can be reduced or even solved in the near future, such as reducing gas emissions, increasing environmental protection, and improving human health. The performance of TENGs can be enhanced by utilizing materials with a significant contrast in their triboelectrical characteristics or by implementing advanced structural designs. This review comprehensively examines the recent advancements in TENG technologies for harnessing mechanical waste energy sources, with a primary focus on their sustainability and renewable energy attributes. It also delves into topics such as optimizing tribo-surface structures to enhance output performance, implementing energy storage systems to ensure stable operation and prolonged usage, exploring energy collection systems for efficient management of harvested energy, and highlighting practical applications of TENG in various contexts. The results indicate that TENG technologies have the potential to be widely applied in sustainable energy generation, renewable energy, industry, and human care in the near future.

Prototype of a System for Tracking Transit Service Based on IoV, ITS, and Machine Learning

The transit service in a city should be the most efficient, least polluting, most accessible, and sustainable means of transportation for its citizens. However, serious shortcomings have been detected, mainly in medium-sized cities in developing countries. These shortcomings are related to a lack of user information, insecurity, low service availability, and repeated stops in inappropriate and/or unauthorized places. Some of these shortcomings contribute to high accident rates and traffic congestion. The development of tools to improve the characteristics and conditions of transit service in cities has become an imperative need to improve the quality of life of citizens and city sustainability. Transit service tracking is relevant in aspects such as online location information to travelers and control by transport companies for compliance with speed limits, schedules, routes, and stops. This research proposes a transit vehicle tracking system based on the Internet of Vehicles (IoV) in Vehicle-to-Roadside (V2R) classification. The proposed system is ideal for the use of electric vehicles due to the low power consumption of the tracking device. This system uses Intelligent Transportation Systems (ITS) tracking service architecture, Long Range (LoRa) communication technology, and its LoRa Wide Area Network (LoRaWAN) protocol. Additionally, the system offers real-time location prediction in the absence of position data. The IoV tracking device integrates a GPS-LoRa module card with an Inertial Measurement Unit (IMU). A location prediction algorithm was implemented to train and store a prediction model with previously collected data from tracking devices. To evaluate the developed model, a case study in the city of Popayán (Colombia) was implemented, using three routes for testing. The results of the system implementation were satisfactory, obtaining an average coverage of 60.4% of the routes in the final field tests through LoRa communication. For the remaining 39.6% of the routes, location data prediction was used, with an average accuracy of 177 m with respect to the real location. Considering the obtained results, a tracking system such as the one proposed in this article can be used in the transit systems of medium-sized cities in developing countries to improve service quality and fleet control.

Distributed energy storage participating in power trading mechanism for power system flexibility

In the paper of the participation of multiple types of market members, such as photovoltaics, wind power, and distributed energy storage, in market-based trading, the development of new power systems hinges on strengthening the adaptability of power systems to accommodate various types of market participants and improving their flexibility. The establishment of a modern power system also faced major challenges. Such as how to achieving collaborative operation between the main grid, regional distribution networks, and distributed power generation and consumption devices, and how to improving the flexibility of grid operation, and how to increasing device utilization, and reducing operating costs. In view of above-mentioned issues, this study proposed employing the traceability and anti-tampering features of blockchain technology tackle the issue of establishing mutual trust among different types of market participants and, considering the high volatility of new energy output, studies the configuration of a flexible power system in response to output deviations resulting from day-ahead forecasting-intraday operation (DAF-IDO). A market-based trading mechanism involving multiple types of market participants has been established to smooth out the deviation in output from different types of participants, improving the economic benefits of system operation. This study has made innovative contributions as follows: First, this study employed blockchain technology to enable the participation of various types of market participants in trading activities together. Second, this study proposed a method for determining DAF-IDO energy storage action deviations to allow regional distribution networks based on distribution network operators to quantitatively calculate their energy storage supply and demand, providing crucial methodological support for their participation in market trading in the future. Third, the study developed a trading mechanism based on combinatorial auctions for multiple types of market participants, and incorporated an valley compensation mechanism into the pricing mechanism to encourage active and autonomous participation of users, while also considering the economic benefits of all parties involved. Ultimately, numerical simulations were conducted to verify the feasibility and rationality of the trading mechanism, taking into account the DAF-IDO energy storage action deviations while multiple regional networks are participating.

Surface topography detection based on an optical differential metasurface.

Surface topography detection can extract critical characteristics from objects, playing an important role in target identification and precision measurement. Here, an optical method with the advantages of low power consumption, high speed, and simple devices is proposed to realize the surface topography detection of low-contrast phase objects. By constructing reflected light paths, a metasurface can perform spatial differential operation via receiving the light directly reflected from a target. Therefore, our scheme is experimentally demonstrated as having remarkable universality, which can be used not only for opaque objects, but also for transparent pure phase objects. It provides a new, to the best of our knowledge, application for optical differential metasurfaces in precise detection of microscale surface topography.

A QCA placement and routing algorithm based on the SA algorithm

ABSTRACT In the Beyond Moore era, QCA (Quantum-dot Cellular Automata) has been widely studied because of its low power consumption and high device concentration. As the core of chip design, EDA technology has become an indispensable step in QCA research. It refers to the use of computer-aided design software to complete large-scale circuit function design, logic synthesis, placement and routing, design rule check and other processes. In the present study, there are still many defects in QCA placement and routing. The main problems it faces are low success rate, too large area and too many cross lines. To address these problems, our team had proposed a hybrid strategy based on the genetic algorithm and the improved A-star algorithm. But the running time of the previously proposed algorithm is not satisfying, besides it lacks self-adaption feature which is important as the problem size varies among different circuits. This paper replaces the genetic algorithm with a simulated annealing algorithm, and introduces a self-adaption strategy to better accommodate different circuit sizes. Experimental results show that the new algorithm combination possesses a higher success rate, lower running time and more intelligent adaption ability.

Transition Factors of Power Consumption Models for CPA Attacks on Cryptographic RISC-V SoC

Physical cryptographic devices are vulnerable to side-channel information leakages during operation. They are widely used in software as well as hardware implementations, ranging from microcontrollers and microprocessors to hardware accelerators in System on Chips (SoCs). Nowadays, cryptographic RISC-V SoCs are becoming the most prominent solution compared to the rest. Cryptographic accelerators provide users with a very high level of flexibility and customization of chips suited to specific applications in these systems. First, this research aims to confirm the effectiveness of the Correlation Power Analysis attack on cryptographic SoCs based on three different power consumption models. In each model, the effectiveness of an attack depends on the transition factor, which is a ratio related to different characteristics of the device's power consumption. Then, we focus on modifying the configuration on the SoC and attacking the AES hardware implementation on these designs. The experimental results show that applying the Switching Distance model brings the highest performance. With our suggested range of transition factors, the number of traces needed to find the secret key can be reduced by 13.35% in the best case.

Suppress ambient temperature interference strategy based on SnO2 gas semiconductor sensor using dynamic temperature modulation mode and principal component analysis algorithm

Semiconductor gas sensors have been widely used in environmental monitoring, toxic gas monitoring, respiratory marker monitoring and other fields due to their low price and high sensitivity etc. An easily overlooked parameter, ambient temperature, is a major factor affecting the accuracy of the sensor. In this paper, a new idea to suppress ambient temperature interference is proposed. Dynamic temperature modulation method is used to extend the dimension of output information, so that both ambient temperature and target gas concentration can be expressed simultaneously. The ambient temperature component is separated by coordinate transformation and component elimination. The data inverse transformation is carried out to achieve the purpose of suppressing the ambient temperature interference. Compared with the performance optimization of gas-sensing materials and additional temperature sensors, the first advantage of this method is to reduce the complexity and power consumption of sensor devices. In addition, the use of PCA algorithm also reduces the complexity of the recognition algorithm. At the same time, more intuitive data reduces the cost of parameter optimization.

Information Quality Improvement With Task Selection Algorithm For IoT Energy Harvesting Devices

The purpose of study is to propose a task selection algorithm that both keeps information quality and saves power consumption in IoT energy harvesting devices. The proposed algorithm not only keeps stable information quality but saves power loss also. The sensor node operation is divided into four tasks depending on the input data including battery capacity, solar panel charging current, and input sensor data variation. The task selector based on a neural network consists of an input layer, a hidden layer of 20 neurons, and an output layer. The proposed algorithm is different from the predefined task algorithm, which mainly focused on deep sleep mode or scheduled tasks. Our proposed algorithm helps the sensor node to be more adaptive to the environment based on real-time execution at each node. The collected information amount varies according to the input data variation. The experiment results show that the proposed algorithm collects higher quality information at large input data variation. The battery lifetime is also improved by up to 22%.

Large‐Scale N‐Type FET and Homogeneous CMOS Inverter Array Based on Few‐Layer MoTe2

Abstract2D MoTe2 is regarded as a favorable candidate for semiconductor nanoelectronics integration. Chemical‐vapor‐deposition‐grown MoTe2 usually presents p‐type characteristics. In order to realize basic electronic units like complementary metal‐oxide‐semiconductor (CMOS) inverter, controllable fabrication of p‐ and n‐type transistors at large scale is of vital importance. Here, large‐scale MoTe2 n‐channel field‐effect transistor (n‐FET) arrays are successfully fabricated with seamless coplanar metallic 1T′‐WTe2 contacts to reduce contact resistance. High‐k HfO2 serves as a gate dielectric and its atomic‐layer‐deposition (ALD) process causes an n‐doping effect on the 2H‐MoTe2 channel. The FETs perform typical n‐type characteristics with average electron density and on/off ratio of ≈1.7 × 1013 cm−2 and 2.1 × 104, respectively. Furthermore, large‐scale homogeneous CMOS inverter arrays are fabricated, showing clear logic swing with low power consumption (≈0.4 nW) and high device yield (≈92%). Notably, their voltage transfer characteristics exhibit small hysteresis, and they work well after being kept in air for 16 months, indicating high device stability. The statistical results show that both the n‐FETs and CMOS inverters have high uniformity and reliability in performance. Significantly, this fabrication method is free from transfer processes and compatible with traditional silicon technology. This work paves the way for the application of few‐layer MoTe2 in semiconductor nanoelectronics integration.

Design and Comparative Analysis of Silicon and GaAs MOSFET for Low Power Applications

The demand for low power consumption in modern electronic devices has led to the development of various technologies, including usage of different materials such as Si and GaAs. In this paper, we present a design and comparative analysis of Si and GaAs MOSFETs for low power applications. The analysis includes the electrical characteristics, performance parameters, and power consumption of both devices. The Si MOSFET and GaAs MOSFET are simulated and analyzed using TCAD tools, and the results are compared. The simulation results show that the GaAs MOSFET has a higher transconductance (gm) compared to the Si MOSFET. However, the Si MOSFET has a lower gate leakage current (Ig) and lower power consumption at low operating frequencies. We also investigate the effect of scaling on the performance and power consumption of both MOSFETs. The results show that scaling improves the performance of both devices, but the power consumption increases as the device dimensions are reduced. The comparative analysis of Si and GaAs MOSFETs for low power applications provides useful insights into the selection of suitable MOSFET technology for specific applications. The results show that both Si and GaAs MOSFETs have their advantages and disadvantages, and the choice depends on the application requirements.

Low-temperature growth of MoS2 on polymer and thin glass substrates for flexible electronics.

Recent advances in two-dimensional semiconductors, particularly molybdenum disulfide (MoS2), have enabled the fabrication of flexible electronic devices with outstanding mechanical flexibility. Previous approaches typically involved the synthesis of MoS2 on a rigid substrate at a high temperature followed by the transfer to a flexible substrate onto which the device is fabricated. A recurring drawback with this methodology is the fact that flexible substrates have a lower melting temperature than the MoS2 growth process, and that the transfer process degrades the electronic properties of MoS2. Here we report a strategy for directly synthesizing high-quality and high-crystallinity MoS2 monolayers on polymers and ultrathin glass substrates (thickness ~30 µm) at ~150 °C using metal-organic chemical vapour deposition. By avoiding the transfer process, the MoS2 quality is preserved. On flexible field-effect transistors, we achieve a mobility of 9.1 cm2 V-1 s-1 and a positive threshold voltage of +5 V, which is essential for reducing device power consumption. Moreover, under bending conditions, our logic circuits exhibit stable operation while phototransistors can detect light over a wide range of wavelengths from 405 nm to 904 nm.

Adaptive Algorithms for Batteryless LoRa-Based Sensors.

Ambient energy-powered sensors are becoming increasingly crucial for the sustainability of the Internet-of-Things (IoT). In particular, batteryless sensors are a cost-effective solution that require no battery maintenance, last longer and have greater weatherproofing properties due to the lack of a battery access panel. In this work, we study adaptive transmission algorithms to improve the performance of batteryless IoT sensors based on the LoRa protocol. First, we characterize the device power consumption during sensor measurement and/or transmission events. Then, we consider different scenarios and dynamically tune the most critical network parameters, such as inter-packet transmission time, data redundancy and packet size, to optimize the operation of the device. We design appropriate capacity-based storage, considering a renewable energy source (e.g., photovoltaic panel), and we analyze the probability of energy failures by exploiting both theoretical models and real energy traces. The results can be used as feedback to re-design the device to have an appropriate amount energy storage and meet certain reliability constraints. Finally, a cost analysis is also provided for the energy characteristics of our system, taking into account the dimensioning of both the capacitor and solar panel.