Electrical Domain Research Articles

Role of polarization evolution in the hysteresis effect of Pb-based antiferroelecrtics

The electric field-induced irreversible domain wall motion results in a ferroelectric (FE) hysteresis. In antiferroelectrics (AFEs), the irreversible phase transition is the main reason for the hysteresis effects, which plays an important role in energy storage performance. Compared to the well-demonstrated FE hysteresis, the structural mechanism of the hysteresis in AFE is not well understood. In this work, the underlying correlation between structure and the hysteresis effect is unveiled in Pb(Zr,Sn,Ti)O3 AFE system by using in-situ electrical biasing synchrotron X-ray diffraction. It is found that the AFE with a canting dipole configuration, which shows a continuous polarization rotation under the electric field, tends to have a small hysteresis effect. It presents a negligible phase transition, a small axis ratio, and electric field-induced lattice changing, small domain switching. All these features together lead to a slim hysteresis loop and a high energy storage efficiency. These results offer a deep insight into the structure-hysteresis relationship of AFEs and are helpful for the design of energy storage material.

A Hybrid Optical-Electrical Analog Deep Learning Accelerator Using Incoherent Optical Signals

Optical deep learning (DL) accelerators have attracted significant interests due to their latency and power advantages. In this article, we focus on incoherent optical designs. A significant challenge is that there is no known solution to perform single-wavelength accumulation (a key operation required for DL workloads) using incoherent optical signals efficiently. Therefore, we devise a hybrid approach, where accumulation is done in the electrical domain, and multiplication is performed in the optical domain. The key technology enabler of our design is the transistor laser, which performs electrical-to-optical and optical-to-electrical conversions efficiently. Through detailed design and evaluation of our design, along with a comprehensive benchmarking study against state-of-the-art RRAM-based designs, we derive the following key results: (1) For a four-layer multilayer perceptron network, our design achieves 115× and 17.11× improvements in latency and energy, respectively, compared to the RRAM-based design. We can take full advantage of the speed and energy benefits of the optical technology because the inference task can be entirely mapped onto our design. (2) For a complex workload (Resnet50), weight reprogramming is needed, and intermediate results need to be stored/re-fetched to/from memories. In this case, for the same area, our design still outperforms the RRAM-based design by 15.92× in inference latency, and 8.99× in energy.

State-Flow Control Based Multistage Constant-Current Battery Charger for Electric Two-Wheeler

Battery charging is a greater challenge in the emerging electric vehicle domain. A newer multistage constant-current (MSCC) charging technique encompassing state-flow control tool-based design is implemented for charging the battery of an electric two-wheeler. MSCC method allows for faster charging and reduced battery degradation per charge. The designed controller incorporates line current power factor correction, thereby limiting the total harmonic distortion (THD) in line current and reactive power. The control strategy for battery charging has been developed using the state flow chart approach for implementing MSCC. The model has been formulated and implemented in MATLAB/Simulink. The proposed control monitors the state-of-charge (SOC) of the battery, age, and thermal behavior due to the charging strategy. The results show that the proposed charging technique with a state flow control approach gives effective and efficient output with reduced THD. Simulation results disclose that the desired parameters are controllable, stable, and effective within the operational limits.

Urban IoT ontologies for sharing and electric mobility

Cities worldwide are facing the challenge of digital information governance: different and competing service providers operating Internet of Things (IoT) devices often produce and maintain large amounts of data related to the urban environment. As a consequence, the need for interoperability arises between heterogeneous and distributed information, to enable city councils to make data-driven decisions and to provide new and effective added value services to their citizens. In this paper, we present the Urban IoT suite of ontologies, a common conceptual model to harmonise the data exchanges between municipalities and service providers, with specific focus on the sharing mobility and electric mobility domains.

Femtosecond-precision electronic clock distribution in CMOS chips by injecting frequency comb-extracted photocurrent pulses

A clock distribution network (CDN) is a ubiquitous on-chip element that provides synchronized clock signals to all different circuit blocks in the chip. To maximize the chip performance, today’s CDN demands lower jitter, skew, and heat dissipation. Conventionally, on-chip clock signals have been distributed in the electric voltage domain, resulting in increased jitter, skew, and heat dissipation due to clock drivers. While low-jitter optical pulses have been locally injected in the chip, research on effective distribution of such high-quality clock signals has been relatively sparse. Here, we demonstrate femtosecond-precision distribution of electronic clocks using driver-less CDNs injected by photocurrent pulses extracted from an optical frequency comb source. Femtosecond-level on-chip jitter and skew can be achieved for gigahertz-rate clocking of CMOS chips by combining ultralow comb-jitter, multiple driver-less metal-meshes, and active skew control. This work shows the potential of optical frequency combs for distributing high-quality clock signals inside high-performance integrated circuits, including 3D integrated circuits.

A piezoelectric energy harvester with inner beam adapting to low and high wind speeds: modeling, simulation and experiment

Traditional vortex-induced vibration energy harvesters could transform wind or water energy into electricity at low flowing speeds. However, it has the disadvantage of narrow working speed band, which limits wide application in velocity-changing environments. A piezoelectric harvester with an inner beam for harvesting wind energy at both low and high wind speed regions is presented. A comprehensive nonlinear distributed fluid–solid–electric governing equations for vortex-induced vibration piezoelectric energy harvesting are derived and the theoretical results show that dimensions of outer beam and diameter of attached cylinder can affect optimal wind speed and maximum power output at both low and high wind speeds. In contrast, the dimensions of the inner beam and mass block only have impacts at high wind speeds. The equivalent circuit modeling method is utilized to analyze energy harvesting output characteristics. Analogies between mechanical and electrical domains are built, and the governing equations are converted to circuit equations. Then the circuit equations are settled in electrical software for time-varying analysis. The electrical circuit simulation results show that the optimal load resistance is 400 kΩ at low wind speed and 500 kΩ at low wind speed, which is consistent with theoretical results. The prototypes were fabricated and experiments were carried out in a wind tunnel. Experimental results indicate that energy harvester could generate power at both low and high speeds. Mass block has great impact on optical speed and working wind speed band. The energy harvester with 7.06 g mass block could output 127.36 μW at 2.65 m s−1 and 63.63 μW at 4.4 m s−1. Numerical and circuit simulation results are consistent with experimental results on optical load resistances and optical wind speeds. This design provides a feasible method for broadening wind speed region for energy harvesting.

Existence of Magneto-Resistance and Magneto-Dielectric Effect in Composite of Perovskite Pb0.79Nd0.21TiO3 and Sr -Based U-Type Hexaferrite (Sr1–3xNd2x)4Co2Fe36O60

The increasing demand of multipurpose equipment materials leads us to study the behaviour of composite consisting of ferroelectrics with high dielectric properties and ferrites with magnetic properties. The coupling among the properties of these materials with one another will favor many application paths. Based upon the dielectric and magnetic properties of perovskite and U-type hexaferrite, composite of these materials have been selected for this study. The composites, (1-x)PbNdTiO3-x(Sr1–3x Nd2x )4Co2Fe36O60 where x = 0.42, 0.44, 0.46, 0.48 are manufactured using the solid state reaction process, and analyzed for phase formation. The magnetic, dielectric and magneto-dielectric properties have been considered. The coupling between the electric and magnetic domains on imposing electric and magnetic forces on the materials has been established under this work. All of the samples showed magneto-electric coupling, according to the magneto-dielectric investigation. The sample, however, indicates the highest coupling for x = 0.46 with MDR% values of 90.68% which may be due to the appearance of high magneto-resistance (68.23%) in this sample.

Pain Detection in Biophysiological Signals: Knowledge Transfer from Short-Term to Long-Term Stimuli Based on Distance-Specific Segment Selection

In this study, we analyze a signal segmentation-specific pain duration transfer task by applying knowledge transfer from short-term (phasic) pain stimuli to long-term (tonic) pain stimuli. To this end, we focus on the physiological signals of the X-ITE Pain Database. We evaluate different distance-based segment selection approaches with the aim of identifying individual segments of the corresponding tonic stimuli that lead to the best classification performance. The phasic domain is used to train the classification model. In the first main step, we compute class-specific prototypes for the phasic domain. In the second main step, we compute the distances between all segments of the tonic samples and each prototype. The segment with the lowest distance to the prototypes is then fed to the classifier. Our analysis includes the evaluation of a variety of distance metrics, namely the Euclidean, Bray–Curtis, Canberra, Chebyshev, City-Block and Wasserstein distances. Our results show that in combination with most of the metrics used, the distance-based selection of one individual segment outperforms the naive approach in which the tonic stimuli are fed to the phasic domain-based classification model without any adaptation. Moreover, most of the evaluated distance-based segment selection approaches lead to outcomes that are close to the classification performance, which is obtained by focusing on the respective best segments. For instance, for the trapezius (TRA) signal, in combination with the electric pain domain, we obtained an averaged accuracy of 68.0%, while the naive approach led to 66.0%. For the thermal pain domain, in combination with the electrodermal activity (EDA) signal, we obtained an averaged accuracy of 59.6%, outperforming the naive approach, which led to 53.2%.

On the mechanism of anomalous phenomena in current-carrying magnetized plasma

The explanation of the mechanisms of anomalous resistance and diffusion of plasma, as well as the generation of fast particles, is given from a unified position on the basis of experimental results obtained in plasma in a magnetically isolated diode of an electron accelerator with a microsecond pulse duration. It is shown that oscillations of the potential and current in plasma with current occur by charge separation and the formation of electric domains with a strong field. Electric domains are generated by means of runaway electrons resulting from the redistribution of the current density and its channelling in the current-carrying plasma. An increase in plasma resistance occurs due to a decrease in the number of electrons in the current-conducting state, since some of the plasma electrons pass into layers of excess negative charge of electric domains. The speed of movement of electrons in the composition of the electric domain is much lower than the velocity of electrons in the conducting state. The nucleation of domains is accompanied by microwave emission. Quasi-neutrals in whole electrical domains are injected into the region of the anode wall. The destruction of domains leads to the appearance of plasma channels between the anode and cathode plasma. The transverse electromagnetic waves generated during the nucleation of domains capture charged particles and inject them in a direction that is perpendicular to the insulating longitudinal magnetic field. Plasma turbulence occurs due to charge separation and the generation of electrical domains that create channels between the plasma and the chamber wall, as well as generating fluxes of fast particles.

Single-Carrier, Single-λ Full-Duplex Analog Radio Feed Over a Single-Port RRH Transceiver

The densification of radio access and the massive deployment of radio heads calls for efficient optical fronthaul technologies. The adoption of analogue radio-over-fiber schemes promises greatly simplified equipment that can be distributed at the antenna sites for the purpose of radio signal conditioning and electro-optic conversion. Towards this direction, we propose and experimentally evaluate a full-duplex interface at the intersection between the optical and the radio frequency layer, aiming at bidirectional radio signal transmission over a single wavelength (1577 nm) and a single carrier frequency (5.375 GHz). Analogue coherent optical reception is performed through an electro-absorption modulated laser, which is employed as multi-functional element that accomplishes wavelength re-use for full-duplex radio-over-fiber transmission. The directional split is shifted to the electrical domain through adoption of a crosstalk-cancelling circulation stage, ensuring compatibility with a high dynamic power range for the simultaneous transmission and reception of up- and downlink radio signals, respectively, without the need for further duplexing methods subject to frequency translation or time slotting. We prove that margins of >2% in terms of error vector magnitude can be accomplished for an unpaired spectral configuration, where down- and uplink radio signals share the same spectrum in the optical and electrical domains.

Engineering Application of Nanomaterial and Ferroelectric Domain Polarization to the Dynamic Structure of the Surrounding Rock of Heavy-Duty Railway with Small Clear Intersection Tunnel

With the development of national railways and railways as one of the important channels for heavy-haul transportation, the construction of heavy-haul railways must be a rapid development, which makes it inevitable that the heavy-duty situation of small-distance interchange tunnels will appear. Nanomaterials refer to materials that have at least one dimension in the three-dimensional space in the nanoscale range (1 nm∼100 nm) or are composed of them as basic units. Ferroelectric domain polarization refers to the existence of electric domains in ferroelectrics, electric domains refer to small regions with the same spontaneous polarization direction, and the boundaries between electric domains and electric domains are called domain walls. It is also urgent to study the dynamic structure of the surrounding rocks of heavy-duty railways. This article aims to study the use of nanomaterial and ferroelectric domain technology to improve the overall strength, wear resistance, toughness, and other properties of steel to ensure the safety of the surrounding rock dynamic structure of the heavy-duty railway in the small clearance intersecting tunnel. Moreover, on this basis, this article proposes the method of spraying steel with nanomaterials and the use of ferroelectric domain polarization technology. The strength and wear resistance of steel can be improved under different nanomaterial content and the degree of ferroelectric domain polarization. Sustainability and toughness have been improved, respectively. After the wear resistance experiment and analysis, the experimental results of this article show that the impact resistance of the steel increased by 18.75%. When 0.012% of CeO2 is added, the impact toughness of the steel is increased to the maximum of 3.4 J, an increase of 16.31%, and a 37% increase in wear resistance. Under the premise of ensuring the demand for heavy-duty transportation, the safety performance and sustainability of transportation are greatly improved.

Multiferroic and ferroelectric phases revealed in 2D Ti3C2Tx MXene film for high performance resistive data storage devices

Multiferroic materials, showing simultaneous ferroelectric and ferromagnetic orders, are considered to be promising candidates for future data storage technology however, the multiferroic phenomenon in two-dimensional (2D) materials is rarely observed. We report a simple approach to observe frequency-dependent ferroelectricity and multiferroicity in 2D Ti3C2Tx MXene film at room-temperature. To study the frequency and poling effect on ferroelectricity, we performed electric polarization vs. electric field (P-E) measurement at different frequencies, measured under zero and non-zero static magnetic fields. The results not only indicate a clear frequency dependence of electric domains owing to varying time relaxation during reversal dynamic but also showed magnetic field control of electric polarization thus, confirmed the presence of strong magneto-electric (ME) coupling at room-temperature. The existence of ME coupling was attributed to the coupling between disordered electric dipoles with local spin moments as well reduced dielectric loss after heat-treatment. Moreover, the ferroelectric Ti3C2Tx MXene film was employed as an active layer within the resistive data storage device that showed a stable switching behavior along with improved on/off ratio in comparison to non-ferroelectric Ti3C2Tx active layer. The unique multiferroic behavior along with ferroelectric-tuned data storage devices reported here, will help understand the intrinsic nature of 2D materials and will advance the 2D ferroelectric data storage industry.

Analytical Electro-Thermal Model for Multianode Schottky Diodes With Improved Temperature-Dependent Parameters Extraction Method

An analytical electro-thermal model for multianode Schottky diodes is proposed in this work. By characterizing the self-heating effects, the temperature-dependent parameters including series resistance, ideality factor, and saturation current could be accurately extracted. By means of self-consistent mapping between thermal and electrical domain, the proposed model could eliminate the errors in conventional method, which makes the assumption that each anode operates at the same temperature even at high-junction current levels. This approach is capable of determining highly accurate real-time parameters for diode under different dissipated powers, which is critical for circuit reliability analysis and high-power multiplier design. The proposed electro-thermal model has been applied to analyze a novel four-port balanced tripler, operating up to 220 GHz, with the comparison to two conventional models. With an input power of 350 mW, the circuit efficiency simulated based on this extraction method only features a difference of ~1.1% at 219-GHz measured results.

An Analog EIC-PIC Receiver With Carrier Phase Recovery for Self-Homodyne Coherent DCIs

Coherent techniques, used for high-capacity optical links, conventionally use high-speed ADCs and digital signal processing, which make them power hungry. For short-reach coherent links such as data center interconnects, power consumption, form factor, cost, and latency have to be greatly reduced. Co-designed photonic and electronic integrated circuits, in the optical and electrical analog domains, respectively, can achieve these goals. In this brief, for the first time, we present integration of a silicon photonic integrated coherent receiver (ICR) front-end with an electronic carrier phase recovery chip, as a part of a complete coherent receiver solution. A phase shifter in the ICR (fabricated in a 220 nm silicon-on-insulator technology) receives feedback from the CPR chip, and the combination compensates for the time varying phase offset between the modulated signal and the unmodulated carrier in the closed loop configuration. In this proof-of-concept demonstration, we present experimental results obtained from the stand-alone ICR, and its system level integration with CPR chip, for QPSK signals. The technique can be extended to a higher-order modulation formats, such as 16-QAM, for capacity scaling. The proposed scheme is suitable for carrier-forwarded coherent links, such as polarization multiplexed carrier based self-homodyne links.

Impact Force Analysis in Inertia-Type Piezoelectric Motors

In an inertia-type motor, a piezoelectric multilayer actuator is espoused to a transient vibration velocity as high as 1.0 m/s during slip time. This vibration velocity makes the inertia-type motors dynamic but not quasi-static. We propose a kinetic model to describe the condition under which slippage can occur between a slider and a stator. The transient current absorbed by the multilayer actuators in a stator during slip time defines the slippage behavior of the slider. A new thickness-mode force factor expression (A33), which is a relation between the transient current and the transient vibration velocity, is described in electrical domain. Impact force acting on a friction coupler produced by the actuators in the stator is proportional to the rate of change in the transient current during the sliding time. Additionally, we present the structure and characteristics of a two-phase inertia-drive-type piezoelectric motor, on which the proposed model was evaluated. Driving the multilayer actuators with truncated and mirrored sawtooth signals enhances the system dynamics. As one actuator expands and the other shrinks, their respective hysteretic nonlinearities are canceled. The motor operating frequency can be as great as 30 kHz and typically load characteristics are unloaded velocity greater than 16.0 mm/s and generated force higher than 3.0 N.

Assessment of pre-service physics teachers’ conceptual understanding in electricity and magnetism

This study focused on an assessment of pre-service physics teachers’ conceptual understanding of physics in the domain of electricity and magnetism concepts. The study employed a descriptive survey method of research. The study sample consisted of 100 pre-service physics teachers from five teacher education colleges during the academic year 2021/21. The study used preliminary data from a PhD dissertation that was gathered by administering a conceptual understanding test on electricity and magnetism, which contained 32 items adapted from standardized tests. The data were analyzed using descriptive statistics, one sample t-tests, independent samples t-tests, and one-way ANOVA. The results of the one sample t-test showed that the conceptual understanding test scores for electricity and magnetism were considerably below 50 and 70 which are the national standard pass mark points and the baseline for certification of competency to the teaching profession, respectively. ANOVA analysis revealed that there was a statistically significant mean difference among the pre-service physics teachers in the colleges. The post hoc test analysis showed that there was a statistically significant mean difference between pre-service teachers from two colleges. The independent samples t-test revealed that there was statistically significant mean difference between test scores of males and females in favor of male pre-service physics teachers. In addition, the participation of female candidates was too low compared to their male counterparts. In conclusion, the achievement of pre-service physics teachers was below the expected values; differences among colleges were detected; and there was an achievement and participation imbalance in relation to gender, though consecutive measures were taken. Based on the conclusions, recommendations are given that could be applicable.

Procedural- and Reinforcement-Learning-Based Automation Methods for Analog Integrated Circuit Sizing in the Electrical Design Space

Analog integrated circuit sizing is notoriously difficult to automate due to its complexity and scale; thus, it continues to heavily rely on human expert knowledge. This work presents a machine learning-based design automation methodology comprising pre-defined building blocks such as current mirrors or differential pairs and pre-computed look-up tables for electrical characteristics of primitive devices. Modeling the behavior of primitive devices around the operating point with neural networks combines the speed of equation-based methods with the accuracy of simulation-based approaches and, thereby, brings quality of life improvements for analog circuit designers using the gm/Id method. Extending this procedural automation method for human design experts, we present a fully autonomous sizing approach. Related work shows that the convergence properties of conventional optimization approaches improve significantly when acting in the electrical domain instead of the geometrical domain. We, therefore, formulate the circuit sizing task as a sequential decision-making problem in the alternative electrical design space. Our automation approach is based entirely on reinforcement learning, whereby abstract agents learn efficient design space navigation through interaction and without expert guidance. These agents’ learning behavior and performance are evaluated on circuits of varying complexity and different technologies, showing both the feasibility and portability of the work presented here.

Characterization of high-speed electro-optic phase modulators based on heterodyne carrier mapping at a fixed low-frequency.

A self-referenced method based on heterodyne carrier mapping is proposed to characterize the modulation efficiency of high-speed electro-optic phase modulators (EOPMs). The heterodyne carrier mapping replicates the optical carrier after phase modulation to an electrical replica, which enables observing the power variation of the optical carrier at a fixed low-frequency in the electrical domain. The modulation depths and half-wave voltages within the frequency range of up to 40 GHz are determined by measuring the amplitude ratio of the mapped low-frequency component at 80 MHz in the cases of on and off single-tone modulation of the EOPM. The measured results are compared to those obtained with the traditional optical spectrum analysis method and the electrical spectrum sweep method to check the consistency and accuracy. Surpassing the heterodyne spectrum mapping (HSM) scheme, our method only requires a single-tone driving of the EOPM under test and completely avoids the roll-off responsivity of the photodetector through the fixed low-frequency detection.

Big Data Detection System of Electric Meter Based on LSTM Technology

With the sustained development of power plant of China, the installed base of electric meter grows gradually. It is more and more important to monitor smart meters with their mature use. In order to avoid huge resource wasting and solve the issue because of physical testing of smart meter when smart meter service life time arriving (maximum 8 years), LSTM method related to time series model (TSM) is firstly used to do research on smart meter. Smart meter testing without physical disassembling is realized successfully. Eventually testing abnormity and failure recognition can be obtained through prediction research based on deep learning time series model. Based on electric meter running big data analysis, the electric meter situation including normal and abnormal (error or electricity stealing) and relevant position can be obtained so as to take further action. The research and application of the testing system can avoid physical testing to electric meter. The service time of normal meter can be prolonged by abnormal meters testing. This will lead to saving a lot of resources. The LSTM research method on deep learning is the innovative application in electric power domain.

Programmable photonics for coherent transceivers

AbstractThe implementation of coherent systems in communications involves the post‐processing of the optical transmitted signal after photodetection due to the need to mitigate transmission impairments. This processing is currently performed in the electrical domain using a digital signal processing device (DSP), which increases latency, and costs in the form of power consumption and additional equipment. The use of programmable photonics in coherent systems opens the door to correcting the main transmission impairments in real‐time inside the photonic chip, allowing adaptive processing through time fluctuations.