Voltage Conditions Research Articles

Analysis on effect of hot-carrier-induced degradation of NPT-IGBT

In this paper we present measurement results of hot-carrier-induced degradation of NPT-IGBT under the condition of voltage applied on its collector.The effect of hot carriers on NPT-IGBT is investigated in three ways: stress test measurement according to the gate voltage under the voltage of 400 V applied, TCAD (Tsuprem4 and MEDICI) simulation and electric charge pumping test measurement. The experimental results confirm that the proposed structure of NPT-IGBT has sustainable characteristics and enables the hot-carrier-induced degradation to be effectively optimized in order to guarantee the stability of the device.

Series Voltage Conditioner (SeVC) to Mitigate Commutation Failure in HVDC-LCC Systems

Series Voltage Conditioner (SeVC) to Mitigate Commutation Failure in HVDC-LCC Systems

Effect of current density and operating temperature on degradation of protonic ceramic fuel cells containing BaZr0.8Yb0.2O3-δ electrolyte during long-term operation

Barium zirconate doped with 20 mol% Yb (BaZr0.8Yb0.2O3-δ, BZYb20) is one of the most promising candidates for use as an electrolyte material in protonic ceramic fuel cells (PCFCs) due to its high proton conductivity and high chemical stability under CO2-containing fuel conditions. The long-term durabilities of PCFCs prepared using the BZYb20 electrolyte were evaluated as a function of the current density at 500 and 600 °C over a period of 1000 h. At 600 °C, the internal resistance of the cell increased even under open circuit voltage (OCV) condition. Comparing the voltage lowering rates at a current density of 0.172 A cm−2 based on the current density–voltage curves recorded during the durability tests, rates of 3.0, 5.3, and 9.0%/1000 h were achieved at the OCV, 0.047, and 0.172 A cm−2, respectively. A small amount of Ni elements diffused into the electrolyte from the anode to the cathode side, resulting in the formation of cumulus cloud shapes that corresponded to Ni element segregation at the grain boundaries in the electrolyte layer after long-term durability testing at 0.172 A cm−2. At current densities of 0.047–0.048 A cm−2, the voltage lowering rate at 500 °C was higher than that at 600 °C, with values of 6.0 and 2.6%/1000 h being recorded, respectively. This effect may be due to the higher resistance of the cell at 500 °C compared to that at 600 °C.

Effects of voltage stress conditions on degradation of iridium-based catalysts occurring during high-frequency operation of PEM water electrolysis

Proton exchange membrane water electrolysis (PEMWE) is needed to store renewable energy in the form of hydrogen. To improve the performance of PEMWE, elucidating the degradation mechanism of iridium (Ir)-based catalysts used for oxygen evolution reaction (OER) that is a rate-determining step is important. To date, it is known that one important reason for that is undesirable change in crystal structure of Ir. To further evaluate its degradation mechanism, in this study, effects of operating voltage conditions on crystal structure of Ir are investigated because the voltage conditions can accelerate changes in crystal structure of Ir. Especially how Ir was changed into an unfavorable metallic form was analyzed. PEMWE single cells under conditions of (i) a constant voltage of 1.9 V, (ii) a voltage cycle of 1.7–1.9 V, then a constant voltage of 1.9 V, and (iii) an applied voltage cycle with open circuit voltage (OCV). In the OCV condition, the crystalline structure of Ir was irreversibly transformed into a metallic form. This transformation induced lower OER activity than other crystalline states of Ir, followed by lower performance of PEMWE single cells. These findings help to establish baseline protocols for the stable operation of PEMWEs using Ir-based catalysts.

Investigation of Operational Parameters for Nanoelectrokinetic Purification and Preconcentration.

This work reports on experimental investigations into the operational parameters of nanoelectrokinetic purification and preconcentration, especially utilizing on ion concentration polarization (ICP). ICP as a nanoscale electrokinetic phenomenon has demonstrated promising advances in various fields utilizing an ion depletion zone (IDZ) with a steep electric field gradient inside the ICP layer. However, the inevitable electrokinetic instability occurring within the IDZ has posed a challenge in operating the ICP system stably. To address the need for a stable and efficient ICP operation in various devices and applications, we propose an operational strategy along with conducted research to determine optimal operating ranges. In order to investigate the operational parameters, a unit voltage (VTH) is introduced as the threshold for initiating ICP. We examined the applicability of VTH across various operating ranges to ensure its effectiveness and versatility. In ICP purification, we categorize three modes (steady, burst, and unsteady) based on IDZ expansion and stability under varying VTH and flow rate conditions, presenting optimal operational conditions that minimize the voltage margin. In ICP preconcentration, a systematic investigation is conducted to observe the influence of background electrolyte concentration and voltage conditions on preconcentration efficiency, offering insights into the correlation between preconcentration factor, electrical conditions, and preconcentration time. Therefore, this research would contribute to the practical understanding of nanoelectrokinetics, providing insight into experimental designs. These findings are expected to offer valuable guidance to researchers aiming to utilize ICP's potential across a spectrum of applications, from purification to preconcentration, in the realm of micro/nanofluidic systems.

An Ultra-Low-Voltage Approach to Accurately Set the Quiescent Current of Digital Standard Cells Used for Analog Design and Its Application on an Inverter-Based Operational Transconductance Amplifier

An approach to design analog building blocks based on digital standard cells is presented in this work. By ensuring that every CMOS inverter from a standard-cell library operates with a well-defined quiescent current and output voltage, the suggested method makes it possible to construct analog circuits that are resistant against PVT variations. The method uses the local supply voltages connected to the source terminals of the p-channel and n-channel MOS transistors of the standard-cell inverters as control inputs. It is based on adaptive supply voltage generator (ASVG) reusable blocks, which are comparable to those used in digital applications to handle process variations. All of the standard-cell inverters used for analog functions receive the local supply voltages produced by the ASVGs, which enable setting each cell’s quiescent current to a multiple of a reference current and each cell’s static output voltage to an appropriate reference voltage. Both the complete custom design of the ASVG blocks and a theoretical study of the feedback loop of the ASVG are presented. An application example through the design of a fully synthesizable two-stage operational transconductance amplifier (OTA) is also provided. The TSMC 180 nm CMOS technology has been used to implement both the OTA and the ASV generators. Simulation results have demonstrated that the proposed approach allows to accurately set the quiescent current of standard-cell inverters, dramatically reducing the effect of PVT variations on the pmain performance parameters of the standard-cell-based two-stage OTA.

Charge Trapping and Emission during Bias Temperature Stressing of Schottky Gate GaN-on-Silicon HEMT Structures Targeting RF/mm Wave Power Amplifiers.

For operation as power amplifiers in RF applications, high electron mobility transistor (HEMT) structures are subjected to a range of bias conditions, applied at both the gate and drain terminals, as the device is biased from the OFF- to ON-state conditions. The stability of the device threshold voltage (Vt) condition is imperative from a circuit-design perspective and is the focus of this study, where stresses in both the ON and OFF states are explored. We see rapid positive threshold voltage increases under negative bias stress and subsequent recovery (i.e., Vt reduces), whereas conversely, we see a negative Vt shift under positive stress and Vt increase during the subsequent relaxation phase. These effects are correlated with the thickness of the GaN layer and ultimately result from the deep carbon-acceptor levels in the C-GaN back barrier incorporated to screen the buffer between the silicon substrate and the epitaxially grown GaN layer. Methods to mitigate this effect are explored, and the consequences are discussed.

Assessing Voltage Stability in Distribution Networks: A Methodology Considering Correlation among Stochastic Variables

Distributed photovoltaic (PV) output exhibits strong stochasticity and weak adjustability. After being integrated with the network, its interaction with stochastic loads increases the difficulty of assessing the distribution network’s static voltage stability (SVS). In response to this issue, this article presents a probabilistic assessment method for SVS in a distribution network with distributed PV that considers the bilateral uncertainties and correlations on the source and load sides. The probabilistic models for the uncertain variables are established, with the correlation between stochastic variables described using the Copula function. The three-point estimate method (3PEM) based on the Nataf transformation is used to generate correlated samples. Continuous power flow (CPF) calculations are then performed on these samples to obtain the system’s critical voltage stability state. The distribution curves of critical voltage and load margin index (LMI) are fitted using Cornish-Fisher series. Finally, the utility function is introduced to establish the degree of risk of voltage instability under different scenarios, and the SVS assessment of the distribution network is completed. The IEEE 33-node distribution system is utilized to test the method presented, and the results across various scenarios highlight the method’s effectiveness.

Derating factor determination of the three‐phase induction motor under unbalanced voltage using pumping system

AbstractA novel method is presented for determining the derating factors of a three‐phase induction motor under the condition of the unbalanced supply voltages. In this method, a mechanical system is used which consist of the a centrifugal pump, two valves, a DC motor, which are connected to the shaft of the three‐phase induction motor. A sliding mode control system is used for position control of the DC motor for adjusting the valve angle for derating the induction motor. The authors present the results of an experiment in which a three‐phase induction motor was subjected to various unbalanced voltage conditions. The results of simulations were used to look into what happened when there were different levels of imbalanced voltage. This was done to determine how these situations changed an induction motor's speed, torque, and efficiency. For this system, the stator current would be greater than the rated current if there was an imbalance in the supply voltage. Therefore, to reduce the amount of power that the three‐phase induction motor can produce, the control system uses a DC motor to reduce the angle of one of the two valves. This decreasing angle continues until the root mean square value of the stator current returns to the rated current. At this point, the derating factor may be calculated by dividing the output power of the three‐phase induction motor in the unbalanced condition by the output power when there are ideal sinusoidal. The MATLAB SIMULINK environment is utilised to perform simulations of the proposed system.

Analysis of Improvements to Bank Capacitor Requirements in 20kv Voltage Distribution Network Panels for Power Plant 2 at PT. Toyota Motor Manufacturing Indonesia

This research aims to describe and analyze the effectiveness of using capacitor bank capacity in PT's power plant 2 distribution system. TMMIN. The focus is to analyze the initial design of capacitor bank requirements for each panel in the substation production line, including Painting, Assembly and Welding, to increase capacitor bank requirements according to electrical theory standards. The Power Factor calculation method is used to measure the required capacitor bank capacity. The power factor is influenced by the type of electrical load which is resistive, inductive or capacitive, with a value range between 0 and 1. A power factor close to 1 indicates high active power and better electrical power quality, while a power factor close to 0 indicates high reactive power. reducing power quality and increasing electrical energy use. The current power factor value is obtained from the actual voltage and active power conditions, and the required capacitor bank value is calculated with a target power factor of 0.9 or 0.95. According to calculations, the panels that can be repaired are panels 3, 4, 5, 6 Painting, panel 1 Assembly, and panel 1 Welding. The results show that 2 MDB panels reach ideal conditions with 6 steps of 2x50kVAR capacitor bank, while the other 6 MDB panels require an additional 2 steps of 2x50kVAR capacitor bank to achieve ideal conditions.

Data-dependent half-select free GSRAM cell with word line write-assist and built-in read buffer schemes for use in PUFs-based IoT devices

In this study, a static-RAM cell using the Gnr-GDI method is proposed as a weak-type physical unclonable function (PUF) circuit to generate a unique and stable binary output for secure IoT devices. Regarding the memory level, a suitable combination of dynamic body bias, stacked networks, and multi-Vth techniques has been used in the architecture of asymmetric cell-structure inverters as a latch section to reduce power consumption and improve hardware efficiency. In addition, the logic styles of virtual ground and power gating based on word and BL data lines and a tri-state buffer structure have been used to extend the write VTC and improve read stability, respectively. From the perspective of PUF performance, the body of the latch section can form skewed VTCs based on the setting of critical parameters in GnrFET technology to achieve an efficient PUF circuit design.At the memory performance level, the Monte Carlo (MC) method-based results confirm the reasonable performance of the proposed structure in terms of static noise margin (SNM) and hardware efficiency, such as 53 % delay and 72 % energy-delay product (EDP) parameters, compared with the 6 T SRAM structure in a similar 16 nm GnrFET technology. In addition, in terms of the performance as a PUF circuit, the simulation results demonstrate the superiority of the proposed cell in terms of energy consumption, BER, response time, uniqueness, and stability under non-technological variation conditions of temperature and supply voltage. The outstanding performance results of the figure of merits (FoMs), CEQM, and UR2, which are composed of variability, energy, reliability, and layout-level factors, indicate the suitability of the proposed memory architecture for use in both the memory and PUF modes.Furthermore, to investigate the application level, memory structure has been used to store fingerprint images as PUF data using a hardware algorithm. The results of the proposed comprehensive FoM, which is based on the simultaneous consideration of circuit level and quality parameters, indicate that the proposed memory scheme in a bit-interleaved architecture-compatible design can be introduced as a high-performance candidate for generating and storing unique binary data in PUF-based IoT platforms.

Self-rectifying NiOX/WOX heterojunction synaptic memristor for crossbar architectured reservoir computing system

In this study, we examine an ITO/NiOX/WOX/Pt p-n heterojunction memristor for neuromorphic applications as a synaptic crossbar array. The transition in the depletion region at the interface between p-type NiOX and n-type WOX crucially influences the self-rectifying characteristics of the device depending on the voltage polarity. Furthermore, long- and short-term memory coexist depending on the switching voltage condition, thus enabling various neuromorphic applications, such as reservoir computing and the use of the synaptic device at the off-chip trained network. The reliable operational characteristics are confirmed by obtaining an average memory window (>9) and rectification ratio (>58) between device-to-device and cycle-to-cycle. Furthermore, synaptic functions were successfully implemented, such as spike-rate-dependent plasticity, spike-number-dependent plasticity, paired-pulse facilitation, post-tetanic potentiation, paired-pulse depression, and post-tetanic depression, in conjunction with repeatability. Ultimately, reservoir computing is accomplished based on the I–V nonlinearity and short-term memory characteristics. A high pattern recognition rate (>96.2 %) is achieved in MNIST tasks using 16 reservoir states, thus affirming the trustworthiness of the reservoir computing system. With its comprehensive approach to synaptic applications for neuromorphic computing systems, the heterojunction device highlights its considerable potential to advance artificial neural networks in conjunction with novel memristor technology directions.

Evaluation of cobalt removal from polycrystalline diamond compact in the coupling mechanism of acid leaching and electrolysis

Polycrystalline diamond compact (PDC) is a widely used superhard material, and its thermal stability and wear resistance are the main factors determining its performance. The residual cobalt binder content in polycrystalline diamond (PCD) has a significant impact on the thermal stability and wear resistance of PDC. Therefore, cobalt removal treatment is required to improve the performance of PDC. The current cobalt removal methods mainly include acid leaching and electrolysis. This study proposes a novel coupling method that combines acid leaching and electrolysis for cobalt removal. Cobalt removal was conducted for 10 h under the conditions of electrolytic voltage of 12 V, direct current power supply current of 0.01 A, and sulfuric acid electrolyte concentration of 9.2 mol/L. The cobalt removal effect was evaluated using scanning electron microscopy (SEM), energy-dispersive spectroscopy (EDS), and X-ray diffraction (XRD). The hardness and elastic modulus of PDC before and after cobalt removal were measured using nanoindentation experiments. The results indicate that the coupled electrolysis process effectively removes the cobalt phase in the PCD layer while retaining the WC phase. The hardness and elastic modulus of PDC decrease after the removal of cobalt binder, and the cobalt removal depth can reach 807 μm.

Semantic Web-Based Energy-Efficient Design of Dual-Mode Vehicles Based on Deep Neural Networks

Dual-Mode Vehicles (DMVs) represent a new and sustainable solution to the problems of urban mobility, and energy consumption. This proposed work of a DMV can operate without a conventional battery. Instead, it uses a combination of energy management technology, renewable energy systems, and other energy sources to ensure continuous operation. The efficiency and the working statistics of such DMV could also be sufficiently monitored through semantic techniques. The user can freely choose the type of working of the vehicle based on the current inputs given by the users. These semantics serve a crucial role in establishing a reference model for seamless data exchange between the trained Bald Eagle Search (BES) algorithm and the deep neural network (DNN). This proposed work has been implemented and the performance has been analyzed concerning the State Of Charging (SOC), generator voltage, and DC-DC converter voltage. The proposed work yields higher SOC and voltage than other existing schemes.

Mechanisms of stationary voltage fluctuation in the neuromuscular junction endplate and corresponding denoising paradigms.

The neuromuscular junction (NMJ) has an elaborate anatomy to ensure agile and accurate signal transmission. Based on our formerly obtained expressions of the thermal and conductance induced voltage fluctuations, in this paper, the mechanisms underlying the conductance-induced voltage fluctuation are characterized from two aspects: the scaling laws with respect to either of the two system-size factors, the number of receptors or the membrane area; and the "seesaw effect" with respect to the intensive parameter, the concentration of acetylcholine. According to these mechanisms, several aspects of the NMJ anatomy are explained from a denoising perspective. Finally, the power spectra of the two types of voltage fluctuations are characterized by their specific scaling laws, based on which we explain why the endplate noise has the low-frequency property that is described by the term "seashell sound".

Mechanisms and controlling factors of heavy metals removal by electroflocculation in estuarine environments

Estuaries play a crucial role in preventing the influx of metals from rivers into seas, thereby offering potential insights for the water purification industry. This study seeks to identify the key parameters (including pH, electricity conductivity (EC), and Eh) influencing the removal efficiency of Mn, Zn, Cu, Co, and Ni during natural and electro-flocculation processes in the Siahroud River estuary. The experiments were conducted in three stages, each representing varying salinity levels and voltage conditions, to determine the most effective parameters for metal removal. The findings revealed that heavy metal flocculation rates were highest at lower salinities (0.5 to 1.5 PSU), with no significant improvement in contaminant removal observed with increasing voltage. Electro-flocculation efficiency was found to be more dependent on Eh. Overall, the flocculation processes reduced the annual total dissolved metal content from 14.84 to 6.46 tons, underscoring the potential of this method in water quality management.

Multivariate signal-to-noise ratio as a metric for characterizing spectral computed tomography

Objective. With the introduction of spectral CT techniques into the clinic, the imaging capacities of CT were expanded to multiple energy levels. Due to a variety of factors, the acquired signal in spectral CT datasets is shared between these images. Conventional image quality metrics assume independence between images which is not preserved within spectral CT datasets, limiting their utility for characterizing energy selective images. The purpose of this work was to develop a metrology to characterize energy selective images by incorporating the shared information between images within a spectral CT dataset. Approach. The signal-to-noise ratio (SNR) was extended into a multivariate space where each image within a spectral CT dataset was treated as a separate information channel. The general definition was applied to the specific case of contrast to define a multivariate contrast-to-noise ratio (CNR). The matrix contained two types of terms: a conventional CNR term which characterized image quality within each image in the spectral CT dataset and covariance weighted CNR (Covar-CNR) which characterized the contrast in each image relative to the covariance between images. Experimental data from an investigational photon-counting CT scanner was used to demonstrate the insight of this metrology. A cylindrical water phantom containing vials of iodine and gadolinium (2, 4, and 8 mg ml−1) was imaged under conditions of variable tube current, tube voltage, and energy threshold. Two image series (threshold and bin images) containing two images each were defined based upon the contribution of photons to reconstructed images. Analysis of variance (ANOVA) was calculated between CNR terms and image acquisition variables. A multivariate regression was then fitted to experimental data. Main Results. Image type had a major difference on how Covar-CNR values were distributed. Bin images had a slightly higher mean and wider standard deviation (Covar-CNRlo: 3.38 ±17.25, Covar-CNRhi: 5.77 ± 30.64) compared to threshold images (Covar-CNRlo: 2.08 ±1.89, Covar-CNRhi: 3.45 ± 2.49) across all conditions. ANOVA found that each acquisition variable had a significant relationship with both Covar-CNR terms. The multivariate regression model suggested that material concentration had the largest impact on all CNR terms. Signficance. In this work, we described a theoretical framework to extend the SNR to a multivariate form that is able to characterize images independently and also provide insight regarding the relationship between images. Experimental data was used to demonstrate the insight that this metrology provides about image formation factors in spectral CT.

In Situ and Continuous Decoding Hydrogen Generation in Solar Water-Splitting Cells.

Photoelectrochemical (PEC) water splitting is gaining recognition as an effective method for producing green hydrogen. However, the absence of in situ, continuous decoding hydrogen generation tools hampers a detailed understanding of the physics and chemistry involved in hydrogen generation within PEC systems. In this article, we present a quantitative, spatiotemporally resolved optical sensor employing a fiber Bragg grating (FBG) to probe hydrogen formation and temperature characteristics in the PEC system. Demonstrating this principle, we observed hydrogen formation and temperature changes in a novel cappuccino cell using a BiVO4/TiO2 photoanode and a Cu2O/CuO/TiO2 photocathode. Our findings demonstrate that FBG sensors can probe dynamic hydrogen formation at 0.5 s temporal resolution; these sensors are capable of detecting hydrogen concentrations as low as 0.6 mM. We conducted in situ and continuous monitoring of hydrogen and temperature to ascertain various parameters: the rate of hydrogen production at the photocathode surface, the time to reach hydrogen saturation, the distribution of hydrogen and temperature, and the rate of hydrogen transfer in the electrolyte under both external bias and unbiased voltage conditions. These results contribute valuable insights into the design and optimization of PEC water-splitting devices, advancing the in situ comprehensive monitoring of PEC water-splitting processes.

Quantitative assessment of static voltage stability for power system with high-penetration wind power based on energy function

As the scale of power systems expands, the penetration of renewable energy sources and power electronic devices are accelerating. With the growing complexity of power system, there is an urgent need for in-depth research on the impact of reactive power on static voltage stability. This paper proposes a quantitative assessment approach of static voltage stability for the power system with high-penetration wind power based on the energy function. A quantitative assessment framework for voltage stability indices based on power flow analysis has been established. The classic static voltage stability index L based on reactive power has been comprehensively analyzed. Additionally, combining the energy function and power flow analysis, a new quantitative index for voltage stability based on bus reactive power injection has been proposed. Finally, the effectiveness of this index has been validated by case studies. With the increasing penetration of wind power, the trend of the change of the assessment index of voltage margin is analyzed.

Empirical design and comprehensive analysis of multiport converter in distributed generation enabled microgrids

Distributed generation-enabled microgrids are a revolutionary approach for the energy paradigms that will transform the ways of generation, distribution, and utilization. A decentralized approach to energy generation in microgrids results in the robustness and independence of energy networks. Empowerment of the communities to take control of energy requirements with multiport converter-based microgrids promotes sustainability, efficiency, reduced losses, and increased resilience against the evolving trends of the energy sector. In this research, a hybrid energy-integrated multiport converter is designed and analyzed under its various modes of operation. Rapid transitions from one energy source to another are attained within 0.4μs to feed the load at a steady state voltage of 400 V, and within 0.15μs to charge the energy storage system at a steady state voltage of 48 V which indicates the robustness and independence of energy systems via this proposed approach. The resilience of the microgrid is obtained because of this rapid trans Moreover, the proposed converter offers a voltage gain of 8.3 with 96 % efficiency making it sustainable for maximization of renewable energy. In addition, the resilience of the proposed converter is exhibited through high power densities at power losses of not more than 7.5 % making it an innovative candidate for hybrid energy systems as compared to existing technologies. Simulation scenarios are validated through mathematical analysis, proving their effectiveness in distributed generation-enabled microgrids. The proposed research model is effective in a real environment because of the minimal effects of parasitic resistance, reduced total harmonic distortion under different loads, and negligible electromagnetic interferences, demonstrated through simulations.