Electrical Stress Research Articles

Investigating the Impact of Hardness on Dielectric Breakdown Characteristics of Polyurethane.

Polymeric materials play a vital role in high-voltage insulation, but their insulating properties can deteriorate over time, leading to insulation failures. The presence of voids resulting from manufacturing defects or external stresses can create a highly divergent field, further contributing to this issue. However, certain polymers, such as polyurethane (PU), possess self-healing properties that enable them to repair these voids and restore a uniform electric field distribution, thereby ensuring the reliability of the insulation. Surprisingly, the potential of PU as an insulating material in high-voltage applications remains unexplored. However, the self-healing capability of PU decreases with an increase in the hardness of the material. Therefore, in this study, the dielectric breakdown properties of PU with different levels of hardness, rated on the Shore scale as 40° (soft), 70° (medium), and 90° (hard), were investigated. The AC and DC dielectric breakdown characteristics of these PU variants and dielectric spectra were examined. Additionally, the study explores the relationship between the dielectric properties and the hardness of the material. Our findings revealed that the dielectric breakdown strength of PU increases as the material's hardness is increased under both AC and DC electric stress. However, this may come at the cost of reduced self-healing capabilities of PU. Therefore, there is a need to balance the hardness of the material with its ability to recover from breakdown events. The findings from this study can be useful for researchers and engineers, as they offer valuable insights into the dielectric properties of PU at various hardness levels.

37‐4: Degradation Analysis on Li‐doped Organic Charge Generation Layer

Understanding degradation of charge generation layer (CGL) is uprising issue for efficient and stable tandem devices. Here, we explored how the electrical characteristics of Li‐doped CGL device change according to different stress conditions comprehensively and found out thermal stress affects more severely than electrical stress via capacitance‐voltage and temperature‐dependent current density‐voltage measurements. The exponential trap distribution model analysis and Poisson and drift‐diffusion simulation informed that the degradation of electrical properties is attributed to Li diffusion and actual thermal diffusion of Li was experimentally observed by XPS depth

P‐2: Investigation of high mobility crystalline IGO TFT with top‐gate structure for LCD display application

The present paper reports the study of electrical characteristics and bias temperature stress (BT) stability of crystalline Indium‐Gallium oxide (IGO) dual‐gate thin film transistor (TFT) with top‐gate structure. TFT with normalized Ion over 100εA and PBTS/NBTIS of 0.35/‐2.85V was successfully fabricated. By adjusting oxygen partial pressure (O2%) and substrate temperature, we can control the wet etching rate (WER) of as‐deposited IGO film. After post annealing, crystalline IGO containing In2O3 phase with preferred orientation of (222) has been formed. The TFT characteristics uniformity and BT stability were found to depend on parameters of gate insulator (GI) deposition and pre‐treatment before GI. Based on experimental results, we propose high GI deposition temperature associated with low N2O plasma treatment power as the optimal condition for industrial production of crystalline IGO TFT.

Studies on temperature dependent dielectric properties of some insulators down to liquid helium temperatures

The work discusses on the behavior of dielectric properties of various commercially available insulators with respect to temperature (4.2 K to 300 K) and operating frequency range of 2.52 KHz to 500 KHz. A conventional parallel plate-based capacitor setup was designed and developed considering various conditions. The dielectric constant was found to be very dependent on the pre-breakdown partial discharges at low temperatures. At 4.2 K the discharges move far away from the electrodes and exert high electric stress on the sample under test, which results in the breakdown or the decrease in the dielectric strength. The relative permittivity (ϵr) also decreased rapidly with the increase in frequency in most of the samples, this decrease is due to the reduction of space charge polarization effect. The correlation between the dielectric properties, operating frequencies and temperature have been studied in detailed.

Mitigation of Electrical Stresses on Outdoor Polymeric Insulator Using Nano-Zinc Oxide Coating: Simulation and Experimental Validation

Mitigation of Electrical Stresses on Outdoor Polymeric Insulator Using Nano-Zinc Oxide Coating: Simulation and Experimental Validation

A Comparative Analysis of Support Vector Machine and Decision Tree Algorithm for Predicting Fault in Uninterruptible Power Supply Systems

Power supply systems can have problems, and Ghana Gas Limited is not an exception. Ghana Gas Limited uses an intricate Uninterruptible Power Supply (UPS) system which is made up of several parts such as electromechanical components, PCB boards, and electrolytic capacitors. The majority of components have technical lifespans that are governed by usage, operational environment, and working conditions, such as electrical stress, working hours, and working cycles. Most of the time, these errors affect the integrity and power supply after manufacture. The issue is that it takes longer for the professionals who operate on this machine to recognize these flaws, which makes it difficult for them to predict errors quickly or anticipate the likelihood of faults happening in the system components at an early stage for effective corrective action to be performed. Support vector machines (SVM) and decision trees were used in this study to anticipate faults for technical data scheduling of uninterruptible power supply systems for Ghana Gas Limited in an efficient manner. Based on a comparative analysis using these two techniques, faults in Ghana Gas Limited's power supply system were predicted using a four-hour daily interval dataset on UPS recordings, including input voltage, battery voltage, battery current, and alarm, spanning from August 2017 to October 2023. The findings depicted that the support vector machine was more efficient in detecting the fault locations in the power supply system with an accuracy of 96.80%, recall of 99.80%, precision of 100 %, F1-score of 93.15%. The results from the error metrics also validate the measures in assessing the predictive ability of the model with MAE of 0.42%, MSE of 1.18%, RMSE of 4.45%, R2 of 99.97%, RMSLE of 0.036%, and MAPE of 0.21%.

Optimizing Capacitive Pressure Sensor Geometry: A Design of Experiments Approach with a Computer-Generated Model.

This study presents a comprehensive investigation into the design and optimization of capacitive pressure sensors (CPSs) for their integration into capacitive touch buttons in electronic applications. Using the Finite Element Method (FEM), various geometries of dielectric layers were meticulously modeled and analyzed for their capacitive and sensitivity parameters. The flexible elastomer polydimethylsiloxane (PDMS) is used as a diaphragm, and polyvinylidene fluoride (PVDF) is a flexible material that acts as a dielectric medium. The Design of Experiment (DoE) techniques, aided by statistical analysis, were employed to identify the optimal geometric shapes of the CPS model. From the prediction using the DoE approach, it is observed that the cylindrical-shaped dielectric medium has better sensitivity. Using this optimal configuration, the CPS was further examined across a range of dielectric layer thicknesses to determine the capacitance, stored electrical energy, displacement, and stress levels at uniform pressures ranging from 0 to 200 kPa. Employing a 0.1 mm dielectric layer thickness yields heightened sensitivity and capacitance values, which is consistent with theoretical efforts. At a pressure of 200 kPa, the sensor achieves a maximum capacitance of 33.3 pF, with a total stored electric energy of 15.9 × 10-12 J and 0.468 pF/Pa of sensitivity for 0.1 dielectric thickness. These findings underscore the efficacy of the proposed CPS model for integration into capacitive touch buttons in electronic devices and e-skin applications, thereby offering promising advancements in sensor technology.

Evaluation of Strain Sensors Based on Poly(acrylonitrile-co-butadiene) and Polypyrrole Synthesized by the Diffusion Method.

In this study, the functionality of an elastomer composite material containing polypyrrole (PPy) as a stress sensor was evaluated. The material was prepared using the swelling method by diffusing the pyrrole monomer into the elastomer before polymerization. To achieve adequate diffusion, organic solvents with affinity for the elastomer were used. The resulting materials were characterized by scanning electron microscopy (SEM), surface electrical resistance, and thermal and mechanical properties for application as a stress sensor. The simultaneous change in electrical resistance and tension stress was measured using a digital multimeter with electrodes connected to the jaws of a universal mechanical testing machine. The influence of stress cycles on the piezoresistivity of the composite materials was investigated. The obtained PPy/NBR composite presented a good combination of electrical conductivity and mechanical properties. The strain at break remained with mild variation after coating with PPy.

Considering Joule heating in coupled electroporation and electrodeformation modeling of glioblastoma cells

Cells exposed to a pulsed electric field undergo electroporation(EP) and electrodeformation(ED) under electric field stress, and a coupled model of EP and ED of glioblastoma(GBM) taking into account Joule heating is proposed. The model geometry is extracted from real cell boundaries, and the effects of Joule heating-induced temperature rise on the EP and ED processes are considered. The results show that the temperature rise will increase the cell's local conductivity, leading to a decrease in the transmembrane potential(TMP). The temperature rise also causes a decrease in the dynamic Young's modulus of the cell membrane, making the cell less resistant to deformation. In addition, GBM cells are more susceptible to EP in the middle portion of the cell and ED in the three tentacle portions under pulsed electric fields, and the cells undergo significant positional shifts. The ED of the nucleus is similar to spherical cells, but the degree of ED is smaller.

Optimizing Insulated-Gate Bipolar Transistors’ Lifetime Estimation: A Critical Evaluation of Lifetime Model Adjustments Based on Power Cycling Tests

This paper presents a detailed refinement and validation of two well-known lifetime prediction models for IGBTs, namely CIPS08 and SKiM63, using experimental power cycling test data. This study focuses on adapting these models to reflect the operational conditions and degradation patterns to more accurately fit different IGBT types and applications. Key modifications include recalibrating the scale factor and temperature coefficients in the SKiM63 model and refining the CIPS08 model coefficients (β1 = −2.910, β2 = 1083.714, β3 = −4.521) based on the impact of temperature fluctuations, bond wire diameter, and electrical stresses observed during power cycling tests. These adjustments provide a significant shift from traditional values, with the recalibrated models offering a better fit, as evidenced by a reasonable coefficient of determination (R2) and root mean square error (RMSE). Utilizing Monte Carlo simulations with a 5% uncertainty, the study calculates the B10 lifetimes of PV inverters, demonstrating a substantial reduction from 43 years in the unmodified model to 13 years in the modified model. This emphasizes the critical need for ongoing modification and validation of predictive models based on the actual operational data to enhance the reliability and efficiency of IGBTs in power electronic systems.

Stable interphase inducer based on montmorillonite clay mineral to enhance stability and fire safety for lithium metal batteries

Heat buildup from factors like mechanical, electrical, or thermal stress is the main safety issue in lithium metal batteries (LMBs). Even without such stressors, however, LMBs may remain fire-prone because of the development of unstable electrode–electrolyte interphase on charge–discharge, potentially leading to internal short circuits. In this study, a stable cathode-electrolyte interphase inducer (SCEI-I) is proposed to tackle both the cycling stability issue and safety concerns. SCEI-I is synthesized by incorporating montmorillonite, a clay mineral, and methylphosphonic acid dimethyl ester, a flame-retardant material, onto a porous polyethylene film. On cycling, SCEI-I can induce a thin (<8 nm), uniform and robust cathode-electrolyte interphase layer, contributing to a steady and high Coulombic efficiency of 99.6%–99.8% with decreased impedance. SCE-I improves electrochemical performance by reducing the capacity degradation from ∼21.9% to ∼8.9% after 100 cycles. SCE-I also demonstrates strong thermal stability as the endothermic energy of SCEI-I is only –32.4 J/g (24 °C–280 °C), which is less than one-third of that of polypropylene separator (–118.9 J/g). Furthermore, when exposed to fire, the SCEI-I membrane instantly extinguished flames by disrupting combustion chain reaction. The present study proposes an interfacial engineering approach to improve the stability and safety of LMBs.

Fault Detection and Normal Operating Condition in Power Transformers via Pattern Recognition Artificial Neural Network

Aging, degradation, or damage to internal insulation materials often contribute to transformer failures. Furthermore, combustible gases can be produced when these insulation materials experience thermal or electrical stresses. This paper presents an artificial neural network for pattern recognition (PRN) to classify the operating conditions of power transformers (normal, thermal faults, and electrical faults) depending on the combustible gases present in them. Two network configurations were presented, one with five and the other with ten neurons in the hidden layer. The main advantage of applying this model through artificial neural networks is its ability to capture the nonlinear characteristics of the samples under study, thus avoiding the need for iterative procedures. The effectiveness and applicability of the proposed methodology were evaluated on 815 real data samples. Based on the results, the PRN performed well in both training and validation (for samples that were not part of the training), with a mean squared error (MSE) close to expected (0.001). The network was able to classify the samples with a 98% accuracy rate of the 815 samples presented and with 100% accuracy in validation, showing that the methodology developed is capable of acting as a tool for diagnosing the operability of power transformers.

Experiment of electrothermal stress for different types of end turn grading in the inverter‐fed form‐wound windings

AbstractEnd turn grading with resistive–capacitive coupling experiences severe electrothermal stress when subjected to pulse width modulation (PWM) voltage. In this paper, several experiments and simulations were carried conducted for four types of end turn grading. First of all, the temperature rise in the end turn grading increased with a decrease in rise time. When the rise time was less than 500 ns, the temperature rise at the terminal was higher owing to the increased capacitive current coupled from the main wall insulation. Further, the current in the linear region exhibited minimal variation at different fundamental frequencies resulting in synchronized the temperature rise at the terminal and overlap. Furthermore, the jump voltage was the key factor influencing temperature rise in end turn grading, confirmed by comparing different voltage magnitudes. Finally, the transient behaviour of the maximum field in the stress grading material was determined at rise time. The experimental and simulation results indicate that balancing and interdependently addressing the electrical and thermal stress protection in end turn grading is crucial. The study aims to provide an experimental and theoretical foundation for an insulation system of inverter‐fed rotating machinery operating under PWM voltage.

Degradation of superhydrophobic aluminium overhead line conductor surfaces

AbstractIt has been shown that noise emissions from HV overhead line conductors can be reduced under rain conditions by making their surfaces superhydrophobic. The working environment makes ensuring the longevity of any treatment a major challenge. The degradation of various superhydrophobic surfaces generated by applying a superhydrophobic coating and patterning microscale channels is assessed under an AC electric field (18 kV/cm) with continuous water spray. By examining the droplet distribution on the surfaces during the degradation and the surface roughness before and after degradation, the authors demonstrate that no water droplets were found on the microscale patterned surface, but droplets were formed on the coated surface after degradation. The surface roughness reduction of the coated surface and microscale patterned surface was 29.8% and 11.3%, respectively, indicating that the microscale patterned surface has better durability than the superhydrophobic coating under the AC electric stress.

Deterioration of Li-doped phenanthroline-based charge generation layer for tandem organic light-emitting diodes

Understanding the deterioration of the charge generation layer (CGL) is an uprising issue for efficient and stable tandem organic light-emitting diodes. Here, we comprehensively investigated the change in the electrical characteristics of Li-doped CGLs according to different stress conditions and compared the stability of Li diffusion in two phenanthroline-based electron transport materials. Through current density–voltage and capacitance-frequency measurements, it was revealed that electrical stress and thermal stress affect CGL’s electrical properties differently. Moreover, the exponential trap distribution model analysis informed that the Li diffusion is expedited toward narrowing depletion width in the CGL. Diffusion of Li and thermal effect to the diffusion was experimentally observed by X-ray photoelectron spectroscopy (XPS) depth profiling. We also evaluated variations in the operating voltage of tandem devices that differed only in nCGL. Overall, Li diffusion occurs more favorably in sparse Bphen film with weak binding energy rather than closely packed BPPB film with strong binding energy, which highlights that atomic geometry and morphological characteristics are crucial for the stability of tandem devices.

Experimental and Simulation Studies on Stable Polarity Reversal in Aged HVDC Mass-Impregnated Cables

Mass-impregnated (MI) cables have been used for many years as cables in high-voltage direct current (HVDC) systems. In line commutated converter (LCC) HVDC systems, polarity reversal for power flow control can induce significant electrical stress on MI cables. Furthermore, the mass oil and kraft paper comprising the impregnated insulation have significantly different coefficients of thermal expansion. Load fluctuations in the cable lead to expansion and contraction of the mass, creating pressure within the insulation and causing redistribution of the impregnant. During this process, shrinkage cavities can form within the butt gaps. Since the dielectric strength of the cavities is lower than that of the surrounding impregnation, cavitation phenomena in impregnated paper insulation are considered a factor in degrading insulation performance. Consequently, this study analyzes the electrical conductivity of thermally aged materials and investigates the transient electric field characteristics within the cable. Additionally, it closely analyzes the formation and dissolution of cavities in MI cables during polarity reversal based on a numerical model of pressure behavior in porous media. The conductivity of the impregnated paper indicates that it has excellent resistance to thermal degradation. Simulation results for various load conditions highlight that the interval of load-off time and the magnitude of internal pressure significantly influence the cavitation phenomenon. Lastly, the study proposes stable system operation methods to prevent cavitation in MI cables.

On-state electrical stress-induced degradation of NiO/β-Ga2O3 heterojunction pn diodes

Degradation and trap evolution in NiO/β-Ga2O3 heterojunction pn diodes under on-state electrical stress were investigated in this work using deep-level transient spectroscopy measurements and density functional theory (DFT) calculations. The decrease in turn-on voltage and forward current appears to correlate with an increase in the concentration of the compensating acceptor-like traps. From the energy level of EV + 1.3 eV, the corresponding acceptor-like traps can be attributed to the Ga vacancy complex with hydrogen (VGa-H). Interestingly, accompanied by the increase in VGa-H concentration, the self-trapped holes (STH) originally passivated by H may gradually recover. DFT calculations show a monotonous decrease in energy, suggesting the spontaneous diffusion of hydrogen from STH passivated sites to the adjacent VGa, which are generated under stress. This phenomenon leads to the recovery of STH and the generation of VGa-H. This investigation offers new insights into the degradation mechanisms of β-Ga2O3-based devices under electrical stress.

Electrical Stress on the CMOS Inverters Made by Junctionless Gate-All-Around Transistors

Electrical Stress on the CMOS Inverters Made by Junctionless Gate-All-Around Transistors

Electrohydrodynamic flows inside a neutrally buoyant leaky dielectric drop

We present an experimental investigation of electrohydrodynamic (EHD) flows within a neutrally buoyant drop with a radius of 2.25 mm. Utilizing particle image velocimetry and high-speed shadowgraphy, we measure the internal circulation and reported velocity profiles in the bulk and at the interface of the drop. Two leaky dielectric liquids, silicone and castor oils, are employed as the drop and as the external phase, allowing the analysis of two shape configurations: oblate and prolate. The strength of the applied uniform electric field (from 0.125 to 1.75 kV/cm) enables the analysis covering both the small-deformation limit (CaE≪1) and drops with larger deformations. Our measurements show good agreement with the leaky dielectric model (LDM) for the small-deformation cases. The flows begin at the interface as a result of jump in the electric stresses, leading then to four counter-rotating vortices inside the drop. At a permanent regime, the analytical solutions adequately predict the radial and tangential velocity components within the drop. However, a nuanced behavior is noticed for larger deformations, where the LDM theory underpredicts the internal circulation. Moreover, due to the increased deformation, a non-uniform azimuthal profile is observed for the velocity at the interface, vθ. Transient measurements of this velocity component enlighten the dynamic response of the EHD flows of the drop. Following the available analytical solutions, the dynamic response is governed by the timescale of the deformation of the drop, τdef=μa/γ. We propose a critical value of CaE≈0.1 below which the LDM adequately describes the velocity field in both quasi steady-state and transitory regimes.

Data-driven surrogate modelling of multistage Taylor cone–jet dynamics

The Taylor cone jet is an electrohydrodynamic flow typically induced by applying an external electric field to a liquid within a capillary, commonly utilized in colloidal thrusters. This flow generation involves a complex multiphase and multiphysics process, with stability contingent upon specific operational parameters. The operational window is intrinsically linked to flow rate and applied electric voltage magnitude. High voltages can induce atomization instabilities, resulting in the production of an electrospray. Our study presents initially a numerical investigation into the atomization process of a Taylor cone jet using computational fluid dynamics. Implemented within OpenFOAM, our numerical model utilizes a volume-of-fluid approach coupled with Maxwell's equations to incorporate electric body forces into the incompressible Navier–Stokes equations. We employ the leaky-dielectric model, subjecting the interface between phases to hydrodynamic surface tension and electric stress (Maxwell stress). With this model, we studied the droplet breakup of a heptane liquid jet, for a range of operation of 1.53–7.0 nL s−1 and 2.4–4.5 kV of extraction. First, the developed high-fidelity numerical solution is studied for the jet breakup and acceleration of the droplets. Second, we integrate a machine learning model capable of extending the parametric windows of operation. Additionally, we explore the influence of extractor and acceleration plates on colloidal propulsion systems. This work offers a numerical exploration of the Taylor cone–jet transition and droplet acceleration using novel, numerically accurate approaches. Subsequently, we integrate machine learning models, specifically an artificial neural network and a one-dimensional convolutional neural network, to predict the jet's performance under conditions not previously evaluated by computationally heavy numerical models. Notably, we demonstrate that the convolutional neural network outperforms the artificial neural network for this type of application data, achieving a 2% droplet size prediction accuracy.