Voltage Rate Research Articles

Technical specification envelope for SiC semiconductors to enable high-power in space

Abstract High-power electrical systems are needed for the next space missions and the current space qualified silicon semiconductor technology is unable to provide the necessary technical figures to develop them. Following the trend on terrestrial industry, and due to the better physical characteristics when compared to silicon, the silicon carbide semiconductors are considered for their application in space, to address the challenge brought by the high-power. In close collaboration with the European space power industry, the technical characteristics of the new required semiconductors are gathered, classified, and presented in this work. First, the high-power applications mentioned by the industry and the innovation required in each one are presented. Next, the technical characteristics of the required semiconductors for each application and innovation are shown, generating a specific value envelope, starting with the voltage and current ratings, following with the conduction and switching characteristics, and finishing with the thermal requirements and the preferred packaging. Finally, other requirements such as driving components and knowledge generation and transfer are also addressed as requested by industry. This work is a connection between the space power industry and silicon carbide manufacturers, providing them a guide to shape the development of their next products and opening a new business case in space. By giving answer to the needs of the space power industry, this project provides ways for an early and successful adoption of the silicon carbide technology by the European space power industry, giving them an edge advantage over their competitors.

Effect of welding parameters on microstructure and mechanical properties of GMAW welded S275 steel welded zone

This study investigates the effect of welding parameters on the microstructural evolution and mechanical properties, such as tensile strength and hardness, in mild steel plates welded using gas metal arc welding (GMAW). The welding parameters examined include welding current, arc voltage, and gas flow rate, with ER K-71 T filler wire as the consumable material. Results indicate that a higher welding current and reduced gas flow rate result in a maximum tensile strength of approximately 533 MPa. However, discrepancies were noted in the microhardness data across different zones, with the heat-affected zone (HAZ) exhibiting a hardness of 115.8 HV, while the weld zone and base metal showed values of 76.7 HV and 112.9 HV, respectively. Microstructural analysis revealed the presence of bainite and ferrite with a tempered martensitic structure in the welded area, demonstrating that the combination of welding parameters plays a critical role in controlling phase transformations and mechanical behavior. It is essential to reconcile the observed hardness values with the conclusions drawn to ensure accurate interpretation of the data.

Multiobjective optimization of welding process variables in RMD and FCAW techniques using a heat transfer search algorithm for 316LN stainless steel

This study aims to identify the optimal parameters for regulated metal deposition (RMD) and flux-cored arc welding (FCAW) processes when joining 316LN stainless steel. The objective was to determine the optimal settings for current (A), voltage (V), and gas flow rate (GFR, L/min) to achieve the desired weld bead characteristics, including bead width (BW), bead height (BH), depth of penetration (DOP), and heat-affected zone (HAZ). A Box–Behnken design based on response surface methodology was employed for the bead-on-plate trials. Mathematical models were developed from the experimental data and validated through analysis of variance and residual analysis, with R-squared values confirming model accuracy. The heat transfer search (HTS) algorithm was used for both single objective and multiobjective optimization. For RMD, optimal results were achieved with a BW of 9.95 mm, BH of 4.39 mm, DOP of 2.26 mm, and HAZ of 0.29 mm, at 130 A, 18 V, and 20 L/min GFR. For FCAW, optimal values were a BW of 11.45 mm, BH of 3.59 mm, DOP of 2.15 mm, and HAZ of 0.40 mm, at 210 A, 24 V, and 10 L/min GFR. The Pareto solutions offered a most suitable choice of the optimal configuration, balancing the desired BW, BH, DOP, and HAZ values. The effectiveness of the HTS algorithm is demonstrated by the minimal differences between predicted and measured values, highlighting its high accuracy in optimizing 316LN stainless steel welding parameters.

A five‐level nested neutral point‐clamped inverter topology

AbstractClassical five‐level nested neutral point‐clamped (5L NNPC) inverter‐leg is a hybrid of the flying‐capacitor and diode‐clamped 5‐L inverter‐leg configurations. Though uniform reduced voltage stress on the constituting switches is evident in 5L NNPC inverter‐leg, trails of the drawbacks of diode‐clamping concept still exist. Compared with the classical 5L NNPC inverter, the state‐of‐the‐art diode‐free 5L NNPC inverter involves no passive power switches and has low conduction losses. However, in this 5L NNPC inverter, two of the eight active switches have blocking voltage rating of 1/2 of the input voltage. Considering this limiting topological feature, an inverter‐leg for 5L NNPC inverter is presented in this paper. In the proposed 5L NNPC inverter‐leg, only one switch has voltage stress of 1/2 of the input voltage. This reduced voltage stress has inverter cost and loss implications. The performances and competitiveness of the 5L NNPC inverter were analysed in detail and demonstrated with a prototype. The blocking voltages of all the constituting power switches; profiles of the flying‐capacitor voltages; and FFT spectrum of line voltage waveform were experimentally obtained. Experimental deactivation and activation of the inverter's capacitor voltages balancing scheme were typified for varying modulation index values.

Effects of anode voltage and mass flow rate on the erosion of inner permanent magnet conducting cover in a 100 W Hall thruster

Abstract The effects of anode voltage and mass flow rate on the erosion of the inner permanent magnet conducting cover in a 100W Hall thruster were studied in this paper. To accelerate erosion, an inner permanent magnet conducting cover made of aluminum alloy was employed. Experimental results indicate that the erosion rate of the inner conducting cover increases with higher anode voltage and mass flow rate. When the anode mass flow rate is set at 3.8 sccm and the anode voltage increases from 200 V to 300 V and 350 V, the erosion rate at the center of the inner conducting cover increases from 6.54 mm/kh to 9.29 mm/kh and 13.79 mm/kh, respectively, reflecting increases of 42.0% and 110.8% compared to the initial erosion rate. When the anode voltage is 200V and the anode mass flow rate increases from 3.8 sccm to 5.4 sccm and 6.9 sccm, the erosion rate at the center of the cover increases from 6.54 mm/kh to 9.00 mm/kh and 10.91 mm/kh, indicating increases of 37.6% and 66.9%, respectively. These findings underscore the challenges of maintaining the lifespan of the inner conducting cover when thruster is operated under the conditions of high specific impulse and high thrust discharge. Further investigation reveals that the potential difference between the channel exit and the inner conducting cover is a significant factor driving ions near the channel exit bombardment of the inner conducting cover. Increased anode voltage and mass flow rate enhance this potential difference and increase the ion density near the channel exit, resulting in greater current density and energy of ions bombarding the inner conducting cover, thereby accelerating its erosion. This study provides a reference for the lifespan analysis of the inner conducting cover in low-power thrusters operating under multi-mode conditions.

Novel Single-Stage Electrolytic Capacitor-Less Buck-Boost Inverter

Nowadays, single-phase, single-stage, buck-boost power inverters are mostly considered to be used for renewable energy source applications due to their wide range of capabilities. This article introduces a novel, single-phase, single-stage, buck-boost inverter with a wide range of input DC voltage. In addition, the introduced inverter does not use the electrolytic capacitor, which enhances the lifetime and volume reduction in the inverter, avoids the high equivalent series resistance, and reduces the inrush current of electrolytic capacitors in the introduced inverter. Moreover, the introduced inverter exhibits a reduced switch voltage rating, and the novel PWM control strategy with the half-cycle of the sinusoidal is derived to reduce the switching loss of power switches, thus improving the inverter’s efficiency. The operation states, theoretical analysis, and design of components are fully discussed. A comparative study of the introduced inverter with other buck-boost inverter topologies is also reported. Finally, the 500 W laboratory prototype is set up for simulation and experimental verification. The experimental results verify the correctness of operating analysis and simulation.

Transient energy storage systems for fast frequency response: Power‐train considerations

AbstractRenewable energy sources generate power intermittently, which poses challenges in meeting power demand. The use of transient energy storage systems (TESSs) has proven to be an effective solution to this issue. Hence, it is crucial to understand the impact of TESS components design on sizing the power‐train system during fast frequency response. While power‐train systems have been extensively discussed, the impact of dc‐link voltage on the TESS power‐* train and associated power electronics specification requirements has not been evaluated. This study uses a sodium‐nickel chloride (NaNiCl2) battery‐based TESS to assess different power‐train options. Specifically, the research investigates the impact of variations in dc‐link voltage due to battery regulation and state‐of‐charge (SoC) on the design of the TESS‐connected power‐train system, since these will be the major contributions to the power‐train system performance envelope. This paper also compares the performance of TESS power‐train systems with four different schemes. The power‐train models include the detailed modelling of energy sources, power electronic converters, and transformers based on published parameters and testing data. Additionally, the study proposes a performance index to evaluate the superiority of the four schemes in terms of voltage and current rating, efficiency and battery size.

Trace Multifunctional Additive Enhancing 4.8 V Ultra‐High Voltage Performance of Ni‐Rich Cathode and SiOx Anode Battery

AbstractThe combination of high‐voltage Ni‐rich cathodes and high‐capacity Si‐based anodes can result in high energy density for next‐generation batteries. However, the practical capacities accesses are severely hindered by unstable electrode/electrolyte interphases (EEI) and irreversible structural degradation, which necessitates efficient additives in electrolyte for generating stable EEI. Herein, a multifunctional additive, 3‐Fluoro‐5‐(4,4,5,5‐tetramethyl‐1,3,2‐dioxaborolan‐2‐yl)picolinonitrile (FTDP) is proposed to construct robust interfaces at both cathodic and anodic surface, so as to enhance electrochemical performance. FTDP is preferentially decomposed to form B‐contained and cyano (CN) group‐rich cathode electrolyte interphase (CEI), as well as LiF‐, Li3N‐rich solid electrolyte interphase (SEI), simultaneously, resulting in the integrity and stability of electrodes. Moreover, the FTDP‐derived CEI can suppress transition metal ions dissolution, further facilitating battery cyclability. The multifunctionality of FTDP, including quenching free radicals, alleviating the hydrolysis of LiPF6 and inhibiting HF generation, thus greatly improving interfacial stability. With trace addition of 0.2 wt.%, NCM811/Li cell can be performed at an extreme condition, i.e., ultra‐high voltage (4.8 V), high temperature (60 °C) and high rate (10C). 1.6 Ah NCM811/SiOx pouch cell delivers a high capacity retention of 84.0% after 300 cycles.

Novel multi-modular power conditioning system and decoupling control strategy for SMES with coupled superconducting coil

The high-temperature superconducting magnetic energy storage system (HTS-SMES) utilizes a superconducting coil (SC) to store electric energy in a magnetic field. It has several advantages such as high efficiency, fast response, and infinite charge–discharge cycles. Coupling two SCs made of different HTS materials, known as coupled SC (CSC), can enhance the utilization rate of HTS tapes, reduce manufacturing costs, increase the energy storage density of the SC, and lower magnetic leakage. However, the presence of a coupled magnetic field in CSC makes precise power and current regulation of the individual SC challenging. Additionally, the self-inductances of the individual SCs, composed of different materials, typically differ from each other. Consequently, the current variation induces electromotive force in each SC that differs from the others, necessitating the design of power converters with different voltage ratings connected to each SC. To address the difficulties associated with SMES implementation using CSC, this paper proposes novel modular power conditioning system (MPCS) and decoupling control strategy for SMES. The MPCS enables the flexible design of individual SC power ratings by selecting the appropriate number of power modules. The decoupling control ensures precise current control of each individual SC, which significantly reduces the current ripple of the SCs. Moreover, by employing carrier phase shift modulation, the total harmonic distortion (THD) of the PCS output current is as low as 0.79%. Furthermore, the feedforward power control is proposed to reduce the power control overshoot, and the current sharing control is presented to ensure precise current sharing between each SC. Simulation results verify the efficacy of the proposed approaches.

Parametric optimization and determination in machining processes by means of probabilistic multi-objective optimization

In the present article, it attempts to present the determination of optimal parameters of machining processes by means of probabilistic multi-objective optimization (PMOO), in which the optimal objectives (attributes) are fundamentally divided into beneficial type and unbeneficial type, moreover all attributes of both beneficial type and unbeneficial type are evaluated separately with equivalent manner to get their partial preferable probability. Finally, the total preferable probability of each alternative is obtained by the product of all partial preferable probabilities, which is the unique and decisive representative of the alternative to join the competitive optimization, the optimum alternative is with the highest total preferable probability. An example of parametric optimization and determination of aerospace component with Electro Chemical Machining (ECM) is taken to illuminate the procedure. In the case of ECM, the current, voltage, and feed rate are as the optimal parameters to be investigated, while Material Removal Rate (MRR), and Surface Roughness (SR) are the optimal objective responses to be measured. The experimental runs were designed using an L27 Taguchi orthogonal array. In the assessment of PMOO for ECM, the objective MRR belongs to the beneficial attribute, and the objective SR is as the unbeneficial attribute. The novelty of this work is to reflect the simultaneity and the irreplacement of optimization of objectives MRR and SR in the optimal system. The evaluated results reveal that the optimized experimental scheme is the alternative 8, which is with the optimal responses of MRR of 280.112 g/min and SR of 0.45 mm, the corresponding optimum experimental parameters are voltage of 12 V, electrolyte flow rate of 12 m/s and tool feed rate of 0.4 mm/min, respectively. The achievement of the present article indicates the validity of the corresponding approach and algorithm.

A Thermodynamic Analysis of a Proton Exchange Membrane Electrolyzer

A thermodynamic, first law analysis was conducted to understand the temperature of a proton exchange membrane electrolyzer when operated at a constant voltage and feed water flow rate. It emerged that at certain values for both voltage and flow rate, the electrolyzer could work in two operation modii: a high stoichiometry, low current modus where most of the feed water just flows through the electrolyzer unreacted and the electrolyzer itself remains cold, and the preferred low stoichiometry, high current modus that results in a much higher operating temperature. A start-up procedure has to be developed to activate the latter. Overall, the measured electrolyzer temperatures are in very good agreement with the calculated ones.

Modelling and optimization for material removal rate while processing bio-compatible Ti-6Al-7Nb using wire electric discharge machining (WEDM)

Abstract This study utilizes machine learning methodologies, such as artificial neural networks (ANN) and TLBO (teaching Learning Based optimisation), to develop a model and Optimisation of the Material Removal Rate (MRR) in wire electrical discharge machining (WEDM) of Ti-6Al-7Nb. The material removal rate was determined by conducting WEDM experiments with different levels of control parameters, including spark on time, spark off time, peak current, servo voltage, and wire feed rate using a Full Factorial approach through 81 runs. The most effective architecture for the ANN model was 4–10–1, and the parameters were adjusted depending on R2. The Artificial Neural Network (ANN) predictions were compared to those produced by the Multiple Linear Regression (MLR) model. The performance of these models was assessed by calculating the correlation between the experimental values and predicted values by models (R2). MRR value is optimised using TLBO (Teaching Learning Based Optimisation), keeping the relation developed by MLR as the objective function and leading to an improved material removal rate. The proposed method ANN & TLBO would help accurately predict and optimise MRR while processing Ti-6Al-7Nb. These machine learning-based methods significantly enhance complex machining processes by providing predictive capabilities & optimizing parameters, hence playing a vital role in achieving higher efficiency, quality, and adaptability in manufacturing environments.

Taguchi, Grey Relational Analysis, and ANOVA Optimization of TIG Welding Parameters to Maximize Mechanical Performance of Al-6061 T6 Alloy

This study presents a comprehensive investigation into optimizing Tungsten Inert Gas (TIG) welding parameters to enhance the mechanical performance of the widely used Al-6061 T6 alloy, specifically in a double V joint configuration with a plate thickness of 6 mm, for aerospace applications. The Taguchi method was employed to design the experiments, providing a robust framework for analyzing the influence of the electrical current, voltage, and gas flow rate on weld quality. Additionally, a Grey Relational Analysis (GRA) and an Analysis of Variance (ANOVA) were used to validate the optimal welding parameters and quantify the significance of each factor. The optimized parameters were determined to be an amperage of 180 A, a voltage of 18 V, and a gas flow rate of 10 L/min, resulting in significant improvements of up to 40% in tensile strength and 23% in hardness, demonstrating the effectiveness of the optimized conditions. The findings provide valuable insights into welding metallurgy, offering practical guidelines for enhancing high-performance welded joints in critical industrial applications. This study underscores the potential of combining Taguchi, GRA, and ANOVA methodologies to achieve superior mechanical properties and reliability in welded structures.

Investigation of highly efficient CO2 hydrogenation at ambient conditions using dielectric barrier discharge plasma

The increasing utilization of CO2 for synthesizing high-value fuels or essential chemicals is a potentially effective approach to mitigating global warming and climate change. Compared to thermal catalytic CO2 conversion under hash operating conditions (400–500°C, 10 ​MPa), non-thermal plasma can overcome kinetic barriers and trigger reactions beyond thermal equilibrium at ambient temperature and pressure. In this study, the effects of operating conditions (discharge frequency, input power, and gas flow rate) and geometrical parameters (discharge length, discharge gap, and dielectric materials) have been extensively analyzed using typical cylindrical dielectric barrier discharge (DBD) plasma. The discharge characteristics changed by operating conditions (including waveforms of applied voltage and current) are compared, indicating higher applied voltage and lower gas flow rate can strengthen the filamentary discharges. The results demonstrate CO2 conversion rate increases with the increase of applied voltage and the decrease of CO2/H2 ratio, achieving its maximum value of 43.0% at 20 ​mL/min. The highest energy efficiency of 3771.9 ​μg/kJ for CO generation is obtained at the applied voltage of 5.5 ​kV and gas flow rate of 40 ​mL/min, respectively. Besides, the constructure of plasma reactor also impacts the performance of CO2 conversion. On the one hand, the discharge gap has a significant role in the variation of CO2 conversion and product selectivity, which is attributed to the electric field density and corresponding electron-induced reaction. On the other hand, the circulating water-cooling jacket was used to find out the influence of reaction temperature, which switched the product from CO to CH4. This work will pave the way for a sustainable alternative towards future CO2 conversion and utilization.

Array hollow-anode microsecond-pulsed plasma jets at atmospheric pressure: mode transition and influencing factors

Abstract Hollow cathode plasma jets are commonly utilized across various fields, yet there is limited research on hollow anode discharge, particularly on array hollow anode plasma jets. This letter presents the novel design of a array hollow anode discharge device excited by microsecond pulse. Systematical investigations about the discharge characteristics and mode transition process of the device are examined from the perspectives of electricity and space-time distribution to get insights into the formation mechanisms of array hollow anode plasma jets. Results show that three distinct discharge modes when the array hollow anode plasma jets interacting with ITO plate are identified based on the number and location of the discharged hollow anodes: Mode A involves all 16 hollow anodes discharging, Mode B entails 12 hollow anodes discharging, and Mode C comprises 4 hollow anodes discharging at the four vertices of the device. It is observed that experimental outcomes are influenced by the distance from the hollow anode tube port to the plate. The formation mechanism is determined by an increase in distance impacting spatial electric field distribution and facilitating mode transition. Furthermore, the impacts of pulse voltage, pulse frequency, and flow rate on the variation of interval length under different modes are investigated. The results indicate that voltage has the most significant effect on interval length, followed by frequency, while flow rate has a minimal effect. These findings hold significant implications for enhancing understanding of mode transition and influencing factors of array hollow anode plasma jets.

From Textile and Mine Waste Into Sustainable, Low‐Cost and Valuable Nanotextile Fabric‐Based Composites Through Electrospinning Technique

ABSTRACTThe rapid expansion of textile industries has contributed significantly to non‐biodegradable waste generation, presenting a global environmental challenge. Additionally, waste from the mining industry, such as chrysotile serpentine, contributes to this environmental issue. Therefore, this study investigates the possibility of recycling polyamide 6 waste combined with chrysotile serpentine waste to produce nanotextile fabric‐based composite (NTF‐BC). This study highlights the environmental significance of sustainable techniques in waste management specifically within the textile industry. The chrysotile serpentine waste was intensively pulverized into nanoscale particles to eliminate its hazardous fibrous nature and facilitate the electrospinning process. Comprehensive characterization was conducted using various analytical techniques including XRD, XRF, FT‐IR, SEM, BET, and DMA, to explore the properties of prepared fabrics as a function of electrospinning parameters (Ctl.Sp concentration, spinning distance, applied voltage, and flow rate.). SEM analysis indicated optimal fabrication conditions for smoother and more homogeneous NTF‐BC at Ctl.Sp concentration of 7.5%, voltage of 20 kV, spinning distance of 15 cm, and flow rate of 1 mL/h. XRD and FT‐IR analyses showed that increasing the Ctl.Sp ratio, distance, and voltage negatively affected sample crystallinity and favored the α‐form over the γ‐form. In terms of DMA characteristics, the Ctl.Sp ratio and applied voltage positively impacted the E′ values, with minimal influence from spinning distance and rate. Notably, the highest geometric properties (i.e., SBET and Vt) of the fabricated NTF‐BC were attained at the lowest Ctl.Sp ratio of 5%.

Feasibility study on machine learning methods for prediction of process-related parameters during WAAM process using SS-316L filler material

The geometry of objects by means of wire arc additive manufacturing technology (WAAM) is a function of the quality of the deposited layers. The process parameters variation and heat flow affect the geometric precision of the parts, when compared to the actual dimensions. Therefore, in situ geometry monitoring which is integrated in such a way to enable a backward control model is essential in the WAAM process. In this article, an attempt is made to study the effect of four input variables, namely voltage (U), welding current (I), travel speed and wire feed rate on the output function in the form of two geometrical characteristics of a single weld bead. These output functions which are determinant of the weld quality are width of weld bead (BW) and height of weld bead (BH). A machine learning approach is utilised to predict the bead dimensions based on the input parameters and to predict the parameters by assigning suitable scores. For predicting the bead dimensions, two models, namely linear regression and random forest, shall be utilised, whereas for the purpose of classification based on weld parameters, k-nearest neighbours model shall be employed. Through this work, a wide dataset of parameters in the form of input variable and output in the form bead dimensions are generated for 316LSi filler material which shall be used as a training data for a machine learning algorithm. Subsequently, the predicted parameters shall be cross-checked with actual parameters.

An Adaptive Approach in Polymer-Drug Nanoparticle Engineering using Slanted Electrohydrodynamic Needles and Horizontal Spraying Planes.

The present study focuses on the adaptive development of a key peripheral component of conventional electrohydrodynamic atomisation (EHDA) systems, namely spraying needles (also referred to as nozzles or spinnerets). Needle geometry and planar alignment are often overlooked. To explore potential impact, curcumin-loaded polylactic-co-glycolic acid (PLGA) and methoxypolyethylene glycol amine (PEG)-based nanoparticles were fabricated. To elucidate these technological aspects, a horizontal electrospraying needle regime was adapted, and three formulations containing different polymeric ratios of PLGA: PEG (50:50, 75:25, and 25:75) were prepared and utilised. Furthermore, processing head tip geometries e.g.blunt (a flat needle exit) or slanted (a 45° inclination angle), were subjected to various flow rates (5 µL-100 µL). Successful engineering of curcumin-loaded polymeric nanoparticles (< 150nm) was observed. In-silico analysis demonstrated stable properties of curcumin, PEG and PLGA (molecular docking studies) and fluid flow direction towardsthe Taylor-Cone (also known as the stable jet mode), was shownby the assessment of fluid dynamics simulations in various needle outlets. Curcumin-loaded nanoparticles were characterised using an array of methods including Scanning electron microscopy, Differential scanning calorimetry, Fourier transform infrared spectroscopy, X-ray diffraction, as well as their contact angles, encapsulation efficiencies and finally release patterns. The discrepancy when spraying with blunt and angled needles was evidenced by electron micrographs and deposition patterns. Spraying plumes utilising slanted needles enhanced particle collection efficiency and distribution of resultant atomised structures. In addition to needle design, fine-tuning the applied voltage and flow rate impacted the electrospraying process. The coefficient of variation was calculated as 30.5% and 25.6% for blunt and angled needle outlets, respectively, presenting improved particle uniformity with the employment of angled needle tips (8-G needle at 25 µL). The interplay of processing parameters with the utilisation of a slanted exit at a capillary optimised the spray pattern and formation of desired nanoparticulates. These demonstrate great applicability for controlled deposition and up-scaling processes in the pharmaceutical industry. These advances elaborate on EHDA processes, indicating a more cost-effective and scalable approach for industrial applications, facilitating the generation of a diverse range of particle systems in a controlled and more uniform fashion.

The analysis of the overall failure of practical Zn−Ni battery

Zn−Ni batteries are viewed as promising power sources for electric tools and electric vehicles (EVs) due to their benefits of high safety, high working voltage and attractive rate performance. However, the practical applications of the Zn−Ni batteries are hampered by poor cycling performance, posing significant challenges for their widespread utilization. To effectively address this pressing concern, a profound investigation of the intrinsic failure mechanisms underlying Zn−Ni batteries holds paramount importance. This paper carries out a thorough analysis of battery behavior to simulate industrial application scenarios using two different assembly methods of Zn−Ni batteries. One type is a battery composed of one Ni(OH)2 cathode and one Zn anode (abbreviated as OO). The other type is the battery assembled with one Ni(OH)2 cathode and two Zn anodes (abbreviated as OT). Ultimately, it is revealed that the principal factors of Zn anode failure in OO battery are the growth of zinc dendrites, passivation and uneven current distribution. In contrast, for OT battery, the cathode emerges as the failed electrode. Specifically, the rupture of spheres on the positive electrode surface and the detached powder from the substrate result in the decline in capacity and finally the failure of the battery. Two classical battery assembly methodologies were employed to investigate in-depth the failure mechanisms of Zn−Ni batteries, ultimately revealing that the reasons for battery failure mechanism differed, thus providing valuable and practical guidance for future research aimed at enhancing battery lifespan.

Investigation into micro slotting of Cu-based shape memory alloy via µ-ECM using ethylene glycol mixed aqueous NaCl electrolyte

ABSTRACT Micro-Electrochemical Machining (µECM) presents significant promise as a future micromachining process offering higher machining rates, improved precision and the ability to work with a wide range of materials. Cu-based shape memory alloys (SMAs) have exceptional properties that make them quite difficult to machine using traditional techniques. In this investigation a new electrolyte solution consisting of ethylene glycol (EG) and NaCl has been explored while attempting µECM of Cu-SMA. The Cu-based shape memory alloy used consists primarily of Cu-53.19%, Zn-41.50%, and 5.2% other elements. Four different parameter combinations selected based on pilot experiments were used for the main experimentation conducted in four sub-sets. The influence of micromachining parameters including machining voltage, electrolyte concentration and micro-tool feed rate on µECM characteristics such as material removal rate (MRR) and surface roughness (SR) during micro-slot formation has been investigated. With the identified optimum parameters, a high-quality micro-slot was successfully machined on Cu-based shape memory alloys achieving a material removal rate of 0.323 mg/min and surface roughness of 0.384 μm. The investigation demonstrated that an ethylene glycol electrolyte containing NaCl is more suitable for µECM of micro-slots offering superior surface integrity and shape accuracy compared to a water-based electrolyte.