Electrical Applications Research Articles

Evaluation of a multiphase cascaded H-bridge inverter for induction motor operation

Multi-phase systems are becoming more popular for applications requiring high power and precise motor control, even if single-phase AC power is still frequently utilized in households and some enterprises. While both systems have benefits over single-phase, there are trade-offs associated with each. Because of its balanced operation and effective power transfer, the three-phase (3-Φ) system is the most widely used multi-phase system. Nevertheless, different phase values can be investigated for particular applications where reducing torque ripple and harmonic content is essential. Using odd numbers of phases (such as 5-Φ) that are not multiples of three is one method. This design has the ability to reduce torque ripple by producing a more balanced magnetic field as compared with even-numbered phases. But adding more phases also makes the system design and control circuitry more complex. Systems with five phases (5-Φ) provide a compromise between performance and complexity. Applications such as electric ship propulsion, rocket satellites, and traction systems may benefit from their use. Nevertheless, choosing a multi-phase system necessitates carefully weighing the requirements unique to each application, taking into account elements like cost, power transmission, control complexity, and efficiency. The increasing popularity of electric vehicles and renewable energy technologies has led to the need for inverters in current electric applications. Conventional inverters provide square wave outputs, which cause the drive system to become noisy and cause harmonics. Multi-phase multilevel inverters can be used to enhance inverter functioning and produce an improved sinusoidal output. This study focuses on an induction motor drive powered by a five-phase multilevel cascaded H-Bridge inverter. With less torque and current ripples in the motor rotor, the power conversion harmonics are reduced and the switching components of the inverter are under less stress. However, in comparison to traditional inverters, it does require a greater number of legs. Because the switches needed for the cascaded H-Bridge inverter are less expensive in five-phase systems, they are favoured over higher phase orders. Furthermore, the suggested inverter removes 5th order harmonics, something that is not possible with traditional inverters. A five-phase induction motor appropriate for variable speed driving applications is also suggested by this research. Lastly, utilizing pulse width modulation (PWM) converters and an FPGA controller, an experimental study is carried out to assess the dynamic performance of the suggested induction motor drive. Particular attention is paid to the In-Phase Opposition Disposition (IPD) PWM technique.

Detection dataset of electric bicycles for lift control

Electric bicycle datasets for lift control have played a crucial role in the development of electric bicycle lift entry detection algorithms. However, existing datasets often encounter issues, including a small dataset size, a high false detection rate, and the absence of a publicly available benchmark dataset. This paper addresses these challenges by constructing a new electric bicycle detection dataset for lift control based on the research demands of the electric bicycle detection task for lift control. XHNet_EB, a car scene image dataset covering various types of electric bicycles, was constructed based on images taken by a camera from above. Segmented annotation was employed, framing the front and rear of the electric bicycle independently. This approach effectively addressed the problems of many irrelevant features and a high false detection rate caused by the use of whole-electric-bicycle annotations in mainstream datasets. AP_50, AP_75, the mAP, and the number of false detections in the images were used for quantitative analysis of the dataset. The experimental results indicated that the object detection accuracy of the XHNet_EB dataset was excellent. Quantitative analysis and evaluation of the number of false detections in images were conducted using four mainstream lightweight detection model algorithms. The results demonstrated that segmented annotation reduced the false detection rate more effectively than entire electric bicycle annotation. This study identified drawbacks in existing datasets. The dataset proposed in this paper overcomes the shortcomings of existing commercial data and solves problems such as the high false detection rate caused by the inclusion of many irrelevant features caused by the “whole-electric-bicycle annotation” method, which could help with the development of electric bicycle detection applications in lifts.

Real-time estimation of the optimal coil placement in transcranial magnetic stimulation using multi-task deep learning

Transcranial magnetic stimulation (TMS) has emerged as a promising neuromodulation technique with both therapeutic and diagnostic applications. As accurate coil placement is known to be essential for focal stimulation, computational models have been established to help find the optimal coil positioning by maximizing electric fields at the cortical target. While these numerical simulations provide realistic and subject-specific field distributions, they are computationally demanding, precluding their use in real-time applications. In this paper, we developed a novel multi-task deep neural network which simultaneously predicts the optimal coil placement for a given cortical target as well as the associated TMS-induced electric field. Trained on large amounts of preceding numerical optimizations, the Attention U-Net-based neural surrogate provided accurate coil optimizations in only 35 ms, a fraction of time compared to the state-of-the-art numerical framework. The mean errors on the position estimates were below 2 mm, i.e., smaller than previously reported manual coil positioning errors. The predicted electric fields were also highly correlated (r> 0.97) with their numerical references. In addition to healthy subjects, we validated our approach also in glioblastoma patients. We first statistically underlined the importance of using realistic heterogeneous tumor conductivities instead of simply adopting values from the surrounding healthy tissue. Second, applying the trained neural surrogate to tumor patients yielded similar accurate positioning and electric field estimates as in healthy subjects. Our findings provide a promising framework for future real-time electric field-optimized TMS applications.

Modeling methods in overlapping electroporation treatments: Pulse number effects on tissue conductivity and ablation area

Irreversible electroporation (IRE) is a non-thermal tissue ablation technique that utilizes high-voltage pulses between electrode pairs to destroy tissue. Numerical models are essential for predicting treatment outcomes and aiding in treatment planning. This paper studies a nonlinear conductivity model (NC) and a multiparametric nonlinear conductivity model (MPNC) to investigate overlapping electroporation treatments using a three-needle electrode configuration. The NC model accounts for the effects of the electric field and temperature on tissue conductivity during multiple pulsed electric field applications. The MPNC model incorporates the influence of pulse number, alongside electric field and temperature, on tissue conductivity. Results indicate that in the MPNC model, tissue conductivity is significantly higher in regions where the electric field intensity is below the threshold for irreversible electroporation, with the maximum difference reaching 0.4S/m. In contrast, tissue conductivity is slightly lower in regions where the electric field intensity exceeds the IRE threshold. Additionally, the MPNC model predicts a smaller area of irreversible electroporation and a larger area of reversible electroporation, with these differences becoming more pronounced as the distance between electrode needles increases. These findings underscore the importance of considering pulse number effects in numerical models to enhance the accuracy of treatment planning for irreversible electroporation-based therapies.

Experimental validation of fuzzy logic controller based on voltage perturbation algorithm in battery storage photovoltaic system

Introduction. Solar photovoltaic (PV) has recently become very important especially in electrical power applications for countries with high luminosity because it is an effectively unlimited available energy resource. Depending on solar radiation and temperature, the PV generator has a non-linear characteristic with a maximum power point (MPP). The novelty is the efficiency improvement of a PV energy module, it is necessary to track the MPP of the PV array regardless of temperature or irradiation circumstances. Purpose. This paper presents the modeling and the digitally simulation under MATLAB/Simulink of a Fuzzy Logic Controller based on Voltage Perturbation Algorithm (FLC-VPA) applied to PV battery charging system, which consists of PV module, DC-DC boost converter, MPP tracking (MPPT) unit and battery storage. Methods. The DSP1104 is then used to experimentally implement this MPPT algorithm for real-time driving. The obtained results show the high precision of the proposed FLC-VPA MPPT around the optimal point compared to the conventional VPA under stable and changing meteorological conditions. Practical value. The experimental results approve the effectiveness and validity of the proposed total control system in the PV system. References 30, tables 3, figures 17.

Research Status and Prospects of High-Voltage Pulse Plasma Rock-Fracturing Technology

With the continuous development of the geological engineering field, high-voltage electric pulse plasma rock-fracturing technology has become a research hotspot in recent years. It is now widely recognized that this fracturing technology has many application prospects and great economic benefits. Through the research process of this technology, it has proven to be an efficient and new type of rock-fracturing technology, which overcomes the problems of high cost, low efficiency, high safety risk, and serious pollution associated with traditional rock-fracturing technology. Also, it has unique advantages in terms of protecting the environment and reducing damage to the surrounding buildings. This paper reviews the research history of plasma shock wave influencing factors and pulsed discharge plasma rock-fracturing technology, summarizes the research on this technology from the perspectives of the mechanism of high-voltage electric pulse plasma rock fracturing and practical application, and discusses the feasibility of this technology when applied to the field of tunnel boring as well as the future development direction. This technology can be better used in the tunnel-boring field, which can greatly improve the tunnel-boring efficiency, but at present, the research on plasma rock-fracturing-assisted tunnel boring is still in the laboratory research stage, which lacks systematic research equipment and judging indexes, and the follow-up should focus on improving the systematic research capabilities of the plasma rock-fracturing-assisted tunnel-boring equipment, and systematically and comprehensively carry out research on rock-fracturing by plasma-assisted excavation equipment.

Synergistic-strengthening strategy induce excellent electrical and mechanical properties in Cu/AlCrCuFeNi2.5 composites

A novel high-strength conductive Cu-based composite, utilizing AlCrCuFeNi2.5 (Ni2.5) high-entropy alloy particles as the reinforcing phase, is synthesized through a combination of ball milling and spark plasma sintering processes. The mechanical and electrical properties of the composites are optimized by adjusting the composition. Under the synergistic effect of multiple strengthening mechanisms, the fabricated Cu-20 wt% Ni2.5 composites achieve an exceptional compressive strength of 920 MPa while maintaining an electrical conductivity of 44.3 % IACS (International Standard Copper Standard). The establishment of robust interface bonding between Ni2.5 reinforcement and Cu matrix stands as a pivotal assurance for the holistic performance of composites. Ni2.5 HEA is distinguished by good plasticity and high strength compared with traditional brittle reinforcements. An insight into the differences brought about by the distinctive dual-phase structure in terms of interfacial bonding, crack propagation, and performance is provided. It paves the way for selecting and projecting the composites for electrical contact applications, ushering in a realm of fresh possibilities.

Environmental impacts and decarbonization pathways of oily sludge pyrolysis based on life cycle assessment

Oily sludge is a major hazardous waste generated in the petroleum and petrochemical industry. The increasing accumulation of oily sludge necessitates safe and sustainable management. In recent years, pyrolysis has gained great attention as an effective treatment method for oily sludge. However, a comprehensive environmental assessment of industrial-scale oily sludge pyrolysis remains limited. Based on the life cycle assessment (LCA) method, this study employs data collected from oily sludge treatment plants to investigate the environmental impacts of the whole pyrolysis system, specifically its carbon footprint. The utilization and final disposal of pyrolysis products are in accordance with the real industrial operations. The contributions of each unit process in the pyrolysis treatment of oily sludge to global warming potential (GWP), as well as the decarbonization pathways, are explored in detail. Results indicate that, in general, pyrolysis has lower adverse environmental impacts than incineration does. Within the pyrolysis system, processes such as pyrolysis, flue gas purification, and hot washing are major contributors to GWP. The recycling and utilization of pyrolytic oil and solid residues can significantly mitigate the adverse environmental impacts of oily sludge pyrolysis. Given the combined applications of co-pyrolysis, green electricity, and other low-carbon technologies, the carbon footprint of oily sludge pyrolysis could be reduced from 635.9 to 31.8 kg CO2-eq in the most ideal scenario.

Laser Printer Printed Ion Sources for Ambient Ionization Mass Spectrometric Analysis of Volatiles and Semivolatiles.

In this study, we demonstrated a facile method to fabricate ion sources using a laser printer for ambient ionization mass spectrometry (MS). Toner spots printed by a printer can readily facilitate ionizing volatile and semivolatile compounds derived from solid or liquid samples for MS analysis. The experimental arrangement involved positioning the toner-printed paper near the inlet of a mass spectrometer, which was subjected to a high electric potential (e.g., -6 kV). Volatile or semivolatile compounds deriving from the sample positioned below the metal inlet of the mass spectrometer were promptly ionized upon activating the mass spectrometer. No direct electrical connection or voltage application was required on the paper substrate. An electric field was established between the toner spot on the paper and the inlet applied with a high voltage to induce the dielectric breakdown of the surrounding air and water molecules. Consequently, ionic species, including electrons and cationic radicals, were generated. Subsequent ion-molecule reactions facilitated the production of protons for ionizing analytes present in the gas phase proximal to the inlet of the mass spectrometer. Deprotonated analytes were detected in the resultant mass spectra when employing the method in negative ion mode. This methodology presents a straightforward approach for analyzing analytes in the gas phase under ambient conditions utilizing an exceptionally uncomplicated experimental setup. In addition, the developed method can be used to detect trace 2,4-dinitrophenol, an explosive, with a limit of detection as low as ∼30 pg.

Refinement of Primary Si Phase in Hypereutectic Al–Si Alloy by Electrically Assisted Solidification with P Addition

The efficient processing of hypereutectic Al–Si alloys depends on controlling the microstructure of the primary Si phase during solidification. This study investigates the effects of electric current and phosphorus (P) addition on the refinement of primary Si, with the results confirming that applying electric current during solidification refines the primary Si phase; introducing P further enhances this refinement. Notably, when 10 ppm of P is added (below the identified critical amount of 20 ppm), an improved refinement effect is observed compared with the application of either electric current or P alone. Applying an electric current generates a circulating flow within the melt, resulting in an increased cooling rate, which leads to improved nucleation behavior for the primary Si phase. In addition, the circulating flow generated within the melt influences the dispersion of aluminum phosphide during nucleation. Adding P at concentrations above 40 ppm does not yield further benefits, suggesting a saturation point for its efficacy. This study demonstrates that the concurrent electric current application and minimal P addition can significantly enhance the refinement of primary Si phases, offering a potent approach for optimizing the microstructural properties of hypereutectic Al–Si alloys.

Degradation Studies of Fuel Cell Cathode Catalyst Layers Using Machine Learning

Fuel cells are a promising technology that has the potential to significantly revolutionize the energy sector by providing clean and sustainable sources of power for transportation, aerospace, and electricity applications. However, optimizing the performance of these devices remains a significant challenge as it largely depends on the catalyst layer in the electrodes of these devices, composed of carbon-supported Pt nanoparticle catalyst (Pt/C), perflurosulfonic acid (PFSA), ionomer binder, and a solvent. The catalyst layer design and operation require extensive knowledge of complex physical and chemical processes especially when achieving a low (<0.1 mgcm-2) Pt loading.Furthermore, the degradation of fuel cells is usually associated with either mechanical and/or electrochemical processes of the catalyst layer during operations, ultimately resulting in performance loss. While combinations of factors are responsible for the degradation of the catalyst layer in the fuel cell electrodes, it is still challenging to evaluate which factor contributes the most to the degradation of the catalyst layer.Machine learning algorithms, being powerful tools for predicting and optimizing the behavior of systems can be used to model complex processes, identify optimal operating compositions, and conditions, and reduce the laborious time and cost required for experimentation. They can be used to analyze data obtained from various experiments to identify patterns, trends, and anomalies. In this study, machine learning algorithms are employed for the prediction of catalyst layer degradation. Furthermore, an assessment of feature importance is conducted, elucidating the relative contributions of individual features to the degradation of catalyst layers. Leveraging on machine learning, we can develop an efficient, reliable, and cost-effective fuel cell system.

Exploiting Deep Eutectic Solvents in LiFePO4 Battery Recycling: From Cathode Leaching to Resynthesis

Nowadays, the increasing demand for electronic devices and electric vehicles influences the request for Lithium-Ion Batteries (LIBs), which are worldwide the most exploited electrochemical energy storage systems for portable devices and are expected to completely dominate also the sector of transportation soon. In particular, the use of LIBs with ordered-olivine structure LiFePO4 (LFP) cathodes stands out ever since their invention in 1997, being a valid solution in terms of durability, reliability, and safety, essential characteristics in the electric mobility application combined with the benefit of low content of critical raw materials, CRMs. Considering that the average life of LFP cathodes is about 5-8 years, the management of these materials as waste becomes essential: the growing number and volumes of LIBs that are currently produced is inevitably intended to correspond to the number of LIBs that will reach the end of their life, becoming waste that are accumulating, posing a staggering danger. [1,2] An also important consideration concerns the conditions required to synthesize LFP for electrochemical purposes, as it is necessary to coat the surface with conductive species, controlling the morphology and reducing the particle size, thus complicating the synthesis and making it economically more impactful. [3]In such a context, recycling combines the necessity to produce new LIBs with the need to cope with the increase in batteries’ waste accumulation: this can limit the disposal of waste batteries into landfills, thus decreasing the inevitable hazardous environmental consequences, while reducing the demand for new mining, re-assigning value to raw materials, in an attempt to minimize the costs that would be required to synthesize pristine LFP-based cathodes. Today, recycling is already implemented at the industrial level, exploiting the pyrometallurgy approach, which involves thermal treatments at very high temperatures (>1000°C) allowing for the recovery of only a fraction of valuable metals; nevertheless, this approach has a strong environmental impact due to the high energy demand and high carbon footprint. The hydrometallurgical approach is also employed, exploiting the leaching process with strong inorganic acids; however, this brings problematic issues, because producing such acids is itself a polluting process, and acidic wastewater management is a demanding problem. Moreover, today these processes involve the recycling of the most diffused cathode, LiCoO2, Li(Ni/Mn/Co)O2, LiMn2O4, and the sustainability of recycling relies on the possibility to recover valuable CRMs such as Co and Ni.In the proposed work we are currently investigating the degradation properties of Deep Eutectic Solvents (DESs), cheap and greener mixtures of compounds forming a eutectic system, liquid at room temperature. [4] In particular, the focus is on the leaching of LFP with a DES obtained by mixing different molar ratios of hydrogen bond acceptor and various hydrogen bond donors, in order to assess the best combination to leach the elements out of LFP structure. The key point of such approach is the design of a degradation system that can enable the conditions for the direct re-synthesis of new LFP material. Indeed, here the sustainability of the process cannot be driven by the recovery of CRMs, thus must rely on the close-loop recycling scheme. For this reason, we specifically designed DES compositions that allow for this process.The proposed DESs, which have been easily prepared at mild heating conditions, have been investigated through different techniques; the results obtained on the chemical-physical characterization (via FTIR spectroscopy, Solid-State NMR, viscosity, thermal analysis) will be presented. Among the different DESs, those with the best combination of properties (e.g. low viscosity, high thermal stability) have been explored for the leaching of LFP cathode. The leaching process has been optimized with respect to the temperature, duration, and cathode-to-DES ratio for different DESs, and the leaching yields have been evaluated through ICP-OES analysis. The obtained leached solution has been considered as the starting point for a sol-gel-like synthesis of new LFP material, finally characterized through XRD, TGA, ICP-OES, and SEM-EDX analysis. Tuning the parameters of the synthesis (temperature and duration of the heat treatment, ratio between LFP mass and conductive species to realize the coating) enables to control the morphology and the dimension of the synthesized particles, to find the best condition for the electrochemical application. The electrochemical performances of the resynthesized materials will also be presented.[1] Sun et al., J. Alloys Compd., 818 (2020)[2] Lv et al. ACS Sustain. Chem. Eng., 6 (2018)[3] Yuan et al., Energy Environ. Sci, 4 (2010)[4] Zhu et al., Resour. Conserv. Recycl., 188 (2023)

Preparation of Soft Magnetic Composite Using Cold Sintering Technique

Soft magnetic composites are powder metal products under development as an alternative to 2D laminates in electric motor applications. The 3D design of SMCs offers greater energy efficiency but poses a challenge to maintain adequate strength properties required for application. Soft magnetic composites are fabricated through compaction and heat treatment of iron particles coated with insulated coating to form a dense compact. The soft magnetic properties of the compact are affected by the properties of the iron powder, density of compact as well as the efficacy of forming uniform thin insulating coating at the particle boundary. Additionally, the strength of the compact is also affected by the nature of the insulating boundary at the particle interfaces. We report a low temperature process that involves cold sintering phenomenon to densify and strengthen soft magnetic composites. Iron powders have been modified using a co-precipitation method that forms a hydrated copper/iron oxalate coating on individual iron particles. Warm compaction of the modified iron powders at 100°C resulted in a highly dense soft magnetic composite which demonstrated ~ 3x improvement in strength. The compacts can be further heat treated in air at higher temperatures to form high strength oxide coating iron based soft magnetic composites. Results of the AC and DC magnetic measurements of fabricated cold sintered toroid compacts made as a function of heat treatment temperature reveal that DC permeability increased with heat treatment temperature. Analysis of AC core loss data showed that hysteresis power losses dominated the performance at lower heat treatment temperatures (< 300°C) beyond which dynamic core losses significantly increased.

(Invited) Towards Rechargeable Zn/CuO Batteries for Grid-Scale Storage

Alkaline Zn batteries are a strong candidate for electrical grid storage applications due to Zn’s high capacity (820 mAh/g), established materials supply chain and low cost. To realize the highest energy dense batteries, Zn needs to be coupled with a similarly low cost, abundant and high-capacity cathode. CuO (674 mAh/g) is an intriguing high-capacity cathode when paired with a Zn anode in alkaline electrolyte, a battery that until recently has been relegated to the history books as a primary system. In 2021 Schorr et al. reported a rechargeable Zn/CuO battery that utilized 10% of a Bi additive to help facilitate the electrochemical reversibility of the Cu conversion electrode. Bi2O3, a species with comparable redox potentials to Cu2O, promoted reversibility and minimized passivation in the historically non-reversible system. The battery cycled without any observable Cu and Bi mixed oxide phases, cycling between metallic Cu and Bi and Cu2O/Cu(OH)2 and Bi2O3, respectively. Although the Bi additive did not eliminate capacity fade completely, limiting the cells to a 30% depth of discharge (relative to CuO) enabled 250 cycles at > 124 Wh/L. Optimization studies performed for Bismuth content indicate that changes in Bi2O3 concentration can impact the charge-discharge behavior of the CuO cathodes resulting in the suppression of metal hydroxide-related redox peaks on charge. The absence of these peaks correlates with improved cyclability, suggesting that methods and materials approaches to further suppress these recharge pathways may lead to CuO high-capacity cathodes with improved cycle-life in the future.Seeking to improve performance and minimize the spatial segregation of Cu- and Bi-phases observed upon cycling in the prior system, D. Arnot et al. prepared nanoscale carbon coated (Cu/Bi) particles, where the coating partially minimized dissolution and diffusion of soluble cuprate and bismuthate complexes, where 200 cycles at 300 mAh/g was demonstrated (@ ~ 100 Wh/L). CuBi2O4 and CuO phases were formed upon oxidation, indicating carbon coatings can also affect the battery cycling mechanism and may have future roles of increasing performance.Data collected from a variety of experimental techniques, including cyclic voltammetry, rotating ring-disk electrode voltammetry, electrochemical impedance spectroscopy, electron microscopy, transmission electron microscopy, Raman spectroscopy, operando energy-dispersive X-ray diffraction measurements, battery cycling along with recent DFT modeling will be presented to help elucidate the role of additives, carbon coatings, polymer gel electrolytes and ion selective polymers in enabling reversible Cu-based cathodes. The general challenges of achieving a highly reversible energy dense battery based on two conversion electrodes operating in highly alkaline environment will be covered as will development towards a > 200 Wh/L industrially relevant Zn/CuO battery.This work was supported by the U.S. Department of Energy Office of Electricity. This work was performed, in part, at the Center for Integrated Nanotechnologies, an Office of Science User Facility operated for the U.S. Department of Energy (DOE) Office of Science. The views expressed in this article do not necessarily represent the views of the U.S. Department of Energy or the United States Government. This article has been co-authored by an employee of National Technology & Engineering Solutions of Sandia, LLC under Contract No. DE-NA0003525 with the U.S. Department of Energy (DOE). The employee owns all right, title and interest in their contribution to the article and is solely responsible for its contents. The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a non-exclusive, paid-up, irrevocable, world-wide license to publish or reproduce the published form of this article or allow others to do so, for United States Government purposes. The DOE will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan.

Diketopyrrolopyrroles As Performance Enhancing Additives for Lithium-Sulfur Batteries

Although the lithium-ion battery (LIB) has been instrumental in global electrification, more premium applications (such as electrification of aircraft) require capacities and performance beyond the capabilities of traditional LIB chemistries[1]. Lithium-sulfur (Li-S) batteries are a front runner among next generation battery technologies thanks to their very high theoretical capacities (1675 mAh g-1) and impressive gravimetric energy densities (2,700 Wh kg-1) [2,3]. Despite their potential, there are numerous chemical challenges (polysulfide shuttle, dendrite formation etc.) that must be overcome before widespread adoption of the technology [4]. Electrolyte additives have been explored as a means to facilitate the electron transfer reactions that occur within the cell and improve cell capacity and cyclability [5].Diketopyrrolopyrroles (DPPs) are a class of organic π-conjugated compounds that have garnered significant interest in a variety of electrical applications, including solar cells and sensors [6]. The high electrochemical tunability, made possible through the editable organic structure, makes them suitable candidates for redox active electrolyte additives. Here, we explore DPP derivatives as a novel class of electrolyte additive for improving the cell cycling performance of Li-S batteries. A variety of electrochemical and analytical techniques have been utilised to assess the suitability of DPPs as redox active additives, building an understanding of their interactions with active materials in a Li-S cell. Galvanostatic cycling allows us to connect these electrochemical findings to cell cycling performance, where we observe a large enhancement in capacity. We also present an alternative statistical approach to cell data analysis, providing a more concrete method to assessing cycling enhancement than that shown throughout literature. Figure 1. A box plot displaying the discharge capacities at specific cycle numbers for standard (light grey) and DPP (dark grey) cells to provide a statistical comparison.

Tailoring the structural, magnetic and dielectric properties in holmium doped Ca-Ba hexaferrite nanoparticles by regulating the Ca-Ba (1:1) concentration for magnetic and electric applications

This work reports the synthesis and characterizations of holmium (Ho) doped Ba-Ca hexaferrites (Ba0.5Ca0.5Fe12-xHoxO19). Structural analysis confirms the pure hexagonal phase throughout, and morphology shows the uniformly distributed hexagonal-shaped particles. The incorporation of Ho3+ ions significantly enhanced magnetic properties, as evidenced by vibrating sample magnetometry (VSM), attributed to the reconfiguration of Fe3+ ions and the reinforcement of superexchange interactions. Across all samples, magnetic hysteresis (M−H) loops exhibited a consistent hard ferrimagnetic behavior, with saturation magnetization (Ms) values varying within the range of 28.64 to 36.33 emu/g, remanent magnetization (Mr) from 16.24 to 20.68 emu/g, and coercivity (Hc) from 1.771 to 2.059 kOe, respectively. The composition with x = 0.09 demonstrated the highest Ms, Mr, and Hc values. The dielectric properties underscore the potential applications of fabricated M−type hexaferrites in microwave technology due to their low dissipation factor and ε“, pivotal for minimizing signal attenuation in crucial components such as filters and resonators. Moreover, Ho doped Ba-Ca hexaferrites present promising alternatives to magnets in electric vehicle applications, suggesting avenues for further research and optimization in this domain.

Treating scars after burns with pulsed electric fields in the rat model.

Reducing scar size after severe burn injuries is an important and challenging medical, technology and social problem. We have developed a battery-powered pulsed electric field (PEF) device and surface needle electrode applicator to deliver pulsed electric fields to the healing dorsal burn wound in rats. PEF was used to treat residual burn wounds caused by metal contact in rats starting 10 days after the injury for 4 months every 11 or 22 days for 4 months using varying time applied voltages at 250-350V range, 400mA current, 40 pulses, 70 μs duration each, delivered at pulse repetition frequency 10 Hz at 5 locations inside the wound. We found 40-45% reduction in the scar size in comparison with untreated controls in both upper and lower dorsal locations on rats' backs two months after the last PEF application. We have not detected significant histopathological differences in the center of the scars besides the thickness of the newly generated epidermis, which was thicker in the PEF treated group.We showed that minimally invasively applied pulsed electric fields through needle electrodes are effective method and device for treating residual burn wounds in the rat model, reducing the size of the resulting scars, without any adverse reaction.

Chemiresistive effect of p-type delafossite CuScO2 microsheets to gaseous alcohols.

The chemiresistive effect of an oxide significantly influences its electrical properties, which depend greatly on the interactions between the ambient gas molecules and the solid surface, including the gas adsorption and charge transfer still challenging to be clarified. In this work, we investigate the chemiresistive effect of the p-type delafossite CuScO2 microsheets by comparing their responses to various gaseous alcohols, which increase with an approximately linear relationship with the length of straight carbon chains from methanol to n-hexanol. A new mechanism is proposed to elucidate such a dramatic trend of observed chemiresistive change based on the first-principles calculations and test results. The increasing carbon chain length modulates the adsorption configuration and provides supplementary routes for electron transfer, which is assumed to account for the observed chemiresistive effect. This work may provide a novel perspective for the investigation and development of more advanced functional oxides for electrical applications.

Nonwoven fabric supported flame-retarding quasi-solid electrolyte for wider-temperature safer Li-ion battery

Energy-dense lithium-ion battery (LIB) is in high demand for advanced portable electronics as well as electric vehicle EV applications. However, the flammability of conventional carbonate-based electrolytes makes the safety of the LIB questionable. Here, we demonstrate a nonflammable, thermally stable electrolyte for LIB application in the wide temperature range of −20 °C–50 °C. Specifically, we developed a non-woven fabric-supported quasi-solid flexible polymer electrolyte with a unique liquid electrolyte combination of methyl propionate (MP), trimethyl phosphate (TMP), fluoroethylene carbonate (FEC), and Poly (vinylidene fluoride-co-hexafluoropropylene) (PVDF-HFP) polymer. The resulting composite electrolyte is compatible with Li metal, and in a half-cell (Li||LFP) performs superior to the commercial electrolyte over the wide temperature range. A full-cell with high-loading (cathode loading 13.2 mg/cm2) LFP combined with graphite demonstrated electrochemical performance. An initial discharge capacity of 115 mAh/g at a C/10 rate and capacity retention of 57 % was observed after 100 cycles. The thermal safety of the full cell was evaluated through multimodule calorimetry, where a low heat release of 37 J/g was observed, compared to 1.5 kJ/g with commercial electrolyte. This report aims to demonstrate the great potential of using flame-retardant quasi-solid polymer electrolytes for fabricating safer LIBs.

Innovative biomass waste heat utilization for green hydrogen production: A comparative and optimization study of steam and organic rankine cycles

Today, designing a green hydrogen production process under an optimal, efficient, and economical configuration is one of the priorities of energy systems engineers. This research aims to explore the application of electricity produced by the steam Rankine cycle (S/RC) and Organic Rankine cycle (ORC) through biomass-based waste heat utilization in an alkaline electrolyzer (AE) system for the production of green hydrogen. The S/RC unit utilizes high-temperature waste heat, while the ORC system utilizes medium to low-temperature ones from the S/RC to improve overall system efficiency and hydrogen output. The study developed eight distinct configurations of the combined system, employing two organic fluids across four ORC designs. It aimed to assess the influence of integrating a recuperator or/and an OFOH (open feed organic heater), as well as varying the organic fluids, on the ORC unit's hydrogen production capability. A detailed thermodynamic, thermo-economic, and eco-economic analysis was conducted to assess key metrics. The environmental analysis quantified the carbon dioxide (CO2) emission reductions achieved through hydrogen production, using the emission rate from the steam methane reforming method as a benchmark. This approach underscored the environmental benefits of the AE system for hydrogen production. Further, the study quantified the financial gains from CO2 reduction, referred to as carbon credit gain (CCG), through an eco-economic analysis. From the outcomes, the highest hydrogen yield and the lowest LCOH (levelized cost of hydrogen) value were 94.65 tons/year and 1.724 US$/kg, respectively, related to Case (IV)-a (biomass waste heat-based S/RC- Regenerative& recuperator ORC system-AE system under R245fa). Lastly, optimization process for maximizing hydrogen production via the optimization methodology was established.