Search Results (109)

The transition to renewable energy makes energy storage crucial. Aqueous organic redox flow batteries (AORFBs) show great potential in large-scale energy storage due to their outstanding safety compared to conventional systems. Derivatives of 2,2,6,6-tetramethylpiperidin-1-oxyl (TEMPO) show significant promise as catholyte materials in AORFBs. In this work, a bipyridine-ester dual-modified TEMPO derivative, (2,2,6,6-tetramethyl-1-piperidinyloxy)carbonyl-ethyl-(4-(pyridin-4-yl)benzyl) ammonium bromide (TEMP-BPy) was successfully synthesized via a two-step functionalization. The synthesized compound was experimentally confirmed to possess excellent electrochemical stability. The electron-withdrawing effect of the 4,4′-bipyridine moiety elevates the redox potential by 60 mV. When implemented as a catholyte paired with methyl viologen (MV) as the anolyte in AORFB, the TEMP-BPy/MV system demonstrates excellent performance: achieving a cell voltage of 1.28 V and an energy density of 14.5 Wh L⁻¹ at a 0.6 M (16.08 Ah L⁻¹) concentration with 71.3% material utilization. Notably, it demonstrates exceptional cycling stability with an average capacity retention of 99.86% per cycle over 200 cycles, and it exhibits particularly impressive initial stability, with an average capacity retention of 99.997% per cycle during the first 100 cycles. Full article

In recent years, transition metal-based catalytic materials have garnered considerable attention, particularly those exhibiting high catalytic efficiency toward both the oxygen evolution reaction (OER) and hydrogen evolution reaction (HER). In this work, a self-supporting ternary transition metal phosphide (CoFeNi_0.2P) with a hierarchical structure was synthesized using the Prussian blue analogue (PBA)/zeolitic imidazolate framework-L (ZIF-L) template. Benefiting from the hierarchical structure of the PBA/ZIF-L precursor and the electronic structure modulation induced by Ni doping, the resulting CoFeNi_0.2P demonstrates impressive bifunctional electrocatalytic activity. Specifically, in 1 M KOH electrolyte, the CoFeNi_0.2P catalyst requires an overpotential of only 88 mV to deliver 10 mA cm⁻² for the HER and 248 mV to achieve 50 mA cm⁻² for the OER. Moreover, it demonstrates satisfactory stability toward both the HER and OER. When integrated into a two-electrode electrolyzer, CoFeNi_0.2P enables a current density of 10 mA cm⁻² at a cell voltage of 1.59 V, maintaining robust performance for over 25 h. This study provides a feasible strategy for the rational design of hierarchical electrocatalysts for efficient overall water splitting. Full article

In this research work, two distinct types of three-dimensional (3D) capacitors were successfully fabricated, each with its own unique features and advantages. The first type of capacitor is centered around a 3D nanoporous structure. This structure is formed on a nickel substrate through anodic oxidation. After undergoing high-temperature thermal oxidation, a monolithic Ni-NiO-Pt metal–insulator–metal (MIM) capacitor with a nanoporous dielectric architecture is achieved. Structurally, this innovative design brings about several remarkable benefits. Due to the nanoporous structure, it has a significantly increased surface area, which can effectively store more charges. As a result, it exhibits an equivalent capacitance density of 69.95 nF/cm², which is approximately 18 times higher than that of its planar, non-porous counterpart. This high capacitance density enables it to store more electrical energy in a given volume, making it highly suitable for applications where miniaturization and high energy storage in a small space is crucial. The second type of capacitor makes use of Through-Glass Via (TGV) technology. This technology is employed to create an interdigitated blind-via array within a glass substrate, attaining an impressively high aspect ratio of 22.5:1 (with a via diameter of 20 μm and a depth of 450 μm). By integrating atomic layer deposition (ALD), a conformal interdigital electrode structure is realized. Glass, as a key material in this capacitor, has outstanding insulating properties. This characteristic endows the capacitor with a high breakdown field strength exceeding 8.2 MV/cm, corresponding to a withstand voltage of 5000 V. High breakdown field strength and withstand voltage mean that the capacitor can handle high-voltage applications without breaking down easily, which is essential for power-intensive systems like high-voltage power supplies and some high-power pulse-generating equipment. Moreover, due to the low-loss property of glass, the capacitor can achieve an energy conversion efficiency of up to 95%. Such a high energy conversion efficiency ensures that less energy is wasted during the charge–discharge process, which is highly beneficial for energy-saving applications and systems that require high-efficiency energy utilization. Full article

La-doped Li_1.2Ni_0.13Mn_0.54Co_0.13O₂ cathode materials were successfully synthesized by the sol-gel method. The structure, morphology, element valence states, cyclic voltammetry, and cyclic properties were characterized to investigate the properties of the synthesized materials. The as-prepared La-doped Li_1.2Ni_0.13Mn_0.54Co_0.13O₂ materials exhibit well the crystalline hexagonal layered structures with lamellar-like particles featuring a rough surface. The optimal sample, designated as LLRMO-2 with 1/100 La³⁺ doping, delivers an impressive discharge capacity of 271.2 mAh g⁻¹ with a capacity retention of 87.8% after 100 cycles at the current density of 100 mA g⁻¹ compared with that of 203.5 mAh g⁻¹ with only 110.6 mAh g⁻¹ after 100 cycles for the pristine sample. Furthermore, the LLRMO-2 cathode exhibits a superior rate capability compared to the pristine sample and shows excellent cyclic performances with the capacity retention of 48.1% after 400 cycles. The voltage decay per cycle is only 1.60 mV, which is less than 3.70 mV of the pristine one. The enhanced capacity, rate capability, and cyclic performance observed in the La-doped Li-rich layered cathode can be attributed to the improved structural stability as well as the higher diffusion coefficient of lithium ions. These results suggest that the strategy of introducing La³⁺ into the transition metal slabs is an efficient approach for boosting electrochemical performances of Li-rich Mn-based cathode materials via enhancing structural stability. Full article

The efficient mass transport and enhanced accessibility of active sites are crucial for high-performance electrocatalysts in water splitting. Inspired by the hierarchical structure of natural wood, we engineered a monolithic electrocatalyst, cobalt nanoparticles encapsulated in nitrogen-doped carbon layers on carbonized wood (Co@NC/CW), by carbonizing wood to create a three-dimensional framework with vertically aligned macropores. The unique architecture encapsulates cobalt nanoparticles within in situ-grown nitrogen-doped graphene layers on wood-derived microchannels, facilitating ultrafast electrolyte infusion and anisotropic electron transport. As a result, the optimized freestanding Co@NC/CW electrode exhibits remarkable bifunctional activity, achieving overpotentials of 403 mV and 227 mV for the oxygen evolution reaction (OER) and hydrogen evolution reaction (HER), respectively, at a current density of 50 mA cm⁻². Furthermore, the integrated hybrid electrolyzer combining the HER and the OER delivers an impressive 50 A cm⁻² at a cell voltage of 1.72 V while maintaining a Faradaic efficiency near 99.5% and sustaining long-term stability over 120 h of continuous operation. Co@NC/CW also demonstrates performance in the complete decomposition of alkaline seawater, underscoring its potential for scalable applications. This wood-derived catalyst design not only leverages the natural hierarchical porosity of wood but also offers a sustainable platform for advanced electrochemical systems. Full article

The state of health (SoH) of lithium-ion batteries is critical for diagnosing the actual capacity of the battery. Data-driven methods have achieved impressive accuracy, but their sensitivity to sensor noise, missing samples, and outliers remains a limitation for their deployment. This paper proposes a robust, purely data-driven SoH estimation methodology that addresses these challenges. Our method uses a proposed non-iterative closed-form signal reconstruction derived from a modified Tikhonov regularization. Five new features were extracted from reconstructed voltage and temperature discharge profiles. Finally, a Huber regression model is trained using these features for SoH estimation. Six ageing scenarios built from the public NASA and Sandia National Laboratories datasets, under severe Gaussian noise conditions (10 dB SNR), were employed to validate our proposed approach. In noisy environments and with limited training data, our proposed approach maintains a competitive accuracy across all scenarios, achieving low error metrics, with an RMSE on the order of ${10}^{-4}$, an MAE on the order of ${10}^{-2}$, and a MAPE below 1%. It outperforms state-of-the-art deep neural networks, direct-feature Huber models, and hybrid physics/data-driven models. In this work, we demonstrate that robustness in SoH estimation for lithium-ion batteries is influenced by the choice of machine learning architecture, loss function, feature selection, and signal reconstruction technique. In addition, we found that tracking the time to minimum discharge voltage and the time to maximum discharge temperature can be used as effective features to estimate SoH in data-driven models, as they are directly correlated with capacity loss and a decrease in power output. Full article

Aqueous zinc-ion batteries (ZIBs) represent an emerging energy storage solution that offers significant advantages in terms of safety, cost-effectiveness, and longevity in cycling. Among the various materials available, manganese-based oxides stand out as the most promising options for cathodes due to their impressive theoretical specific capacity, suitable operating voltage, and abundant natural availability. In published reports, pre-embedding is frequently used to modify the layered cathode; however, non-electrochemically active molecular embedding often results in a decrease in battery capacity. In this paper, a hydrothermal method is employed to intercalate poly(o-phenylenediamine) (PoPD) into δ-MnO₂ (MO) to produce PoPD-MO cathode materials. Here, PoPD serves a dual role in the cathode: (1) PoPD is inserted into the interlayer of MO, providing support within the intercalation layer, enhancing material stability, increasing ionic storage sites, and creating space for more Zn²⁺ to be embedded, and (2) inserting PoPD into the interlayer structure of MO effectively expands the space between layers, thus allowing for greater ion storage, which in turn enhances the rate and efficiency of electrochemical reactions. Consequently, PoPD-MO shows remarkable cycling durability and adaptability in ZIBs, achieving a specific capacity of 359 mAh g⁻¹ at a current density of 0.1 A g⁻¹, and even under the strain of a high current density of 3 A g⁻¹, it maintains a respectable capacity of 107 mAh g⁻¹. Based on this, PoPD-MO may emerge as a new cathode material with promising applications in the future. Full article

With the growing demand for electric vehicles and consumer electronics, lithium-ion batteries with a high energy density are urgently needed. Lithium-rich manganese-based materials (LRMs) are known for their high theoretical specific capacity, rapid electron/ion transfer, and high output voltage. Constructing electrodes with a substantial amount of active materials is a viable method for enhancing the energy density of batteries. In this study, we prepare thick LRM electrodes through a dry process method of binder fibrillation. A point-to-line-to-surface three-dimensional conductive network is designed by carbon agents with various morphologies. This structural design improves conductivity and facilitates efficient ion and electron transport due to close particle contact and tight packing. A high-loading cathode (35 mg cm⁻²) is fabricated, achieving an impressive areal capacity of up to 7.9 mAh cm⁻². Moreover, the pouch cell paired with a lithium metal anode exhibits a remarkable energy density of 949 Wh kg⁻¹. Compared with the cathodes prepared by the wet process, the dry process optimizes the pathways for e⁻/Li⁺ transport, leading to reduced resistance, superior coulombic efficiency, retention over cycling, and minimized side reaction. Therefore, the novel structural adoption of the dry process represents a promising avenue for driving innovation and pushing the boundaries for enhanced energy density for batteries. Full article

Deep learning-based image classification techniques have been widely utilized in low-voltage AC series-type fault arc detection. However, the transformation of signals into images frequently leads to significant loss of current signal characteristics, thereby compromising arc recognition accuracy. Additionally, uncharacterized signal content may be lost due to multiple factors, including sensor bandwidth limitations, sensor-event distance, and the topological configuration of the circuit where the fault originated. To address this challenge, a novel framework for identifying series-type low-voltage AC fault arcs is presented, which integrates the Markov transfer field (MTF) with multi-feature fusion and an improved residual neural network (ResNet18). This approach employs fast Fourier transform (FFT) to compute magnitude and phase data and then converts the original current signals, magnitude spectrograms, and phase spectrograms into MTF images. An adaptive weighted averaging strategy is subsequently applied to fuse these MTF images, generating composite discriminative features that preserve both amplitude and phase information from the original signals. The proposed system incorporates a convolutional block-based attention mechanism (CBAM) into the ResNet18 architecture to enhance feature representation while reducing training complexity. Extensive experimental evaluations on a diverse dataset demonstrate that the developed method achieves an impressive recognition accuracy of 99.88% for series fault arcs. This result validates the effectiveness of the proposed framework in maintaining critical signal characteristics and improving detection precision compared to existing approaches. Full article

Electrochromic fabrics (ECFs) can be applied to wearable displays and military camouflage clothing, and they have great potential in developing wearable products. Current ECFs are often bulky, involve complicated processes, and have high production costs. In this study, we report a novel strategy for preparing electrochromic fabrics that require only a three-layer structure: cotton fabric as the substrate, poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS) as the electrochromic layer and the electrodes, and an ion-conducting film (ICF) bonded to the fabric by hot pressing. Compared with conventional ECFs, this method does not require the extra preparation of electrode layers on the fabric, as these layers affect the color-changing effect. Hot pressing eliminates the need for a complex sealing process and is more suitable for fabrics with poor wicking effects, which increases the method’s applicability. Cotton fabrics offer the value of biodegradability and are more environmentally friendly. Meanwhile, unlike carbon cloth, the fabric’s color does not interfere with the electrochromic effect. The ICF is non-liquid and can maintain the dryness of the fabric. Additionally, the ICF provides high-temperature protection up to 150 °C. The ECFs exhibit exceptional thinness at 161 µm and a lightweight construction with a 0.03 g/cm² weight. Furthermore, the ECFs exhibit a relatively long sustain time of 115 min without voltage, demonstrating impressive performance. Improved peel strength to 7.11 N is achieved through an improved hot-pressing process. The development strategy for ECFs can also be applied to other electrochromic substances, potentially advancing intelligent applications such as wearable fabrics and military camouflage while promoting rapid progress in electrochromic fabrics. Full article

The increasing energy demand and initiatives to lower carbon emissions have elevated the significance of renewable energy sources. Photovoltaic (PV) systems are pivotal in converting solar energy into electricity and have a significant role in sustainable energy production. Therefore, it is critical to implement maximum power point tracking (MPPT) controllers to optimize the efficiency of PV systems by extracting accessible maximum power. This research investigates the performance and comparison of various MPPT control algorithms for a standalone PV system. Several cases involving individual MPPT controllers, as well as hybrid combinations using two and three controllers, have been simulated in MATLAB/SIMULINK. The sensed parameters, i.e., output power, voltage, and current, specify that though individual controllers effectively track the maximum power point, hybrid controllers achieve superior performance by utilizing the combined strengths of each algorithm. The results indicate that individual MPPT controllers, such as perturb and observe (P&O), particle swarm optimization (PSO), and fuzzy logic (FL), achieved tracking efficiencies of 97.6%, 90.3%, and 90.1%, respectively. In contrast, hybrid dual controllers such as P&O-PSO, PSO-FL, and P&O-FL demonstrated improved performance, with tracking efficiencies of 96.8%, 96.4%, and 96.5%, respectively. This research also proposes a new hybrid triple-MPPT controller combining P&O-PSO-FL, which surpassed both individual and dual-hybrid controllers, achieving an impressive efficiency of 99.5%. Finally, a comparison of all seven cases of MPPT control algorithms is presented, highlighting the advantages and disadvantages of individual as well as hybrid approaches. Full article

Enhancing the performance of organic solar cells (OSCs) is essential for achieving sustainability in energy production. This study presents an innovative strategy that involves fine-tuning the thickness of the bulk heterojunction (BHJ) photoactive layer at the nanoscale to improve efficiency. The organic blend D18:L8-BO is utilized to capture a wide range of photons while addressing the challenge of minimizing optical losses from low-energy photons. The research incorporates SnO₂ and ZnO as electron transport layers (ETLs), with PMMA functioning as a hole transport layer (HTL). A comprehensive analysis of photon absorption, charge carrier generation, localized energy fluctuations, and thermal stability reveals their critical role in enhancing the efficiency of D18:L8-BO active films. Notably, introducing SnO₂ as an ETL significantly decreased losses and modified localized energy, achieving an impressive efficiency of 19.85% at an optimized blend thickness of 50 nm with low voltage loss (ΔV_oc) of 0.4 V within a J_sc of 28 mA cm⁻² by performing an optoelectronic simulation employing “Oghma-Nano 8.1.015” software. In addition, the SnO₂-based structure conserved 88% of the PCE at 350 K compared to room temperature PCE, which describes the high thermal stability of this structure. These results demonstrate the potential of this methodology in improving the performance of OSCs. Full article

High-voltage (HV) cables are increasingly used in urban power grids, and their safe operation is critical to grid stability. Previous studies have analyzed various defects, including the open circuit in the sheath loop, the flooding in the cross-bonded link box, and the sheath grounding fault. However, there is a paucity of research on the defect of the reverse direction between the inner core and the outer shield of the coaxial cable. Firstly, this paper performed a theoretical analysis of the sheath current in the reversed-connection state and established a simulation model for verification. The outcomes of the simulation demonstrate that there are significant variations in the amplitudes of the sheath current under different reversed-connection conditions. Consequently, a feature vector was devised based on the amplitude of the sheath current. The support vector machine (SVM) was then applied to diagnose the reversed-connection defects in the HV cable cross-bonded grounding system. The artificial rabbits optimization (ARO) algorithm was adopted to optimize the SVM model, attaining an impressively high diagnostic accuracy rate of 99.35%. The effectiveness and feasibility of the proposed algorithm are confirmed through the analysis and validation of the practical example. Full article

With growing environmental concerns and the need for sustainable energy, multifunctional materials that can simultaneously address water treatment and clean energy production are in high demand. In this study, we developed a cost-effective method to synthesize zinc oxide (ZnO) nanowires via the anodic oxidation of zinc foil. By carefully controlling the anodization time, we optimized the Zn/ZnO-5 min electrode to achieve impressive dual-function performance in terms of effective photoelectrocatalysis for water splitting and waste water treatment. The electrode exhibited a high photocurrent density of 1.18 mA/cm² at 1.23 V vs. RHE and achieved a solar-to-hydrogen conversion efficiency of 0.55%. A key factor behind this performance is the presence of surface defects, such as oxygen vacancies (OVs), which enhanced charge separation and boosted electron transport. In tests for waste water treatment, the Zn/ZnO-5 min electrode demonstrated the highly efficient degradation of methylene blue (MB) dye, with a reaction rate constant of 0.4211 min⁻¹ when exposed to light and a 1.0 V applied voltage significantly faster than using light or voltage alone. Electrochemical analyses, including impedance spectroscopy and voltammetry, further confirmed the superior charge transfer properties of the electrode under illumination, making it an excellent candidate for both energy conversion and pollutant removal. This study highlights the potential of using simple anodic oxidation to produce scalable and efficient ZnO-based photocatalysts. The dual-function capability of this material could pave the way for large-scale applications in renewable hydrogen production and advanced waste water treatment, offering a promising solution to some of today’s most pressing environmental and energy challenges. Full article

Dual-ion batteries (DIBs) were demonstrated as a promising technology for large-scale energy storage due to their low cost, recyclability, and impressively fast charge capability. Graphite as a commonly used cathode material in DIBs, however, suffers from poor compatibility with commercial Li-ion electrolytes and graphite anodes, making it difficult to directly utilize the well-established infrastructure for Li-ion batteries. Herein, we report a small aromatic amine molecule 4,4′,4″-tris(diphenylamino)triphenylamine (N4) functioning as a compatible anion host in the EC-containing Li-ion electrolyte. With an average discharge voltage of 3.6 V (vs. Li⁺/Li), the N4 electrode delivers a reversible specific capacity of 108 mAh/g, which is much higher than 29 mAh/g for the graphite cathode at the same condition. The high capacity retention of 91.3% was achieved after 500 cycles at 1 A/g. The N4 electrode also exhibited good rate performance. Via different characterization techniques like Fourier transform infrared spectroscopy and X-ray photoelectron spectroscopy, the energy storage mechanism of N4 was revealed as a conversion between amine and quaternary amine cations, accompanied by PF₆⁻ (de-)insertion. As consequences, the assembled N4||graphite DIB w showed a high discharge capacity of 90 mAh/g within 1.5–4.1 V, and good cycling stability with a 98% capacity retention after 40 cycles. Decent rate performance was achieved in the N4||graphite DIB as well. This work provides new insights into designing a compatible anion host for affordable DIBs. Full article