Natural esters exhibit excellent flame retardant and biodegradability, which help minimize power accidents and reduce environmental impact. These qualities make natural esters a promising alternative to conventional transformer insulating oils. However, the practical applications of natural esters in power equipment have been significantly restricted by their inherent limitations, including elevated viscosity, high dielectric loss, and poor oxidative stability. Nano-modification technologies present a novel methodological approach to solve these inherent constraints. A systematic analysis of the latest research developments in nano-modified natural ester transformer oils is provided in this review. The properties of various natural esters are examined, and their suitability as base fluids is evaluated, while the modification effects and mechanisms of typical nano-additives are comprehensively reviewed. The key role of nano-modification technology in improving the overall performance of natural esters is elucidated through detailed analysis of how nanoparticles influence physical properties, dielectric properties, and oxidative stability. In addition, the practical challenges facing nano-modification technology are addressed, providing valuable theoretical guidance for future developments in this field.

The water-gas shift (WGS) reaction plays a pivotal role in various industrial processes, particularly in hydrogen production and carbon monoxide removal. As global energy demands rise and environmental concerns intensify, the development of efficient and sustainable catalysts for the low-temperature WGS (LT-WGS) reaction has gained significant attention. This review focuses on recent advancements in water-gas-shift catalyst design for low-temperature conditions and emerging renewable energy-driven catalytic processes, such as photocatalysis, electrocatalysis, and plasma catalysis for the WGS reaction, which are less commonly explored in existing reviews. We systematically analyze mechanisms studies of LT-WGS, rational catalyst design strategies, and recent frontier advances in the development of highly efficient catalysts. Furthermore, this review provides actionable insights for refining catalyst architectures, enhancing operational efficiency, elucidating reaction pathways, and pioneering hybrid technologies, all contributing to further advancements in this field.

As economic globalization accelerates, biofuel supply chain systems are becoming increasingly complex and large-scale, with businesses facing rising uncertainties and an increased risk of disruptions. Designing resilient biofuel supply chains that can withstand these risks while maintaining security and competitiveness has become a major concern and an urgent issue for enterprises. However, due to the lack of effective methods for quantifying and evaluating supply chain disruption risks, existing supply chain design approaches fail to adequately address the problem of mitigating such risks. To address this issue, this paper proposes an improved Node Disruption Impact Index with adjustable parameters, based on cost changes in the supply chain caused by disruptions at different nodes. This index enables the identification of nodes with varying risk levels and provides a means for evaluating disruption impact. The adjustable parameters can be tailored to meet the needs of supply chain enterprises, facilitating a trade-off between economic benefits and supply chain resilience. Furthermore, the paper applies the index to the fluctuation range of node uncertainties and develops a two-stage stochastic programming supply chain optimization model. This model incorporates a mechanism for addressing potential high disruption risks. By applying the model to a biofuel supply chain case in Guangdong Province, the results demonstrate that, when high-risk nodes are interrupted, the proposed model outperforms traditional models in terms of cost and market delivery rate. This confirms the effectiveness of the method in the optimization design of resilient supply chain.

Zinc-bromine flow batteries are considered as one of the most promising energy storage devices with high energy density and low production price. However, its practical application is hampered by the short cycle life, which is mainly due to the uneven zinc deposition and the shuttle effect of bromide ions. Modification of membranes, an important part of zinc-bromine flow batteries, is a common approach to address these issues. In this study, inspired by the adhesion mechanism of filament proteins secreted by marine mussels, we propose a novel method for modifying polyethylene membranes with polydopamine. The self-polymerization of dopamine on a polyethylene membrane surface is simple and mild compared to traditional methods. This dopamine-based modification enhances the hydrophilicity of polyethylene membrane, improves ion transport, and reduces the pore size of the membranes, effectively blocking bromine ion shuttling. Additionally, polydopamine modification promotes uniform zinc deposition, further improving the battery performance. Consequently, the resulting PDA@PE-24 membrane demonstrates a significant improvement in both voltage and energy efficiencies, reaching 83.5% and 79.7%, respectively, under 20 mA·cm^–2, compared to the 80.3% and 76.5% voltage and energy efficiencies, respectively, for unmodified polyethylene membranes. Furthermore, the cycle life of a single cell increased 4-fold, operating continuously for more than 2000 h.

The hybrid material based on polyelectrolyte complexes of chitosan with oxycompounds of cobalt and nickel was electrodeposited on a stainless steel plate using the method of non-stationary electrolysis. The hybrid material layer was investigated by scanning electron microscopy, atomic force microscopy, transmission electron microscopy, X-ray diffraction, X-ray photoelectron spectroscopy, Brunauer-Emmett-Teller method, Fourier transform infrared spectroscopy, and Raman spectroscopy. The electrocatalytic properties of the hybrid material were studied in the hydrogen evolution reaction in alkaline electrolyte (1 mol·L⁻¹ NaOH). It was determined that during the initial four-hour period of the hydrogen evolution process, the overpotential underwent a substantial decline, remaining constant for a minimum of 17 h thereafter, from 289 up to 210 mV at −10 mA·cm⁻². After a long-term hydrogen evolution, the activity of the hybrid material electrode exceeded hydrogen evolution reaction activity by 20% Pt/C commercial catalyst at a high current density of −100 mA·cm⁻².

In this work, a novel nitrogen-doped biochar-supported nanoscale ferrous sulfide composite (nFeS@NBC) was fabricated by pyrolyzing corn straw pretreated with Mohr’s salt through a one-step carbothermic reduction process, which was applied in the efficient disposal of hexavalent chromium (Cr(VI))-containing wastewater. The key effects of impregnation ratio and pyrolysis temperature on the properties and removal performance of nFeS@NBC for Cr(VI) were subsequently investigated. The properties of nFeS@NBC were characterized through a series of techniques. It indicated that FeS nanoparticles were successfully loaded and –NH₂ functional groups effectively formed on the biochar surface, which enhanced the removal performance of nFeS@NBC for Cr(VI) from wastewater. The removal performance of nFeS@NBC for Cr(VI) was systemically evaluated at different experimental conditions and in the presence of major co-existing ions. Adsorption kinetics was best suited to the pseudo-second-order model. Additionally, Langmuir isotherms model could well explain the adsorption experiment data for the removal of Cr(VI) by nFeS@NBC with the highest adsorption capacity of 373.85 mg·g^–1. According to the thermodynamic study, nFeS@NBC dominated the adsorption of Cr(VI) through an endothermic and spontaneous process. The adsorption and reduction served as the main removal mechanisms of nFeS@NBC for aqueous Cr(VI). nFeS@NBC could be used repetitively for its regeneration. Thus, the above results showed that it was feasible and efficient to remove Cr(VI) by nFeS@NBC, providing a potential green material for environmental remediation.

This article presents a novel, facile method for studying the kinetics of liquid-phase synthesis of precious metal nanoparticles. The method is particularly suitable for use in concentrated solutions and under conditions involving gas purging and medium stirring. It is based on the continuous measurement of changes in the solution’s color components and the potential of an indicator electrode during the synthesis process. The method was applied to investigate the effect of solution pH on the kinetics of polyol synthesis of Pt nanoparticles and Pt/C electrocatalysts. The obtained Pt/C electrocatalysts demonstrate high structural-morphological and electrochemical characteristics, surpassing commercial analogs. The simplicity and efficiency of the “kinetic control” technique makes it promising for use in various liquid-phase synthesis technologies.

Electrochemical impedance spectroscopy plays a crucial role in monitoring the state of health of lithium-ion batteries. However, effective feature extraction often relies on limited information and prior knowledge. To address this issue, this paper presents an innovative approach that utilizes the gramian angular field method to transform raw electrochemical impedance spectroscopy data into image data that is easily recognizable by convolutional neural networks. Subsequently, the convolutional block attention module is integrated with bidirectional gated recurrent unit for state of health prediction. First, convolutional block attention module is applied to the electrochemical impedance spectroscopy image data to enhance key features while suppressing redundant information, thereby effectively extracting representative battery state features. Subsequently, the extracted features are fed into a bidirectional gated recurrent unit network for time series modeling to capture the dynamic changes in battery state of health. Experimental results show a significant improvement in the accuracy of state of health predictions, highlighting the effectiveness of convolutional block attention module in feature extraction and the advantages of bidirectional gated recurrent unit in time series forecasting. This research provides an attention mechanism-based feature extraction solution for lithium-ion battery health management, demonstrating the extensive application potential of deep learning in battery state monitoring.

Diabetes mellitus has emerged as a globally prevalent chronic metabolic disorder, characterized by persistent hyperglycemia and associated complications. Continuous glucose monitoring is a technology that continuously monitors blood glucose by implanting microelectrodes under the skin, which is the most common method of diabetes treatment. Due to the discomfort caused by frequent blood collection through traditional blood glucose monitoring, continuous glucose monitoring has become a major research focus, mainly relying on blood glucose biosensors. In this paper, the progress of electrochemical biosensors in continuous glucose monitoring systems and the characteristics of electrochemical biosensors in different stages of development were mainly summarized. The commonly used enzyme immobilization technology aiming to solve the problems of enzyme leakage, activity decrease, and sensitivity decline caused by long-term subcutaneous implantation of blood glucose biosensors were discussed, meanwhile, the advantages and disadvantages of the different methodologies were also compared. These methodological advancements provide critical insights for optimizing biosensor stability and durability, establishing a theoretical foundation for developing next-generation implantable continuous glucose monitoring devices with enhanced clinical performance.

Lightweight and robust polypropylene foams are essential for resource efficiency; however, the poor foaming ability of polypropylene remains a significant challenge in developing high-performance foams. This study proposes a scalable and cost-effective strategy that integrates in situ fibrillation reinforcement with chemical foam injection molding. Nanofibrillar polypropylene/polyamide 6 composites were fabricated via twin-screw compounding and melt spinning. For the first time, polyamide 6 nanofibrils were observed to exhibit selective dispersion with distinct morphologies in the skin and core layers of in situ fibrillation injection-molded samples. The incorporation of maleic anhydride-grafted polypropylene induced a 70% reduction in polyamide 6 nanofibril diameter. Rheological and crystallization analyses demonstrated that polyamide 6 fibrils significantly enhance polypropylene viscoelasticity and crystal nucleation rate, thereby improving foamability. Compared to polypropylene foam, in situ fibrillation composite foam exhibited a refined and homogeneous cellular structure, with a cell size of 61 μm and a cell density of 5.8 × 10⁵ cells·cm^–3 in the core layer, alongside elongated cells in the skin layer. The synergistic effects of polyamide 6 nanofibrils and maleic anhydride-grafted polypropylene resulted in a 15.4% weight reduction and 100% enhancement in impact strength compared to polypropylene foam. This work provides new insights into developing lightweight, high-performance industrial porous materials.