Frontiers of Chemical Science and Engineering最新文献

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.

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.

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, highperformance industrial porous materials.

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.

Membrane gas separation is an energy-efficient approach to extract helium from natural gas. However, the limited separation performance shown as Robeson’s upper bound has hindered the techno-economic feasibility. This study introduces an advanced copolyimide membrane engineered for He extraction from natural gas. The membranes were facilely achieved by dip-coating the α-alumina substrates in the copolyimide solution followed by in situ thermal rearrangement. In addition to the rigid 5-amino-2-(4-aminobenzene)benzimidazole segments, the active ortho-hydroxyl groups were converted to benzoxazole rings, contributing to extra micropores. The membrane showed an improved mixture selectivity of 120 and He permeance of 23.5 GPU, far surpassing the performance of benchmark membranes for helium separation over CH₄. The membrane also demonstrated long-term stability as evidenced by the continuous operation over 250 h. Additionally, the membrane exhibited resistance to impurities such as CO₂ and C₂H₆, enduring the asymmetric membranes promising for practical helium extraction from natural gas.

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.

An anaerobic digester of sewage sludge or agro-industrial waste produces biogas and ammonia-rich digestate. Three H₂-producing processes exist: dry reforming of methane (from biogas), catalytic decomposition of methane (from biogas after CO₂ capture), and catalytic decomposition of ammonia (from digestate). Dry reforming of methane offers the best syngas yield at 700 °C and for a 50–50 vol % CH₄/CO₂ biogas. Catalytic decomposition of methane achieved a H₂ yield of 95%. Finally, the digestate was stripped and NH₃ was further completely decomposed into H₂ and N₂, for a complete NH₃ conversion at 650 °C. A methanol valorization case study of a wastewater treatment plant of 300000 person equivalents with an anaerobic digester is examined. The methanol production from syngas (H₂/CO) and H₂ product streams is simulated using Aspen Plus®. This anaerobic digester process will daily generate 4485 m³ CH₄, 2415 m³ CO, and 320 kg NH₃. The methanol production will be 183 kg·h⁻¹ (1600 t·y⁻¹). The additional H₂ from ammonia’s catalytic decomposition (631 m³·d⁻¹) can be valorized with excess biogas in the anaerobic digester-associated combined heat and power unit. Due to a significantly higher ammonia concentration in manure, catalytic decomposition of ammonia will produce more H₂ if manure would be co-digested.

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.