Durable Operation Research Articles

Activation of ammonium oxalate on dandelion-derived nitrogen-doped carbon for electrocatalytic oxygen reduction reaction

Development of electrocatalysts with high catalytic activity for the oxygen reduction reaction (ORR) plays an important role in sustainable energy technology. Herein, a carbon-based electrocatalyst was prepared by pyrolyzing the dandelion straw, accompanied with the activation of ammonium oxalate (AO) for the first time. Based on the physical characterization, the DAO-1100 exhibits a well-developed pore structure, rich morphologies, high surface area, high graphitization degree, as well as high total content of pyridinic nitrogen and graphitic nitrogen. Therefore, DAO-1100 shows excellent electrocatalytic activity for ORR at the onset potential of 0.991 V, half-wave potential of 0.883 V and limiting diffusion current of 5.30 mA·cm−2 approximately, in comparison to those of the Pt/C catalyst. DAO-1100 catalyzes the ORR through a 4 e- pathway like Pt/C catalyst. In addition, it also possesses the better operational durability and catalytic selectivity than those of Pt/C catalyst. Therefore, ammonium oxalate, serving as a low-cost, efficient activator, can efficiently promote the transformation of abundant dandelion straw to metal-free biochar catalysts.

Integrating ensemble learning and meta bagging techniques for temperature-specific State of Health prediction in Lithium-ion Batteries

Accurately predicting the State of Health (SOH) of lithium-ion batteries is crucial in the field of battery technology to guarantee operational dependability and durability. This study introduces a novel methodology that integrates ensemble learning and meta-bagging techniques to enhance the precision of SOH prediction, particularly in scenarios characterized by fluctuating temperature conditions. We start our methodology by conducting an extensive data-gathering phase, specifically targeting crucial variables: temperature, voltage, current, and capacity. Subsequently, a thorough data preparation stage ensues, encompassing tasks such as cleansing, standardization, and curating relevant features, with particular attention given to temperature characteristics. Next, we employ a temperature-adaptive ensemble learning model that combines different prediction algorithms, such as Linear Regression (LR) and Long Short-Term Memory (LSTM) networks. These algorithms are trained on temperature-stratified data subsets using a Meta-Bagging Estimator (MBE). This strategy enhances the precision of predictions and the ability to overcome the obstacle of temperature changes impacting battery performance. The efficacy of the ensemble model is thoroughly assessed utilizing diverse performance criteria, showcasing its improved predictive capability compared to conventional approaches. Our findings indicate that this customized strategy is better equipped to manage the intricate dynamics of lithium-ion battery behavior, resulting in more dependable and precise assessments of battery SOH. This work substantially contributes to battery health monitoring and can significantly advance battery management systems.

New insights of the imprint at the catalyst-layer/ microporous-layer interface in PEMFC after heavy duty operation of commercial vehicles

Structural degradation and property decay of membrane electrode assemblies (MEAs) are primary causes for the stack performance and lifetime degradation. This study particularly investigates the structural damage and properties evolution of the catalyst-layer/microporous-layer (CL/MPL) interface in the MEA by conducting real-vehicle heavy-duty operational durability test and interfacial structure characterization. This research presents the first report and revelation of the causes and effects of CL/MPL interface imprints, and provides targeted advice for relieving MEA interfacial degradation. Results indicate that excessive assembly stress and stress variation during operation of stack causing the detachment of MPL materials at the region below the bipolar plate ridges is the essential cause of the imprints. The average surface contact angles of the aged CLs generally increase and the imprinted region exhibit stronger hydrophobicity than non-imprinted region due to the attachment of MPL materials. While the opposite is observed in MPL. Carbon corrosion induce structural degradation of the CL/MPL interface, leading to significant loss of carbon support and hydrophobic agent. The surface of aged CL become rougher and the pore size become more larger compared to the fresh CL. The formation of the interface imprint makes the contact between CL and MPL at the imprint region tighter, which reduces the interface resistance and inhibits the increase in ohmic polarization.

A 2D/3D hierarchical hybrid enables energy-saving hydrogen production coupled with glycerol and urea electro-oxidation

The design and development of high-performance electrocatalysts is crucial to improve the utility of anodic reaction for energy-saving hydrogen production. Herein, we present a novel catalyst with 2D/3D multistage structure for the electro-oxidation of renewable biomass and harmful waste to assist hydrogen generation. The hierarchical configuration of NiO/CoO nanosheets interconnected by hollow carbon spheres, leveraging both 2D and 3D advantages. This structure provides rich surface and edge active sites as well as affluent electron and mass transfer pathways, resulting in the accelerated dynamics of electro-oxidation. The hollow carbon spheres serve as a buffering agent to alleviate the strain caused by repetitive redox reactions during electrolysis, thereby bestowing exceptional structural and chemical stability for prolonged operational durability. Additionally, the multiple continuous hetero-interfaces between NiO and CoO, NiO and carbon as well as CoO and carbon can ensure the fast electron transport, leading to the expedited reaction kinetics with the synergistic effect of phase engineering between NiO, CoO and carbon shell. As a result, the 3D carbon shells jointed 2D NiO/CoO hybrids demonstrate promising catalytic activities on electro-oxidation for energy-efficient hydrogen production (∼100 %FE) coupled with urea oxidation and formic acid synthesis with excellent selectivity (95.40 %) and satisfied faradic efficiency (91.6 %).

Effects of the Dynamic Loading Frequency on Performance of the Proton Exchange Membrane Water Electrolysis.

Green hydrogen production via PEM water electrolysis is challenged by fluctuating input power when coupled with renewable energy sources. This study investigates the effects of dynamic loading frequencies on membrane electrode assembly (MEA) performance and durability. We found that higher loading frequencies facilitate the growth of the oxide layer of Ti porous transport layer (Ti-PTL) due to increased duration in the voltage spike region. These thicker and coarser oxide layers directly induce cracks and delamination in the anodic catalyst layers by spontaneously adsorbing an ionomer. These changes negatively impact the interface contact quality and anodic electrochemical active area, ultimately reducing the performance of the MEA, with higher frequencies accelerating this degradation. Additionally, applying a Pt coating to PTL effectively mitigates these adverse effects. This work highlights the importance of dynamic loading studies and reveals that effective management of the Ti-PTL and catalyst/PTL interface is necessary to achieve long-term operational durability of PEM water electrolysis.

Concurrent Regulation of Surface Topography and Interfacial Physicochemistry via Trace Chelation Acid Additives toward Durable Zn Anodes

AbstractElectrolyte additive engineering is a feasible protocol in improving Zn anode stability. Typical additive designs center on the regulation of Zn deposition; nevertheless, versatile additives are urgently requested to comprehensively manage the surface landscape, interface physicochemistry, and by‐product elimination. Here, a straightforward strategy is presented to meet such needs employing an environmentally‐friendly chelator, hydroxyethyl‐ethylenediaminetriacetate acid (HEDTA), as an additive for ZnSO4 electrolyte. Throughout theoretical computations and experimental investigations, it is demonstrated that protons released from the gradual ionization of HEDTA during rest periods aid in the mild engraving of the Zn surface. Both the amino and carboxyl groups of HEDTA⁻ can be protonated, which effectively buffers the interfacial pH value in the entire battery lifespan and eliminates the formation of by‐products. The HEDTA− anions can also adsorb onto the Zn surface, helping facilitate Zn2⁺ mass transfer and accelerate the desolvation process. Benefiting from the synchronous modulation of surface topography and interfacial physicochemistry, the assembled half cells affording HEDTA additive maintain a durable operation of up to 8821 cycles at 5.0 mA cm−2/1.0 mAh cm−2. Additionally, symmetric cells manifest stable cycling for over 4600 h at 0.5 mA cm−2/0.25 mAh cm−2.

Synchronous Modulation of H-bond Interaction and Steric Hindrance via Bio-molecular Additive Screening in Zn Batteries.

In addressing challenges such as side reaction and dendrite formation, electrolyte modification with bio-molecule sugar species has emerged as a promising avenue for Zn anode stabilization. Nevertheless, considering the structural variability of sugar, a comprehensive screening strategy is meaningful yet remains elusive. Herein, we report the usage of sugar additives as a representative of bio-molecules to develop a screening descriptor based on the modulation of the hydrogen bond component and electron transfer kinetics. It is found that xylo-oligosaccharide (Xos) with the highest H-bond acceptor ratio enables efficient water binding, affording stable Zn/electrolyte interphase to alleviate hydrogen evolution. Meanwhile, sluggish reduction originated from the steric hindrance of Xos contributes to optimized Zn deposition. With such a selected additive in hand, the Zn||ZnVO full cells demonstrate durable operation. This study is anticipated to provide a rational guidance in sugar additive selection for aqueous Zn batteries.

Novel Catalyst Formulations for Enhanced Fuel Cell Efficiency

The quest for enhanced fuel cell efficiency is pivotal in advancing sustainable energy solutions. This paper investigates novel catalyst formulations aimed at improving the performance and longevity of fuel cells. Traditional catalysts, primarily based on precious metals such as platinum, present challenges related to cost and resource availability. In response, this study explores non-precious metal catalysts (NPMCs), composite materials, and nanostructured catalysts, which have shown promising results in recent research. Through rigorous experimental methods, including synthesis and characterization techniques, we evaluate the catalytic activity and efficiency of these novel formulations. The findings demonstrate significant improvements in power output and operational durability compared to conventional catalysts. Mechanistic insights into the reaction dynamics reveal how these new materials enhance performance metrics such as current density and voltage output. An economic analysis highlights the potential for scalability and cost-effectiveness of these innovative catalysts in commercial applications. This research underscores the critical role of catalyst design in optimizing fuel cell technology and sets the stage for future explorations aimed at overcoming existing limitations in the field. By leveraging advanced materials and formulations, we aim to contribute to the development of next-generation fuel cells with enhanced efficiency and practicality.

An active and durable ammonia cracking layer for direct ammonia protonic ceramic fuel cells

Ammonia protonic ceramic fuel cells (NH3-PCFCs) are highly appealing energy conversion technologies due to their high efficiency, environmental responsibility, and benign safety features. Nonetheless, progress in NH3-PCFCs is notably impeded by the restricted performance and insufficient lifespan of standard Ni-cermet anodes for ammonia cracking, especially at 550 °C or below. Herein, we report an efficient ammonia cracking layer with a formula of xCo3O4/100-xBaZr0.8Y0.2O3-δ (Co/BZY) (x=10, 20, 30), which is deposited onto the Ni-BaZr0.1Ce0.7Y0.1Yb0.1O3−δ (BZCYYb) anode to significantly enhance the NH3 decomposition catalytic activity, thereby improving the performance and durability of NH3-PCFCs at low temperatures. The cells with the addition of a 20Co/80BZY anode catalytic layer (ACL) exhibit low area-specific resistance (ASR) and promising operational longevity under NH3 conditions. At 550°C, the NH3-PCFCs with a 20Co/80BZY ACL exhibit a high peak power density of 0.626 W cm−2 and promising operation durability. This study provides important guidance for constructing high-performance and durable NH3-PCFCs.

COFs functionalized self-cleaning loose nanofiltration membranes for efficient dye/salt separation

In spite of the fact that loose nanofiltration membrane (LNFM) technology has certified inspiring prospects in the remediation of dyestuff-comprising wastewater, omnipresent membrane fouling deteriorates its separation competence and hinders its practical application. Herein, a neoteric LNFM with finely tuned anti-fouling and self-cleaning properties was manufactured via the reformative phase inversion procedure integrated with the correctional interfacial polymerization process. By altering the casting solution (i.e., adding nano additives) and coagulation bath (i.e., applying melamine aqueous solution rather than pure water) recipes, the porphyrin-based covalent organic framework (COF-366) and melamine monomers were introduced into the polymeric matrix ingeniously in one step, participating the subsequent interfacial polymerization reaction straightly. The COF-366 with photocatalytic degradation performance and hydrophilicity bestows the resultant LNFM with superior decomposing capacity for organic micro-pollutants under visible light irradiation and better operation durability. Moreover, this substrate-confined amine diffusion combined with the high polarity of melamine enables the formation of a thinner nanofilm for easy mass transport. The best-performing LNFM invented in this work exhibited a high water permeance up to 65 L m−2 h−1 bar−1, excellent dye retention (95.7% against methyl blue), and salt/dye discrimination (27.1 for methyl blue and Na2SO4 selectivity) abilities. Eventually, the membrane could recover to original separation efficacy after the cyclic degradation testing. Overall, this work demonstrates an extensive perspective to pioneer an advanced self-cleaning membrane for dye/salt fractionation.

Supersaturated Doping-Induced Maximized Metal-Support Interaction for Highly Active and Durable Oxygen Evolution.

Metal-support interaction (MSI) is pivotal and ubiquitously used in the development of next-generation catalysts, offering a pathway to enhance both catalytic activity and stability. However, owing to the lattice mismatch and poor solubility, traditional catalysts often exhibit a metal-on-support heterogeneous structure with limited interfaces and interaction and, consequently, a compromised enhancement of properties. Herein, we report a universal and tunable method for supersaturated doping of transition-metal carbides via strongly nonequilibrium carbothermal shock synthesis, characterized by rapid heating and swift quenching. Our results enable ∼20 at. % Ni2FeCo doping in Mo2C, significantly surpassing the thermodynamic equilibrium limit of <3 at. %. The supersaturation ensures more catalytically active NiFeCo doping and sufficient interaction with Mo2C, resulting in the maximized MSI (Max-MSI) effect. The Max-MSI enables outstanding activity and particularly stability in alkaline oxygen evolution reaction, showing an overpotential of 284 mV at 100 mA cm-2 and stable for 700 h, while individual Ni2FeCo and Mo2C only last less than 70 and 10 h (completely dissolved), respectively. In particular, the SD-Mo2C catalyst also exhibits excellent durability at 100 mA cm-2 for up to 400 h in 7 M KOH. Such a significantly improved stability is attributed to the supersaturated doping that led to each Mo atom strongly binding with adjacent heteroatoms, thus elevating the dissolution potential and corrosion resistance of Mo2C at a high current density. Additionally, the highly dispersed NiFeCo also facilitates the formation of dense oxyhydroxide coating during reconstruction, further protecting the integrated catalysts for durable operation. Furthermore, the synthesis has been successfully scaled up to fabricate large (16 cm2) electrodes and is adaptable to nickel foam substrates, indicating promising industrial applications. Our strategy allows the general and versatile production of various highly doped transition-metal carbides, such as Ni2FeCo-doped TiC, NbC, and W2C, thus unlocking the potential of maximized or adjustable MSI for diverse catalytic applications.

Calculation of Maximum Permissible Load of Underground Power Cables–Numerical Approach for Systems with Stabilized Backfill

The maximum permissible load of underground power cables (known in U.S. engineering as “ampacity”) is a function of many parameters, in particular, the thermal resistivity of the native soil. If this resistivity is relatively high, thermal/stabilized backfill is applied, i.e., another material is placed around the cables, providing favourable conditions for heat transfer to the environment. It has a positive impact on the reliability of the power supply and favours the operational durability of the cables. In design practice, however, there is a difficult task—correct determination of the ampacity of the cable line depending on the thermal parameters and the geometry of the backfill. Therefore, this article presents the results of a numerical analysis to determine the ampacity of cable lines in which stabilized backfill is used. A new mathematical relationship is proposed that allows the correction of the ampacity of cable lines depending on their cross-section as well as the thermal and geometric parameters of the cable surroundings.

Application of Machine Learning Methods to Analyze the Dependence of Vibration Acceleration Signals on the Tightening Forces of Bolted Connections

The article is devoted to the application of machine learning methods for the analysis of vibration acceleration signals in bolted joints that occur under impact. The relevance of the work is due to the need to ensure the reliability and operability of bolted joints under loads. One of the promising areas of non-destructive testing is the analysis of the characteristics of vibration acceleration signals that change with changes in the state of structures, for example, with an increase in the tightening torque. This allows for the timely detection of possible defects and the prevention of emergency situations, ensuring the safety and durability of structures. The vibration acceleration signals under impact action on a bolted joint were analyzed. After calculating the signal characteristics, data sets were formed, including the values of tightening torques and the corresponding calculated signal characteristics, a search for a correlation between the tightening torque of bolted joints and the obtained set of vibration signal parameters was carried out. The frequency spectrum of signals, the Higuchi fractal dimension, detrended fluctuations, spectral power density and position of signal peaks were calculated. Machine learning models such as decision trees, the nearest neighbor method, the k-means method and neural networks were used for the analysis. For these methods, an optimal set of parameters correlating with the tightening torque was searched for. The main results show that machine learning methods are effective in classifying signals and finding correlations with stress state parameters. They allow us to detect the relationship between a set of signal characteristics and tightening torque, which opens up opportunities for more accurate and reliable monitoring of the condition of bolted connections. This should help to increase their operational reliability and durability, as well as reduce the likelihood of failures and accidents. The use of such methods can improve the quality of monitoring and diagnostics of bolted connections.

A Direct Current Self-Sustained Moisture-Electric Generator with 1D/2D Hierarchical Nanostructure for Continuous Operation of Off-Grid Electronics.

Ubiquitous moisture is a colossal reservoir of clean energy, and the emergence of moisture-electric generators (MEGs) is expected to provide direct power support for off-grid electronic devices anytime and anywhere. However, most MEGs rely on auxiliary energy storage devices and rectifier circuits to drive small electronic devices, which hinder scalability and widespread deployment, and the development of direct current (DC) MEGs with high power output that can directly drive off-grid electronic devices is highly promising but challenging. Herein, a self-sustained moisture-electric generator (SMEG) with a hierarchical nanostructure based on one-dimensional (1D) negatively charged nanofibers and two-dimensional (2D) conductive nanosheets was demonstrated to generate continuous DC electricity from atmospheric humidity. Sulfation of bacterial cellulose nanofibers lowers the surface potential and increases the surface charge energy, and reduced graphene oxide (rGO) provides a conduction pathway for electrons. The hierarchical nanostructures constructed by the combination of 1D nanofibers and 2D nanosheets endow the SMEG with self-sustained moisture gradients and structural anisotropy, which force the generation of a pseudocurrent. This combination also constructs microcapacitors that further enhance the moisture-electric power output. The SMEG can generate a continuous voltage in excess of 0.54 V for over 2160 h, with a power density of about 822 μW cm-3, demonstrating excellent operational durability. This research provides a feasible solution for the development of sustainable, versatile, and efficient power supplies for off-grid self-powered devices.

A multifunctional biomass-based solar interface evaporator with feather-like structure for efficient selective transport, antibacterial properties, salt resistance, and oil-fouling prevention

Solar interface evaporation technology has gained prominence as an efficient, low-cost, and CO2-neutral method for water purification. However, the development of interface evaporators with high evaporation efficiency, durability, and environmentally friendly, cost-effective materials remains a significant challenge. In this study, we fabricated a novel solar-powered hydrogel membrane using sodium alginate (SA), reduced graphene oxide (RGO), and vegetable-tanned collagen fibers (CF). Utilizing a dual-structural engineering design strategy, which incorporates surface patterning and microfiber channel construction, the resulting sodium alginate/collagen fibers/reduced graphene oxide (CF/SA/RGO) composite membranes exhibited remarkable selective mass transport efficiency. The inclusion of vegetable-tanned collagen fibers notably enhanced the flow rate of free water within the CF/SA/RGO membranes. Moreover, the reduction in water evaporation enthalpy increased with successive GO reduction cycles, thereby further boosting the evaporation rate. The CF/SA/RGO membranes demonstrated an outstanding evaporation efficiency of 2.88 kg m−2 h−1, ion rejection rates of 98 % for K+, Ca2+, Na+, and Mg2+, and a dye removal efficiency of 99.52 % for RhB, MB, MO, and CR. Additionally, these membranes exhibited excellent underwater oleophobicity, antibacterial properties, and salt resistance. This study offers a novel approach to the design and fabrication of solar interface evaporators, presenting an advancement in achieving high solar energy conversion efficiency and superior operational durability.

INNOVATIVE APPROACH TO ENSURING THE QUALITY OF GAS TURBINE ENGINE PARTS PRODUCED BY SELECTIVE LASER SINTERING FOR UAV

The research objects are gas turbine engines parts, manufactured using an innovative method of additive manufacturing – selective laser sintering. The main problem solved in this work is the low quality of the surface layer and the residual porosity of the parts obtained by this method, which significantly limits their operational characteristics and durability. As a result of the experimental studies, rational operating parameters of diamond smoothing were established. This allowed to significantly improve the surface quality and increase the operational characteristics of parts made of heat-resistant alloys INCONEL 718 and an intermetallic alloy based on titanium aluminide OX45-3ODS. The effectiveness of diamond smoothing is explained by local plastic deformation and compaction of the surface layer of parts under the influence of high contact pressures and temperatures. This leads to a significant reduction in surface roughness, an increase in the surface hardness due to strain hardening and a significant reduction in the size and number of residual pores. A characteristic feature of the obtained results is the ability to control the quality parameters of the surface layer by varying the diamond smoothing operating parameters – smoothing force, feed, radius, and geometry of the smoother's working part. The established regularities of the smoothing operating parameters have an impact on the quality characteristics of the surface. This information can be utilized in the development of highly efficient technological processes for the production and restoration of gas turbine engines, critical components of unmanned aerial vehicles, obtained through selective laser sintering. Implementing the elaborated technological recommendations will permit broadening the range of goods produced by additive manufacturing and enhancing their capacity and dependability during operation under conditions of cyclical loads and extreme temperatures.

Aviation aspects of engine oil conveying copper tiny particles embedded in a rotating disk with a binary chemical reaction

Nanofluids have significant industrial applications and motivating heat transfer characteristics for various factors that contribute to the movement of nanofluids are essential significance. The aim of the present study focused on importance of heat transfer analysis on engine oil conveying copper nano particles embedded in a porous rotating disk with potential application in aerospace technology. In this model we considered magnetohydrodynamics, non-linear thermal radiation, thermophoresis and Brownian motion. The present investigation utilized copper nanoparticle and engine oil as a base fluid. The mathematical flow equations are transformed into ordinary differential equations (ODEs) by employing suitable self-similarity variables. The resultant ordinary differential equations are solved numerically by using the Midrich technique in the Maple software. The results are calculated to measure the impact of active parameters on velocity, temperature, concentration equations are presented graphically and in tabular form. Higher values of the magnetic field parameter the velocity profile decreased while the opposite tendency we noticed on energy profile. When increasing the radiation parameter values the energy profile increased. In both cases when increasing the magnetic field and radiation parameter values the Nusselt number profile increased. The research has important implications in a number of real-world situations. In particularly, the advancement of aircraft technology has presented manufacturers with new criteria and problems for the functioning of their devices. It is essential that, in order to guarantee the secure operation of aerospace machinery, the failure mechanisms be identified and the operational durability of critical structural components be improved as quickly as possible.

Supramolecular Association of a Block Copolymer via Strong Hydrogen Bonding to Form Self-Healable Ionogels.

The drive to enhance the operational durability and reliability of stretchable and wearable electronic and electrochemical devices has led to the exploration of self-healing materials that can recover from both physical and functional failures. In the present study, we fabricated a self-healable solid polymer electrolyte, referred to as an ionogel, using reversible hydrogen bonding between the ureidopyrimidone units of a block copolymer (BCP) network swollen in an ionic liquid (IL). The BCP consisted of poly(styrene-b-(methyl acrylate-r-ureidopyrimidone methacrylate)) [poly(S-b-(MA-r-UPyMA)], with the IL-phobic polystyrene forming micellar cores that were interconnected via intercorona hydrogen bonding between the ureidopyrimidone units. By precisely regulating the molecular weight and the composition of the hydrogen-bondable motifs, the mechanical, electrical, and self-healing characteristics of the ionogel were systematically evaluated. The resulting ionogel samples exhibited suitable stretchability, ionic conductivity, and room-temperature self-healability due to reversible hydrogen bonding. To highlight the applicability of the self-healing ionogel as a high-capacitance gate insulator, an electrolyte-gated transistor (EGT) was fabricated using a poly(3-hexylthiophene-2,5-diyl) semiconductor, and the performance of the EGT was fully recovered from a complete cut without any external stimuli.

Capacity configuration of fuel cell hybrid vehicles using enhanced multi-objective particle swarm optimization with competitive mechanism

A well-designed hybrid powertrain is crucial for ensuring the safe, efficient, and durable operation of fuel cell hybrid vehicles. This paper introduces a modular design approach for powertrains, utilizing a Competitive mechanism-based Multi-Objective Particle Swarm Optimization (CMOPSO) algorithm integrated with nested dynamic programming. In this approach, the upper layer employs the CMOPSO algorithm to design the powertrain system, while the lower layer optimizes power coordination for each proposed design. This two-layer optimization framework considers factors such as vehicle economy and durability. Under WLTP conditions, the capacity configuration results are a fuel cell with a rated power of 22 kW, 100 batteries in series, and 7 batteries in parallel. Furthermore, the modular approach outperforms three other algorithms in terms of solution count, diversity, and overall performance metrics. The study also highlights that the vehicle’s power demand characteristics, influenced by different driving cycles, significantly affect capacity configuration results. Sensitivity analysis reveals that both the total operating cost and manufacturing cost of the vehicle are most sensitive to variations in the fuel cell rated power.

NiFe layered-double-hydroxide nanosheet arrays grown in situ on Ni foam for efficient oxygen evolution reaction

Developing efficient and stable oxygen evolution reaction (OER) electrocatalysts under various alkaline conditions is crucial for commercial hydrogen (H₂) production. This study synthesized superhydrophilic NiFe LDH/NF with a nanosheet structure. The strong electronic interactions between the metals modify the electronic structures of Ni and Fe. In-situ Raman spectroscopy reveals numerous high-valent nickel intermediates with high OER activity during the reaction, significantly improving the catalyst's overall performance. At room temperature, the NiFe LDH/NF catalyst exhibits a current density of 50/100 mA cm−2 with only 217/233 mV required in 1 M KOH. Moreover, the catalyst requires only 180 mV under industrial conditions (60 °C, 6 M KOH), 243 mV in alkaline artificial seawater, and 280 mV in alkaline natural seawater to achieve 100 mA cm−2. The catalyst also exhibits long-term operational durability under these conditions, indicating a wide range of potential applications.