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The synthesis of bimetallic and trimetallic platinum-based octahedral catalysts for the cathode of proton exchange membrane fuel cells (PEMFCs) is a particularly active area aimed at meeting technological requirements in terms of durability and cost. The electrocatalytic activity and stability of these shaped catalysts were tested at relatively high potentials (@0.9 V vs RHE) and at lower current densities using the rotating disk electrode, which is less suitable for assessing their behavior under the operating conditions of PEMFCs. In this work, we use a gas diffusion electrode (GDE) half-cell setup to test the performance of the catalysts under application-oriented conditions, relatively higher current densities, and a square-wave stability test. After the stability test, we analyzed the GDE catalytic layer to study the agglomeration and dissolution of the transition metal under these conditions by using high-resolution scanning electron microscopy and energy-dispersive X-ray spectroscopy. The present results provide valuable guidance for developing next-generation active and durable catalysts for PEMFCs.

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Proton exchange membrane fuel cells have strict requirements for the CO concentration in H2-rich fuel gas. Here, from the perspective of industrial practicability, a highly dispersed Pt catalyst (2-4 nm) supported on activated carbon (AC), which was modified by electronic promoters (K+) and structural promoters (isopropanol), is studied in detail. Compared with traditional metal oxide supports, the K-Pt/AC catalysts, which benefit from the tuned charge distribution, achieve a significant reduction of CO (from 1% to <0.1 ppb) under H2-rich conditions and show potential for used in large-scale industrial hydrogen purification. Experimental results and theoretical calculations reveal that the K atom, with its lower electronegativity, contributes to the shift of surface Pt2+ to a lower binding energy due to the presence of oxygen species on the AC surface. This facilitates oxygen activation and accelerates desorption of the CO2 product, thereby accelerating the reaction process and enabling the deep removal of CO in a hydrogen-rich atmosphere.

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Proton exchange membranes (PEMs) play an important role in fuel cells. For realizing a nanofiber (NF) structure design in PEMs, the material should have tunable pores and a high specific area. In this study, we attempt to design a novel NF with synergistic architecture doped MOF for constructing three-dimensional (3D) proton conduction networks in PEMs. In this framework, UiO-66-COOH serves as a platform for proton sites to synergistically promote proton conductivity via polyvinylpyrrolidone dissolution, hydrolyzation of polyacrylonitrile, and sulfamic acid functionalization of the shell-layer NF. Benefiting from enriched proton-transfer sites in NFs, the obtained composite membrane overcomes the trade-off among proton conductivity, methanol permeability, and mechanical stability. The composite membrane with 50 % fiber (Nafion/S@NF-50) exhibited a high proton conductivity of 0.212 S cm-1 at 80 °C and 100 % relative humidity, suppressed methanol permeability of 0.66 × 10-7 cm2 s-1, and the maximum power density of direct methanol fuel cell is 182.6 mW cm-2. Density functional theory was used to verify the important role of sulfamic acid in proton transfer, and the activation energy barriers under anhydrous and hydrous conditions are only 0.337 and 0.081 kcal, respectively. This study opens up new pathways for synthesizing NF composite PEMs.

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To plant crops (especially dry crops such as water spinach) with concomitant electricity recovery, a hanging-submerged-plant-pot system (HSPP) is developed. The HSPP consists of a soil pot (anodic) partially submerged under the water surface of a cathode tank. The microbial communities changed with conditions were also investigated. It was found that with chemical fertilizers the closed-circuit voltage (CCV, with 1 kΩ) was stable (approximately 250 mV) within 28 d; however, without fertilizer, the water spinach could adjust to the environment to obtain a better power output (approximately 3 mW m-2) at day 28. The microbial-community analyses revealed that the Pseudomonas sp. was the only exoeletrogens found in the anode pots. Using a secondary design of HSPP, for a better water-level adjustment, the maximum power output of each plant was found to be approximately 27.1 mW m-2. During operation, high temperature resulted in low oxygen solubility, and low CCV as well. At this time, it is yet to be concluded whether the submerged water level significantly affects electricity generation.

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The role of redox mediators in improving electron transport from electrochemically active bacteria to the anode is crucial for enhanced bioelectricity output from microbial fuel cells (MFCs), which makes the selection of an ideal mediator very important. This study aims at exploring a new redox mediator niacin (vit B3) for enhanced bioelectricity generation in MFC while treating distillery wastewater through facile modification of anode electrode by niacin doping (MFC-NME) and simple application of niacin to the anolyte (MFC-NAA). Fourier transform infrared (FTIR) spectroscopy, scanning electron microscopy (SEM), and X-ray diffraction (XRD) of NME confirmed the effective adsorption of niacin onto the carbon felt surface. Notably, MFC-NME exhibited a significantly higher power density (PD) of 6.36 W/m3 compared to MFC-NAA (4.59 W/m3) and control MFC (3.49W/m3). The charge transfer resistance (RCT) in MFC-NME (1.73 Ω) and MFC-NAA (2.06 Ω) were lowered by more than half than that in control MFC (4.33 Ω), which underscores the efficacy of niacin as a redox mediator. SEM analysis revealed improved bacterial attachment over the bioanode in the MFC-NME as compared to that of MFC-NAA and control MFC. Removal of chemical oxygen demand (COD) was higher in MFC-NAA (85%) and MFC-NME (80%) than in control MFC (73%) suggesting that niacin in the anolyte supported greater organic matter removal due to enriched microbial activity. Niacin used in anode modification shows great potential for improved electron transfer and enhanced bioelectricity production and supports greater wastewater treatment performance. The modified bioanode NME exhibits excellent stability.

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Carbon corrosion poses a significant challenge in polymer exchange membrane fuel cells (PEMFCs), leading to reduced cell performance due to catalyst layer degradation and catalyst detachment from electrodes. A promising approach to address this issue involves incorporating an anticorrosive carbon material into the oxygen reduction reaction (ORR) electrode, even in small quantities (≈3 wt% in electrode). Herein, the successful synthesis of fluorine-doped graphene nanoribbons (F-GNR) incorporated with graphitic carbon nanotubes (F-GNR@CNT), demonstrating robust resistance to carbon corrosion is reported. By controlling the synthesis conditions using an exfoliation method, the properties of the composite are tailored. Electronic structural studies, employing density functional theory (DFT) calculations, to elucidate the roles of fluorine dopants and graphitic carbon nanotubes (CNTs) in mitigating carbon corrosion are conducted. Physicochemical and electrochemical characterization of F-GNR@CNT reveal its effectiveness as a cathode additive at the single-cell scale. The addition of F-GNR@CNT to the Pt/C cathode improves durability by enhancing carbon corrosion resistance and water management, thus mitigating the flooding effect through tailored surface properties. Furthermore, advanced impedance analysis using a transmission line model is performed to gain insights into the internal resistance and capacitive properties of electrode structure.

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Efficient CC bond cleavage and the complete oxidation of alcohols are key to improving the efficiency of renewable energy utilization. Herein, we successfully prepare porous Fe-doped hexagonal close-packed (hcp)-PtBi/face-centered cubic (fcc)-Pt heterostructured nanoplates with abundant grain/phase interfaces (h-PtBi/f-Pt@Fe1.7 PNPs) via a simple solvothermal method. The open porous structure, abundant grain/phase interface and stacking fault defects, and the synergistic effect between intermetallic hcp-PtBi and fcc-Pt make h-PtBi/f-Pt@Fe1.7 PNPs an effective electrocatalyst for the glycerol oxidation reaction (GOR) in direct glycerol fuel cells (DGFCs). Notably, the h-PtBi/f-Pt@Fe1.7 PNPs exhibit an excellent mass activity of 7.6 A mgPt-1 for GOR, 4.75-fold higher than that of commercial Pt black in an alkaline medium. Moreover, the h-PtBi/f-Pt@Fe1.7 PNPs achieve higher power density (125.8 mW cm-2) than commercial Pt/C (81.8 mW cm-2) in a single DGFC. The h-PtBi/f-Pt@Fe1.7 PNPs can also effectively catalyze the electrochemical oxidation of 1-propanol (17.1 A mgPt-1), 1,2-propanediol (7.2 A mgPt-1), and 1,3-propanediol (5.2 A mgPt-1). The in-situ Fourier-transform infrared spectra further reveal that the CC bond of glycerol, 1-propanol, 1,2-propanediol, and 1,3-propanediol was dissociated for the complete oxidation by the h-PtBi/f-Pt@Fe1.7 PNPs. This study provides a new class of porous Pt-based heterostructure nanoplates and insight into the intrinsic activity of different C3 alcohols.

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Forced-flow atomic layer deposition nanolamination is employed to fabricate Pt-Ni nanoparticles on XC-72, with the compositions ranging from Pt94Ni6 to Pt67Ni33. Hydrogen is used as a co-reactant for depositing Pt and Ni. The growth rate of Pt is slower than that using oxygen reactant, and the growth exhibits preferred orientation along the (111) plane. Ni shows much slower growth rate than Pt, and it is only selectively deposited on Pt, not on the substrate. Higher ratios of Ni would hinder subsequent stacking of Pt atoms, resulting in lower overall growth rate and smaller particles (1.3-2.1 nm). Alloying of Pt with Ni causes shifted lattice that leads to larger lattice parameter and d-spacing as Ni fraction increases. From the electronic state analysis, Pt 4f peaks are shifted to lower binding energies with increasing the Ni content, suggesting charge transfer from Ni to Pt. Schematic of the growth behavior is proposed. Most of the alloy nanoparticles exhibit higher electrochemical surface area and oxygen reduction reaction activity than those of commercial Pt. Especially, Pt83Ni17 and Pt87Ni13 show excellent mass activities of 0.76 and 0.59 A mgPt -1, respectively, higher than the DOE target of 2025, 0.44 A mgPt -1.

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The structural tailoring of Pt-based catalysts into 1D nanowires for oxygen reduction reactions (ORR) has been a focus of research. Mo(CO)6 is commonly used as a morphological modifier to form nanowires, but it is found that it inevitably leads to Mo doping. This doping introduces unique electrochemical signals not seen in other Pt-based catalysts, which can directly reflect the stability of the catalyst. Through experiments, it is demonstrated that Mo doping is detrimental to ORR performance, and theoretical calculations have shown that Mo sites that are inherently inactive also poison the ORR activity of the surrounding Pt. Therefore, a novel gas-assisted technique is proposed to replace Mo(CO)6 with CO, which forms ultrafine nanowires with an order of magnitude increase in length, ruling out the effect of Mo. The catalyst performs at 1.24 A mgPt -1, 7.45 times greater than Pt/C, demonstrating significant ORR mass activity, and a substantial improvement in stability. The proton exchange membrane fuel cell using this catalyst provides a higher power density (0.7 W cm-2). This study presents a new method for the preparation of ultra-long nanowires, which opens up new avenues for future practical applications of low-Pt catalysts in PEMFC.

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Pt-based alloy with high mass activity and durability is highly desired for proton exchange membrane fuel cells, yet a great challenge remains due to the high mass transport resistance near catalysts with lowering Pt loading. Herein, an extensible approach employing atomic layer deposition to accurately introduce a gas-phase metal precursor into platinum nanoparticles (NPs) pre-filled mesoporous channels is reported, achieved by controlling both the deposition site and quantity. Following the spatially confined alloying treatment, the prepared PtSn alloy catalyst within mesopores demonstrates a small size and homogeneous distribution (2.10 ± 0.53 nm). The membrane electrode assembly with mesoporous carbon-supported PtSn alloy catalyst achieves a high initial mass activity of 0.85 A mg Pt - 1 ${\mathrm{mg}}_{\mathrm{Pt}}^{-1}$ at 0.9 V, which is attributed to the smallest local oxygen transport resistance (3.68 S m-1) ever reported. The mass activity of the catalyst only decreases by 11% after 30000 cycles of accelerated durability test, representing superior full-cell durability among the reported Pt-based alloy catalysts. The enhanced activity and durability are attributed to the decreased adsorption energy of oxygen intermediates on Pt surface and the strong electronic interaction between Pt and Sn inhibiting Pt dissolution.

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The challenge of energy storage is a pivotal consideration in renewable energy-based power systems. Hydrogen emerges as a highly promising alternative or complementary solution to electric batteries, showcasing its potential for long-term and high-capacity storage. In this context, energy system modeling and optimization has gained prominence as an indispensable research tool, aiding in the processes of designing, sizing, and managing the day-to-day operations of renewable energy systems integrated with a hydrogen storage unit. However, the gathering of reliable and accurate techno-economic data emerges as time-consuming tasks, and the lack of standardized reference data introduces variability in model results. This variability arises from inconsistent input parameters rather than the physics or complexity of energy systems, leading to potentially erroneous results and misguided policy recommendations. Recognizing the need for comprehensive and transparent datasets, we introduce this open data techno-economic repository. The dataset is meticulously designed to encompass key technologies essential for hydrogen production, compression, storage, and utilization within a power-to-power system. Specifically, techno-economic data are reported for electrolysers, fuel cells, battery energy storage systems, hydrogen compression units, and hydrogen storage vessels. The learning curves and cost functions embedded in this paper, delineating investment costs as a function of production scale up and size, are derived directly from the raw data, providing a nuanced understanding of the economic landscape.

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Microbial fuel cells can generate electricity by breaking down organic molecules through sustainable bio-electrochemical processes and wastewater as an energy source. A novel approach to remediate wastewater containing selenite was studied utilizing a selenite-reducing mixed bacterial culture with a nano manganese oxide modified cathode in the microbial fuel cells. The modification enhanced electrochemical catalytic activity, extracellular electron transfer rate, chemical oxygen demand (COD) elimination efficiency, and coulombic efficiency. Scanning electron microscopy and energy dispersive X-rays analysis were used to examine a manganese dioxide-coated graphite cathode's surface morphology and chemical composition. The manganese dioxide-coated electrode generated up to 69% higher voltage with 150 ppm selenite concentration than the uncoated graphite electrode. The microbial fuel cell removed up to 80% of the initial COD of 120 mg/L and achieved a maximum power density of 1.51 W/m2. The study demonstrates that microbial fuel cells can effectively treat selenite-containing wastewater, and modifying the cathode can enhance energy production. .

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As interest in eco-friendly work vehicles grows, research on the powertrains of eco-friendly tractors has increased, including research on the development of eco-friendly vehicles (tractors) using hydrogen fuel cell power packs and batteries. However, batteries require a long time to charge and have a short operating time due to their low energy efficiency compared with hydrogen fuel cell power packs. Therefore, recent studies have focused on the development of tractors using hydrogen fuel cell power packs; however, there is a lack of research on powertrain performance analysis considering actual working conditions. To evaluate vehicle performance, an actual load measurement during agricultural operation must be conducted. The objective of this study was to conduct an efficiency analysis of powertrains according to their power source using data measured during agricultural operations. A performance evaluation with respect to efficiency was performed through comparison and an analysis with internal combustion engine tractors of the same level. The specifications of the transmission for hydrogen fuel cell and engine tractors were used in this study. The power loss and efficiency of the transmission were calculated using ISO 14179-1 equations, as shown below. Plow tillage and rotary tillage operations were conducted for data measurement. The measurement system consists of four components. The engine data load measurement was calculated using the vehicle's controller area network (CAN) data, the axle load was measured using an axle torque meter and proximity sensors, and fuel consumption was measured using the sensor installed on the fuel line. The calculated capacities, considering the engine's fuel efficiency for plow and rotary tillage operations, were 131.2 and 175.1 kWh, respectively. The capacity of the required power, considering the powertrain's efficiency for hydrogen fuel cell tractors with respect to plow and rotary tillage operations, was calculated using the efficiency of the motor, inverter, and power pack, and 51.3 and 62.9 kWh were the values obtained, respectively. Considering these factors, the engine exhibited an efficiency of about 47.9% compared with the power pack in the case of plow tillage operations, and the engine exhibited an efficiency of about 29.3% in the case of rotary tillage operations. A hydrogen fuel cell tractor is considered suitable for high-efficiency and eco-friendly vehicles because it can operate on eco-friendly power sources while providing the advantages of a motor.

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Perfluorosulfonic acid (PFSA) polymers are used as electrolyte membranes in polymer electrolyte fuel cells. To investigate the effect on proton conductivity through structural orientation control, we added 1,2,4-triazole to PFSA films during casting to impart anisotropy to the ion-cluster structure of the films. The proton conductivities of the films were found to be high in the film-surface direction and low in the film-thickness direction. Structural analysis using small-angle X-ray scattering suggested that the anisotropy in proton conductivity was due to anisotropy in the ion-cluster structure, which in turn was attributed to the formation of a phase-separated structure via strong bonding between sulfonic acid groups and 1,2,4-triazole during cast film formation and the surface segregation of fluorine. We expect the findings of this study to aid in the fabrication of PFSA films with controlled ion clusters.

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Microbial Fuel Cells (MFCs) are a sophisticated and advanced system that uses exoelectrogenic microorganisms to generate bioenergy. Predicting performance outcomes under experimental settings is challenging due to the intricate interactions that occur in mixed-species bioelectrochemical reactors like MFCs. One of the key factors that limit the MFC's performance is the presence of a microbial consortium. Traditionally, multiple microbial consortia are implemented in MFCs to determine the best consortium. This approach is laborious, inefficient, and wasteful of time and resources. The increase in the availability of soft computational techniques has allowed for the development of alternative strategies like artificial intelligence (AI) despite the fact that a direct correlation between microbial strain, microbial consortium, and MFC performance has yet to be established. In this work, a novel generic AI model based on subspace k-Nearest Neighbour (SS-kNN) is developed to identify and forecast the best microbial consortium from the constituent microbes. The SS-kNN model is trained with thirty-five different microbial consortia sharing different effluent properties. Chemical oxygen demand (COD) reduction, voltage generation, exopolysaccharide (EPS) production, and standard deviation (SD) of voltage generation are used as input features to train the SS-kNN model. The proposed SS-kNN model offers an accuracy of 100% during training period and 85.71% when it is tested with the data obtained from existing literature. The implementation of selected consortium (as predicted by SS-kNN model) improves the COD reduction capability of MFC by 15.67% than that of its constituent microbes which is experimentally verified. In addition, to prevent the effects of climate change and mitigate water pollution, the implementation of MFC technology ensures clean and green electricity. Consequently, achieving sustainable development goals (SDG) 6, 7, and 13.

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Several previous studies concerned of microbial fuel cells integrated into constructed wetlands, nevertheless, their application as a convenient treatment for wastewater is still developing. In this experimental investigation, five CW-MFC systems were similarly designed, setup, and operated in a batch mode for two subsequent cycles. Each cycle lasted for 10 days to evaluate the performance of CW-MFC system for the remediation of real leather tannery wastewater (LTW). Four CW-MFCs were planted, each with different type of vegetation including Conocarpus, Arundo donax, Canna lily, and Cyperus papyrus in CW1-MFC, CW2-MFC, CW3-MFC, and CW4-MFC, respectively. The fifth CW5-MFC was maintained unplanted and considered as the control system. The performance of each CW-MFCs systems was evaluated mainly based on the removal of organic content (COD), total dissolved solid (TDS) elimination, and power generation. The results demonstrated that the four types of plants maintained healthy and no sign of wilting was observed during the 20 days of monitoring. For the first cycle of batch operation, maximum removal efficiencies of COD were 99.8%, 99.5%, 99.7%, 99.6% and 99.5% with power outputs of 10,502.8, 10,254.6, 9956.4, 10,029.6, and 9888.0 mW/m3, while, maximum TDS elimination were 46.7%, 39.7%, 60.8%, 55.5%, and 13.8% observed in CW1-MFC, CW2-MFC, CW3-MFC, CW4-MFC, and CW5-MFC, respectively. Very comparable results were observed in the second operation cycle. Results of phototoxicity test indicated that the germination of Hordeum vulgare and Triticum aestivum were 100% watered with treated effluent compared to 90% accomplished with tap water as the control solution for both types of seeds.

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High-temperature proton exchange membrane fuel cell (HT-PEMFC) based on phosphoric acid doped polybenzimidazole membrane (PBI/PA) operating at 120-200 °C can provide insensitivity to carbon monoxide (CO) and simplified managements of water and heat and thus attract significant global attention. However, one significant drawback is its low utilization of precious metal catalysts resulted from the PA poisoning and inefficient three-phase boundary. Studies of binder materials in catalyst layers for HT-PEMFC are gradually emerging and there are few literature reviews on this important topic. The purpose of this review is to describe the various types of binders based on their molecular structure and electrochemical properties, with particular emphasis on catalyst layer for fuel cells. Importantly, this review provides a better understanding of relationship between fuel cell performance and the gas permeability and conductivity of different binders. Then, future directions of research and development in binder materials of HT-PEMFC are pointed out.

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Overcoming the trade-off between the graphitization of the carbon substrate and enhanced electronic metal-support interaction (EMSI) and intrinsic activity of Pt-C catalysts remains a major challenge for ensuring the durable operation of energy conversion devices. This article presents a hybrid catalyst consisting of PtFe nanoparticles and single Pt and Fe atoms supported on N-doped carbon (PtFeNPs@PtFeSAs-N-C), which exhibits improved activities in hydrogen evolution and oxygen reduction reactions (HER and ORR, respectively) and has excellent durability owing to the high graphitization, rich edge defects, and porosity of the carbon in PtFeNPs@PtFeSAs-N-C, as well as strong EMSI between the PtFe nanoparticles and edge-defective carbon embedded with Pt and Fe atoms. According to theoretical calculations, the strong EMSI optimizes the H* adsorption-desorption and facilitates the adsorption OOH*, accelerating the HER and ORR processes. A novel flow seawater-Al/acid hybrid fuel cell using the PtFeNPs@PtFeSAs-N-C cathode can serve as a high-efficiency energy conversion device that delivers a high power density of 109.5 mW cm-2 while producing H2 at a significantly high rate of 271.6 L m-2 h-1. Moreover, PtFeNPs@PtFeSAs-N-C exhibits a remarkable performance (high power density of 298.0 mW cm-2 and long-term durability of 1000 h) in a flow Zn-air battery.

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Proton exchange membrane fuel cell (PEMFC) parameter extraction is an important issue in modeling and control of renewable energies. The PEMFC problem's main objective is to estimate the optimal value of unknown parameters of the electrochemical model. The main objective function of the optimization problem is the sum of the square errors between the measured voltages and output voltages of the proposed electrochemical optimized model at various loading conditions. Natural rabbit survival strategies such as detour foraging and random hiding are influenced by Artificial rabbit optimization (ARO). Meanwhile, rabbit energy shrink is mimicked to control the smooth switching from detour foraging to random hiding. In this work, the ARO algorithm is proposed to find the parameters of PEMFC. The ARO performance is verified using experimental results obtained from conducting laboratory tests on the fuel cell test system (SCRIBNER 850e, LLC). The simulation results are assessed with four competitive algorithms: Grey Wolf Optimization Algorithm, Particle Swarm Optimizer, Salp Swarm Algorithm, and Sine Cosine Algorithm. The comparison aims to prove the superior performance of the proposed ARO compared with the other well-known competitive algorithms.

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Metal-supported solid oxide fuel cell (MS-SOFC) is very promising for intermediate temperature solid oxide fuel cell (SOFC) due to better mechanical strength, low materials cost, and simplified stack assembling. However, the effects of metal support on the performance and temperature field of MS-SOFC is still necessary for further study. In this study, a three-dimensional multi-physical model is developed to investigate how the use of metal support influence the electrochemical performance and the temperature field of MS-SOFC with a ceria-based electrolyte. The multi-physical model fully considers the conservation equations of mass, momentum, and energy that are coupled with mass transport and electrochemical reactions. The wall temperature in the radiation model is calculated using a discrete method. It is found that the radiation heat flux accounts for 3.13 % of the total heat flux. More importantly, the temperature difference of MS-SOFC is 3.61 % lower than that of conventional anode-supported SOFC, leading to improved temperature uniformity and cell durability.