Operational parameters correlated with the long-term stability of anion exchange membrane water electrolyzers

In this study, we investigated the long-term stability of anion exchange membrane water electrolyzers (AEMWEs) under various bias conditions. The cell performance was relatively stable under conditions of voltage cycling in a narrow range, constant voltage and constant current. On the other hand, a relatively dynamic condition, voltage cycling, in a wide range detrimentally affected the cell stability. Abnormally high negative and positive currents were observed when the cell voltage was switched between 2.1 and 0 V. Impedance results and post-material analyses indicated that the performance degradation was mainly due to anode catalyst detachments, which increased non-ohmic resistance in the wide range voltage cycling. An increase in ohmic resistance was also observed, which was due to the membrane dehydration that occurred in the frequent rest times. Thus, it can be said that the voltage cycling range as well as the frequency of rest times are critical operational parameters in determining the long-term stability of AEMWEs.     

Effect of water distribution in gas diffusion layer on proton exchange membrane fuel cell performance

Water management of proton exchange membrane fuel cells remains a prominent issue in research concerning fuel cells. In this study, the gas diffusion layer (GDL) of a fuel cell is partially treated with a hydrophobic agent, and the effect of GDL hydrophobicity on the water distribution in the fuel cell is examined. First, the effect of the position of the cathode GDL hydrophobic area relative to the channel on the fuel cell performance is investigated. Then, the water distribution in the fuel cell cathode GDL is observed using X-ray imaging. The experimental results indicate that when the hybrid GDL's hydrophobic area lies on the channel, water tends to accumulate under the rib, and the water content in the channel is low; this improves the fuel cell performance. When the hydrophobic area is under the rib, the water distribution is more uniform, but the performance deteriorates.     

Efficient fault diagnosis method of PEMFC thermal management system for various current densities

The temperature of a fuel cell has a considerable impact on the saturation of a membrane, electrochemical reaction speed, and durability. So thermal management is considered one of the critical issues in polymer electrolyte membrane fuel cells. Therefore, the reliability of the thermal management system is also crucial for the performance and durability of a fuel cell system. In this work, a methodology for component-level fault diagnosis of polymer electrolyte membrane fuel cell thermal management system for various current densities is proposed. Specifically, this study suggests fault diagnosis using limited data, based on an experimental approach. Normal and five component-level fault states are diagnosed with a support vector machine model using temperature, pressure, and fan control signal data. The effects of training data at different operating current densities on fault diagnosis are analyzed. The effects of data preprocessing method are investigated, and the cause of misdiagnosis is analyzed. On this basis, diagnosis results show that the proposed methodology can realize efficient component-level fault diagnosis using limited data. The diagnosis accuracy is over 92% when the residual basis scaling method is used, and data at the highest operating current density is used to train the support vector machine.     

Nickel supported over MCM-41 coated ceramic membrane for steam reforming of real tar

A novel catalyst, Nickel supported over MCM-41 coated ceramic membrane (NMC), was developed using coating method and deposition-precipitation method and applied for steam reforming of real tar in fixed bed. The effects of reaction conditions such as Ni loading amount, reaction temperature and mass ratio of steam to tar were also studied. The good dispersion of Ni nanoparticles and the strong interaction between Ni particles and the support were identified by BET, XRD, H₂-TPR and SEM/EDS, resulting in the excellent performance of NMC catalysts. Maximum tar conversion of 96.4% and H₂ yield of 98.7 mmol g^?1 were obtained using 20NMC with a mass ratio of steam to coal tar of 2 at 800 °C. Moreover, 20 NMC exhibited a good stability in 10 h of lifetime test and the resistance of graphitic carbon formation prone to easier regeneration of catalysts illustrated by Raman spectroscopy. It indicates that the utilization of NMC catalysts for tar steam reforming is a promising way.     

Effect of fiber orientation on Liquid–Gas flow in the gas diffusion layer of a polymer electrolyte membrane fuel cell

In this study, the lattice Boltzmann method was used to simulate the three-dimensional intrusion process of liquid water in the gas diffusion layer (GDL) of a polymer electrolyte membrane fuel cell (PEMFC). The GDL was reconstructed by the stochastic method and used to investigate fiber orientation's influence on liquid water transport in the GDL of a PEMFC. The fiber orientation can be described by the angle between a single fiber and the in-plane direction; three different samples were simulated for three different fiber orientation ranges. The simulated permeability correlated well with the anisotropic characteristics of reconstructed carbon papers. It was concluded that the fiber orientation had a significant effect on the liquid invasion pattern in the GDL by changing the pore shape and distribution of the GDL. The results indicated that the stochastically reconstructed GDL, taking into account the fiber orientation, better demonstrates the mass transport properties of the GDL.     

Design and synthesis of side-chain optimized poly(2,6-dimethyl-1,4-phenylene oxide)-g-poly(styrene sulfonic acid) as proton exchange membrane for fuel cell applications: Balancing the water-resistance and the sulfonation degree

Side-chain optimized poly (2,6-dimethyl-1,4-phenylene oxide)-g-poly (styrene sulfonic acid) (PPO-g-PSSA) is designed with balanced water-resistance and sulfonation degree. The PPO-g-PSSA is synthesized by controlled atom-transfer radical polymerization (ATRP) from brominated poly (2,6-dimethyl-1,4-phenylene oxide) (PPO-xBr) and ethyl styrene-4-sulfonate and followed by hydrolysis. A series of PPO-g-PSSA are prepared possessing different bromination degree (x) of PPO-xBr and polymerization degree (m) of the side-chains and the water-resistances of the fabricated membranes are investigated. The results show that a PPO-g-PSSA at relatively low x (x < 0.2) and high m (m > 4) exhibits good balance between the water-resistance and the sulfonation degree. Namely, it displays suitable proton conductivity with compromised water-resistance. Moreover, a maximum ion exchange capacity (IEC) of 3.24 mmol g^?1 is reached without the sacrifice of water-resistance. In addition, PPO-g-0.08PSSA-13 and PPO-g-0.14PSSA-4 are chosen characterized by thermogravimetric analysis, proton conductivities and mechanical properties. At 90% RH, the optimized PPO-g-0.08PPSA-13 possesses a proton conductivity of 37.9 mS cm^?1 at 40 °C and 45.5 mS cm^?1 at 95 °C, respectively.     

Influences of chitosan on freeze–thaw stability of Arenga pinnata starch

This study aims to investigate chitosan (CS) with five different molecular weight (Mw) on freeze–thaw stability of Arenga pinnata starch (APS) gel subjected to five freeze–thaw cycles (FTC). The syneresis of APS gels was reduced by adding CS and the APS gel with high Mw CS had lower syneresis duo to a higher water holding capacity (P < 0.05). The addition of CS significantly decreased the hardness and molecular ordered structure of APS gel. In addition, CS could improve the microstructural stability. The results suggested that CS could effectively improve the freeze–thaw stability of APS gel, and CS with higher Mw might have more practical utility to improve stability of APS gel.     

Sulphonated (PVDF-co-HFP)-graphene oxide composite polymer electrolyte membrane for HI decomposition by electrolysis in thermochemical iodine-sulphur cycle for hydrogen production

In overall iodine-sulphur (I-S) cycle (Bunsen reaction), HI decomposition is a serious challenge for improvement in H₂ production efficiency. Herein, we are reporting an electrochemical process for HI decomposition and simultaneous H₂ and I₂ production. Commercial Nafion 117 membrane has been generally utilized as a separator, which also showed huge water transport (electro-osmosis), and deterioration in conductivity due to dehydration. We report sulphonated poly(vinylidene fluoride-co-hexafluoropropylene) (PVDF-co-HFP) (SCP) and sulphonated graphene oxide (SGO) composite stable and efficient polymer electrolyte membrane (PEM) for HI electrolysis and H₂ production. Different SCP/SGO composite PEMs were prepared and extensively characterized for water content, ion-exchange capacity (IEC), conductivity, and stabilities (mechanical, chemical, and thermal) in comparison with commercial Nafion117 membrane. Most suitable optimized SCP/SGO-30 composite PEM exhibited 6.78 × 10^?2 S cm^?1 conductivity in comparison with 9.60 × 10^?2 S cm^?1 for Nafion® 117. The electro-osmotic flux ofSCP/SGO-30 composite PEM (2.53 × 10^?4 cm s^?1) was also comparatively lower than Nafion® 117 membrane (2.75 × 10^?4 cm s^?1). For HI electrolysis experiments, SCP/SGO-30 composite PEM showed good performance such as 93.4% current efficiency (η), and 0.043 kWh/mol-H₂ power consumption (Ψ). Further, intelligent architecture of SCP/SGO composite PEM, in which hydrophilic SGO was introduced between fluorinated polymer by strong hydrogen bonding, high efficiency and performance make them suitable candidate for electrochemical HI decomposition, and other diversified electrochemical processes.     

Hydrogen production costs of a polymer electrolyte membrane electrolysis powered by a renewable hybrid system

In this work, a novel approach related to the production of hydrogen using a polymer electrolyte membrane electrolysis powered by a renewable hybrid system is proposed. The investigation is carried out by establishing energy balances in the different components constituting the combined renewable system. A mathematical model to predict the production of electricity and hydrogen is proposed. The discrepancies between the numerical results and those from the literature review do not exceed 7%. The results show that the overall efficiency and the capacity factor of the combined renewable system without thermal storage are 20 and 34%, respectively. The levelized cost of hydrogen also is 6.86 US$/kg. The effect of certain physical parameters such as optical efficiency, water electrolysis temperature, unit electrolysis capital cost and solar multiple on the performance of the combined system is investigated. The results show that the performance of hydrogen production is optimal when the solar installation is three times oversized. The results also show that the levelized cost of hydrogen for the optimal sized is 4.07 US$/kg. Finally, the proposed combined system can produce low cost hydrogen and compete with hybrid sulfur thermochemical cycles, conventional photovoltaic installations, concentrated photovoltaic thermal systems and wind farms developed in all regions of the world.     

Parameter identification of proton exchange membrane fuel cell via Levenberg-Marquardt backpropagation algorithm

It is essential to develop an accurate model of proton exchange membrane fuel cell (PEMFC) for a reliable operation and analysis, in which unknown parameters usually need to be determined. The inherent nonlinear, strong coupling, and diversification of PEMFC model seriously hinder traditional methods to identify the parameters. For the sake of overcoming these thorny obstacles, Levenberg-Marquardt backpropagation (LMBP) algorithm based on artificial neural networks (ANNs) is proposed for PEMFC parameter identification. Furthermore, the performance of LMBP is thoroughly evaluated and compared with four typical meta-heuristic algorithms under three cases. Simulation results indicate that LMBP performs a higher accuracy and faster speed for parameter identification. In particular, accuracy and convergence speed can achieve as much as 99.8% and 95.9% growth via LMBP, respectively.