Carbon corrosion mechanism on nitrogen-doped carbon support — A density functional theory study

In this work, density functional theory (DFT) calculations were used to investigate the mechanism of carbon corrosion on nitrogen-doped carbon support. Free energy diagrams were generated based on three proposed reaction pathways to evaluate corrosion mechanisms. The most energetically preferred mechanism on nitrogen-doped carbon was determined. The results show that the step of water dissociation to form ^#OH was the rate-determining step for gra-G-1N (graphene doped with graphitic N) and pyrr-G-1N (graphene doped with pyrrolic N). As for graphene doped with pyridinic N, the step of C^#OC^#O formation was critical. It was found that the control of nitrogen concentration was necessary for precisely designing optimized carbon materials. Abundance of nitrogen moieties aggravated the carbon corrosion. When the high potential was applied, specific types of graphitic N and pyridinic N were found to be favorable carbon modifications to improve carbon corrosion resistance. Moreover, the solvent effect was also investigated. The results provide theoretical insights and design guidelines to improve corrosion resistance in carbon support through material modification by inhibiting the adsorption of surface oxides (OH, O, and OOH).     

Study on ice-melting performance of gradient gas diffusion layer in proton exchange membrane fuel cell

In this study, a three-dimensional model was established using the lattice Boltzmann method (LBM) to study the internal ice melting process of the gas diffusion layer (GDL) of the proton exchange membrane fuel cell (PEMFC). The single-point second-order curved boundary condition was adopted. The effects of GDL carbon fiber number, growth slope of the number of carbon fibers and carbon fiber diameter on ice melting were studied. The results were revealed that the temperature in the middle and lower part of the gradient distribution GDL is significantly higher than that of the no-gradient GDL. With the increase of the growth slope of the number of carbon fiber, the temperature and melting rate gradually increase, and the position of the solid-liquid interface gradually decreases. The decrease in the number of carbon fibers has a similar effect as the increase in the growth slope of the number of carbon fibers. In addition, as the diameter of the carbon fiber increases, the position of the solid-liquid interface gradually decreases first and then increases.     

A novel design for humidifying an open-cathode proton exchange membrane fuel cell using anode purge

The low performance of open-cathode proton-exchange-membrane fuel cells (OCPEMFCs) is attributed to the low-humidity ambient air supplied to the cathode using electric fans. To improve the OCPEMFC performance, this paper proposes a novel humidification method by collecting water purged from the anode and supplying it to the open cathode. The OCPEMFC performance is evaluated at various humidifier distances from the cathode inlet, and it is compared with that where no humidifier is used when the OCPEMFC operates under three different current levels of 1, 5, and 8 A. The results show that the novel design improves the stack power, and optimal performance is achieved at a humidifier distance of 2 cm. The energy efficiency achieves an improvement between 1.4% and 1.8% when a humidifier is used.     

Analysis of surface and interior degradation of gas diffusion layer with accelerated stress tests for polymer electrolyte membrane fuel cell

The effects of surface and interior degradation of the gas diffusion layer (GDL) on the performance and durability of polymer electrolyte membrane fuel cells (PEMFCs) have been investigated using three freeze-thaw accelerated stress tests (ASTs). Three ASTs (ex-situ, in-situ, and new methods) are designed from freezing ?30 °C to thawing 80 °C by immersing, supplying, and bubbling, respectively. The ex-situ method is designed for surface degradation of the GDL. Change of surface morphology from hydrophobic to hydrophilic by surface degradation of GDL causes low capillary pressure which decreased PEMFC performance. The in-situ method is designed for the interior degradation of the GDL. A decrease in the ratio of the porosity to tortuosity by interior degradation of the GDL deteriorates PEMFC performance. Moreover, the new method showed combined effects for both surface and interior degradation of the GDL. It was identified that the main factor that deteriorated the fuel cell performance was the increase in mass transport resistance by interior degradation of GDL. In conclusion, this study aims to investigate the causes of degraded GDL on the PEMFC performance into the surface and interior degradation and provide the design guideline of high-durability GDL for the PEMFC.     

Symmetric and asymmetric membranes based on La0.5Sr0.5Fe0.7Ga0.3O3-δ perovskite with high oxygen semipermeation flux performances and identification of the rate-determining step of oxygen transport

This work focuses on identifying the rate-determining step of oxygen transport through La_0.5Sr_0.5Fe_0.7Ga_0.3O_3-δ membranes with symmetric and asymmetric architectures. The best oxygen semipermeation fluxes are 3.4 10⁻³ mol. m^-2.s^-1 and 6.3 10⁻³ mol. m^-2.s^-1 at 900 °C for the symmetric membrane and asymmetric membrane with a modified surface. The asymmetric membrane with a modified surface leads to an increase of approximately 7 times the oxygen flux compared to that obtained with the La_0.5Sr_0.5Fe_0.7Ga_0.3O_3-δ dense membrane without surface modification. This work also shows that the oxygen flux is mainly governed by gaseous oxygen diffusion through the porous support of asymmetric La_0.5Sr_0.5Fe_0.7Ga_0.3O_3-δ membranes.     

Designing amorphous formulations of polyphenols with naringin by spray-drying for enhanced solubility and permeability

Naringin (NAR), a major flavanone (FVA) glycoside, is a component of food mainly obtained from grapefruit. We used NAR as a food additive to improve the solubility and permeability of hydrophobic polyphenols used as supplements in the food industry. The spray-dried particles (SDPs) of NAR alone show an amorphous state with a glass transition temperature (T_g) at 93.2 °C. SDPs of hydrophobic polyphenols, such as flavone (FVO), quercetin (QCT), naringenin (NRG), and resveratrol (RVT) were prepared by adding varying amounts of NAR. All SDPs of hydrophobic polyphenols with added NAR were in an amorphous state with a single T_g, but SDPs of hydrophobic polyphenols without added NAR showed diffraction peaks derived from each crystal. The SDPs with NAR could keep an amorphous state after storage at a high humidity condition for one month, except for SDPs of RVT/NAR. SDPs with NAR enhanced the solubility of hydrophobic polyphenols, especially NRG solubility, which was enhanced more than 9 times compared to NRG crystal. The enhanced solubility resulted in the increased membrane permeability of NRG. The antioxidant effect of the hydrophobic NRG was also enhanced by the synergetic effect of NAR. The findings demonstrated that NAR could be used as a food additive to enhance the solubility and membrane permeability of hydrophobic polyphenols.     

Phosphorylated chitosan/poly(vinyl alcohol) based proton exchange membranes modified with propylammonium nitrate ionic liquid and silica filler for fuel cell applications

In our previous work, phosphorylated chitosan was modified through polymer blending with poly(vinyl alcohol) (PVA) polymer to produce N-methylene phosphonic chitosan/poly(vinyl alcohol) (NMPC/PVA) composite membranes. The aim of this work is to further investigate the effects of a propylammonium nitrate (PAN) ionic liquid and/or silicon dioxide (SiO₂) filler on the morphology and physical properties of NMPC/PVA composite membranes. The temperature-dependent ionic conductivity of the composite membranes with various ionic liquid and filler compositions was studied by varying the loading of PAN ionic liquid and SiO₂-PAN filler in the range of 5–20 wt%. As the loading of PAN ionic liquid increased in the NMPC/PVA membrane matrix, the ionic conductivity value also increased with the highest value of 0.53 × 10^?3 S cm^?1 at 25 °C and increased to 1.54 × 10^?3 S cm^?1 at 100 °C with 20 wt% PAN. The NMPC/PVA-PAN (20 wt%) composite membrane also exhibited the highest water uptake and ion exchange capacity, with values of 60.5% and 0.60 mequiv g^?1, respectively. In addition, in the single-cell performance test, the NMPC/PVA-PAN (20 wt%) composite membrane displayed a maximum power density, which was increased by approximately 14% compared to the NMPC/PVA composite membrane with 5 wt% SiO₂-PAN. This work demonstrated that modified NMPC/PVA composite membranes with ionic liquid PAN and/or SiO₂ filler showed enhanced performance compared with unmodified NMPC/PVA composite membranes for proton exchange membrane fuel cells.     

Highly stable nanocarbon supported Pt catalyst for fuel cell via a molten salt graphitization strategy

Proton exchange membrane fuel cells (PEMFCs) durability has been severely hindered by carbon support poor stability in the cathodic Pt-based catalyst. Herein, a high-surface-area nitrogen-doped graphitic nanocarbon (N-G-CA) with mesopores is developed as Pt support to address PEMFCs durability challenge. Resorcinol-formaldehyde aerogel pyrolyzed carbon aerogel is selected as N-G-CA raw material. Nitrogen atoms are introduced into carbon aerogel via NH₃ heat treatment. Then, nitrogen-doped carbon aerogel is transferred into N-G-CA via heating together with transition-metal salts (one of FeCl₃, FeCl₂, CoCl₂, or MnCl₂, etc.) at 1200 °C. As ORR catalyst, Pt/N-G-CA half-wave potential only lost 10 mV, after 30, 000 cycles accelerated aging test in the rotating-desk-electrode. Only 12 mV voltage loss at 1.5 A/cm2 is observed, after 5, 000 cycles for membrane electrode. Pt/N-G-CA exhibits superior durability and activity than commercial Pt/C. High durability of Pt/N-G-CA is due to N-G-CA high graphitization extent, as well as the interactions between doping nitrogen and Pt. N-G-CA is promising as stable support for durable Pt-based catalysts in PEMFCs, thanks to enhanced carbon corrosion resistance, uniformly dispersed Pt, and strong support-metals interaction.     

Preparation and antifouling performance of thin inorganic ultrafiltration membrane via assisted sol-gel method with different composition of dual additives

A novel TiO₂ thin film was prepared on the ceramic hollow fiber by the sol-gel method using poly(vinylpyrrolidone) (PVP) and polyvinyl alcohol (PVA) as additives. SEM images verified the formation of TiO₂ layer with various thickness using different composition of titania sols. The effect of the PVP and PVA contents on the TiO₂ sol properties, the separation and the antifouling performance of the ultrafiltration membranes were investigated thoroughly. When the contents of PVP and PVA were 1.0 wt% and 0.8 wt%, respectively, the resultant membrane showed a thickness of 0.55 μm with a pure water flux of 255 L m^?2 h^?1. In addition, the adherent foulant bovine serum albumin was applied to evaluate the antifouling performance. During the three fouling-recovery cycles, the flux recovery ratio and the flux decay ratio maintained about 99% and 30%. The BSA flux and rejection were still 169 L m^?2 h^?1 and 96.9% after the cycles, indicating a superior antifouling property.     

Identifying catalyst layer compositions of proton exchange membrane fuel cells through machine-learning-based approach

Membrane electrode assembly (MEA) is considered a key component of a proton exchange membrane fuel cell (PEMFC). However, developing a new MEA to meet desired properties, such as operation under low-humidity conditions without a humidifier, is a time- and cost-consuming process. This study employs a machine-learning-based approach using K-nearest neighbor (KNN) and neural networks (NN) in the MEA development process by identifying a suitable catalyst layer (CL) recipe in MEA. Minimum redundancy maximum relevance and principal component analysis were implemented to specify the most important predictor and reduce the data dimension. The number of predictors was found to play an essential role in the accuracy of the KNN and NN models although the predictors have self-correlations. The KNN model with a K of 7 was found to minimize the model loss with a loss of 11.9%. The NN model constructed by three corresponding hidden layers with nine, eight, and nine nodes can achieve the lowest error of 0.1293 for the Pt catalyst and 0.031 for PVA as a good additive blending in the CL of the MEA. However, even if the error is low, the prediction of PVA seems to be inaccurate, regardless of the model structure. Therefore, the KNN model is more appropriate for CL recipe prediction.