Method to improve catalyst layer model for modelling proton exchange membrane fuel cell

Correctly describing oxygen reduction within the cathode catalyst layer (CL) in modelling proton exchange membrane fuel cell is an important issue remaining unresolved. In this paper we show how to derive an agglomerate model for calculating oxygen reactions by describing dissolved oxygen in the agglomerates using two independent random processes. The first one is the probability that an oxygen molecule, which dissolves in the ionomer film on the agglomerate surface, moves into and then remains in the agglomerates; the second one is the probability of the molecule being consumed in reactions. The first probability depends on CL structure and can be directly calculated; the second one is derived by assuming that the oxygen reduction is first-order kinetic. It is found that the distribution functions of the first process can be fitted to a generalised gamma distribution function, which enables us to derive an analytical agglomerate model. We also expend the model to include oxygen dissolution in the ionomer film, and apply it to simulate cathode electrodes. The results reveal that the resistance to oxygen diffusion in ionomer film and agglomerate in modern CL is minor, and that the main potential loss is due to oxygen dissolution in the ionomer film

Modelling water intrusion and oxygen diffusion in a reconstructed microporous layer of PEM fuel cells

The hydrophobic microporous layer (MPL) in PEM fuel cell improves water management but reduces oxygen transport. We investigate these conflict impacts using nanotomography and pore-scale modelling. The binary image of a MPL is acquired using FIB/SEM tomography. The water produced at the cathode is assumed to condense in the catalyst layer (CL), and then builds up a pressure before moving into the MPL. Water distribution in the MPL is calculated from its pore geometry, and oxygen transport through it is simulated using pore-scale models considering both bulk and Knudsen diffusions. The simulated oxygen concentration and flux at all voxels are volumetrically averaged to calculate the effective diffusion coefficients. For water flow, we found that when the MPL is too hydrophobic, water is unable to move through it and must find alternative exits. For oxygen diffusion, we found that the interaction of the bulk and Knudsen diffusions at pore scale creates an extra resistance after the volumetric average, and that the conventional dusty model substantially overestimates the effective diffusion coefficient

A proposed agglomerate model for oxygen reduction in the catalyst layer of proton exchange membrane fuel cells

Oxygen diffusion and reduction in the catalyst layer of PEM fuel cell is an important process in fuel cell modelling, but models able to link the reduction rate to catalyst-layer structure are lack; this paper makes such an effort. We first link the average reduction rate over the agglomerate within a catalyst layer to a probability that an oxygen molecule, which is initially on the agglomerate surface, will enter and remain in the agglomerate at any time in the absence of any electrochemical reaction. We then propose a method to directly calculate distribution function of this probability and apply it to two catalyst layers with contrasting structures. A formula is proposed to describe these calculated distribution functions, from which the agglomerate model is derived. The model has two parameters and both can be independently calculated from catalyst layer structures. We verify the model by first showing that it is an improvement and able to reproduce what the spherical model describes, and then testing it against the average oxygen reductions directly calculated from pore-scale simulations of oxygen diffusion and reaction in the two catalyst layers. The proposed model is simple, but significant as it links the average oxygen reduction to catalyst layer structures, and its two parameters can be directly calculated rather than by calibration

Lattice Boltzmann simulation of water and gas flow in porous gas diffusion layers in fuel cells reconstructed from micro-tomography

The porous gas diffusion layers (GDLs) are key components in hydrogen fuel cells. During their operation the cells produce water at the cathode, and to avoid flooding, the water has to be removed out of the cells. How to manage the water is therefore an important issue in fuel cell design. In this paper we investigated water flow in the GDLs using a combination of the lattice Boltzmann method and X-ray computed tomography at the micron scale. Water flow in the GDL depends on water–air surface tension and hydrophobicity. To correctly represent the water–gas surface tension, the formations of water droplets in air were simulated, and the water–gas surface tension was obtained by fitting the simulated results to the Young–Laplace formula. The hydrophobicity is represented by the water–gasfabric contact angle. For a given water–gas surface tension the value of the contact angle was determined by simulating the formations of water droplets on a solid surface with different hydrophobicity. We then applied the model to simulate water intrusion into initially dry GDLs driven by a pressure gradient in attempts to understand the impact of hydrophobicity on water distribution in the GDLs. The structures of the GDL were acquired by X-ray micro-tomography at a resolution of 1.7 microns. The simulated results revealed that with an increase in hydrophobicity, water transport in GDLs changes from piston-flow to channelled flow

The impacts of image resolution on permeability simulation of gas diffusion layer using lattice Boltzmann method

The effect of image resolution on gas permeability through the x-ray reconstructed carbon paper gas diffusion layer (GDL) of a polymer electrolyte fuel cell (PEFC) is examined in this paper. The 3D models of the GDL at six different resolutions are obtained by the x-ray tomography imaging technique. Each GDL image is then characterized its gas permeability through the lattice Boltzmann (LB) numerical method. The results suggest that the image resolution has a great impact on gas permeability in both principal and off-principal flow directions. The coarser resolutions can contribute to significant changes in the resulting permeability. However, it can reduce computational time to a great extent. The results also indicate that the GDL image at the resolution of 2.72 μm provides a good compromise between computational time and accuracy

Simulation of liquid water beakthrough in a nano-tomography reconstruction of a carbon paper gas diffusion layer

This study reports the feasibility of newly simulating liquid water intrusion into the porous gas diffusion layer (GDL) of a polymer electrolyte fuel cell (PEFC) using X-ray nano-tomography and two-phase lattice Boltzmann (LB) simulation. A digital 3D model of the GDL is reconstructed using X-ray nanotomography while two-phase porous flow is simulated at two different levels of surface wettability by applying a newly-developed numerical LB model. The results show liquid infiltration in a hydrophobic GDL is comparatively lower (pore saturation of 0.11 to 0.90) than that for a hydrophilic GDL (pore saturation of 0.36 to 0.96) over the liquid intrusion range of 1 kPa . 100 kPa. Visualisation of simulated results in three dimensions reveal dissimilar liquid infiltration characteristics for the two levels of wettability considered, yet also reveal a general breakthrough of liquid water at a pressure of 10 kPa due to specific structural features of the GDL

Multiscale modeling of single-phase multicomponent transport in the cathode gas diffusion layer of a polymer electrolyte fuel cell

This research reports a feasibility study into multiscale polymer electrolyte fuel cell (PEFC) modeling through the simulation of macroscopic flow in the multilayered cell via one-dimensional (1D) electrochemical modeling, and the simulation of microscopic flow in the cathode gas diffusion layer (GDL) via three-dimensional (3D) single-phase multicomponent lattice Boltzmann (SPMC-LB) modeling. The heterogeneous porous geometry of the carbon-paper GDL is digitally reconstructed for the SPMC-LB model using X-ray computer microtomography. Boundary conditions at the channel and catalyst layer interfaces for the SPMC-LB simulations such as specie partial pressures and through-plane flowrates are determined using the validated 1D electrochemical model, which is based on the general transport equation (GTE) and volume-averaged structural properties of the GDL. The calculated pressure profiles from the two models are cross-validated to verify the SPMC-LB technique. The simulations reveal a maximum difference of 2.4% between the thickness-averaged pressures calculated by the two techniques, which is attributable to the actual heterogeneity of the porous GDL structure

Nondestructive testing of grating imperfections using grating-based X-ray phase-contrast imaging

We reported the usage of grating-based X-ray phase-contrast imaging in nondestructive testing of grating imperfections. It was found that electroplating flaws could be easily detected by conventional absorption signal, and in particular, we observed that the grating defects resulting from uneven ultraviolet exposure could be clearly discriminated with phase-contrast signal. The experimental results demonstrate that grating-based X-ray phase-contrast imaging, with a conventional low-brilliance X-ray source, a large field of view and a reasonable compact setup, which simultaneously yields phase- and attenuation-contrast signal of the sample, can be ready-to-use in fast nondestructive testing of various imperfections in gratings and other similar photoetching products.Comment: 6 pages, 5 figures and 2 table

Determination of the anisotropic permeability of a carbon cloth gas diffusion layer through X-ray computer micro-tomography and single-phase lattice Boltzmann simulation

An investigation of the anisotropic permeability of a carbon cloth gas diffusion layer (GDL) based on the integration of X-ray micro-tomography and lattice Boltzmann (LB) simulation is presented. The method involves the generation of a 3D digital model of a carbon cloth GDL as manufactured using X-ray shadow images acquired through X-ray micro-tomography at a resolution of 1.74 µm. The resulting 3D model is then split into 21 volumes and integrated with a LB single-phase numerical solver in order to predict three orthogonal permeability tensors when a pressure difference is prescribed in the through-plane direction. The 21 regions exhibit porosity values in the range of 0.910–0.955, while the average fibre diameter is 4 µm. The results demonstrate that the simulated through-plane permeability is about four times higher than the in-plane permeability for the sample imaged and that the corresponding degrees of anisotropy for the two orthogonal off-principal directions are 0.22 and 0.27. The results reveal that flow channelling can play an important role in gas transport through the GDL structure due to the non-homogeneous porosity distribution through the material. The simulated results are also applied to generate a parametric coefficient for the Kozeny–Carman (KC) method of determining permeability. The current research reveals that by applying the X-ray tomography and LB techniques in a complementary manner, there is a strong potential to gain a deeper understanding of the microscopic fluidic phenomenon in representative models of porous fuel cell structures and how this can influence macroscopic transport characteristics which govern fuel cell performance

MASALAH-MASALAH PEMBELAJARAN YANG DIHADAPI WIDYAISWARA : Studi Kasus Pada Lembaga Diktat Pemda Tk.I Propinsi Bengkulu

<div><p>Rat strains differ dramatically in their susceptibility to mammary carcinogenesis. On the assumption that susceptibility genes are conserved across mammalian species and hence inform human carcinogenesis, numerous investigators have used genetic linkage studies in rats to identify genes responsible for differential susceptibility to carcinogenesis. Using a genetic backcross between the resistant Copenhagen (Cop) and susceptible Fischer 344 (F344) strains, we mapped a novel mammary carcinoma susceptibility (<i>Mcs30</i>) locus to the centromeric region on chromosome 12 (LOD score of ∼8.6 at the D12Rat59 marker). The <i>Mcs30</i> locus comprises approximately 12 Mbp on the long arm of rat RNO12 whose synteny is conserved on human chromosome 13q12 to 13q13. After analyzing numerous genes comprising this locus, we identified <i>Fry</i>, the rat ortholog of the furry gene of <i>Drosophila melanogaster,</i> as a candidate <i>Mcs</i> gene. We cloned and determined the complete nucleotide sequence of the 13 kbp <i>Fry</i> mRNA. Sequence analysis indicated that the <i>Fry</i> gene was highly conserved across evolution, with 90% similarity of the predicted amino acid sequence among eutherian mammals. Comparison of the <i>Fry</i> sequence in the Cop and F344 strains identified two non-synonymous single nucleotide polymorphisms (SNPs), one of which creates a putative, de novo phosphorylation site. Further analysis showed that the expression of the <i>Fry</i> gene is reduced in a majority of rat mammary tumors. Our results also suggested that FRY activity was reduced in human breast carcinoma cell lines as a result of reduced levels or mutation. This study is the first to identify the <i>Fry</i> gene as a candidate <i>Mcs</i> gene. Our data suggest that the SNPs within the <i>Fry</i> gene contribute to the genetic susceptibility of the F344 rat strain to mammary carcinogenesis. These results provide the foundation for analyzing the role of the human <i>FRY</i> gene in cancer susceptibility and progression.</p></div