Neutron imaging of generated water inside polymer electrolyte fuel cell using newly-developed gas diffusion layer with gas flow channels during power generation

Nasu, Mitsunori; Yanai, Hiroshi; Hirayama, Naoki; Adachi, H.; Kakizawa, Yu; Shirase, Yuto; Nishiyama, Hiromichi; Kawamoto, Teppei; Inukai, Junji; Shinohara, T.; Hayashida, Hirotoshi; Watanabe, Masahiro

doi:10.1016/j.jpowsour.2022.231251

Cited by 32 publications

(15 citation statements)

References 43 publications

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“…This effect prevents water from accumulating in the porous rib part near the catalyst layer in a high humidity state, and also has the effect of suppressing the drying of the catalyst layer in a low humidity state, contributing to the stability of the cell performance under the severe conditions described above. While this model can explain the present results and is consistent with our previous neutron imaging study, 17 it will be necessary to test the model further with various types of imaging and visualization techniques. Efforts in this direction are now in progress.…”

Section: Resultssupporting

confidence: 88%

“…Our previous study is also considered to support our proposed model. 17 In that study, the amount of accumulated water in the porous ribs was larger than that in the flow channels when the newly designed cell was operated under the experimental condition with a current density of 3.0 A cm −2 and a relative humidity of 73% RH both in anode and cathode, which was measured by neutron imaging. We have successfully visualized the fact that generated water is accumulated in the porous ribs of the GDL near the exit.…”

Section: Resultsmentioning

confidence: 86%

“…The results show that this cell stack exhibited higher performance, especially at higher current density, than that of a conventional cell in which serpentine or interdigitated channels are formed on the separator. 17 This performance improvement was proposed to be due to the effect of the ribs being porous. However, it is necessary to elucidate both the detailed contribution to the improvement of cell performance and the mechanism.…”

mentioning

confidence: 99%

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Improvement of PEFC Performance Stability under High and Low Humidification Conditions by Use of a Gas Diffusion Layer with Interdigitated Gas Flow Channels

Inoue

Sakai

Hirota

et al. 2022

J. Electrochem. Soc.

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A new design concept for polymer electrolyte fuel cells, which included a flat-metal separator and a gas diffusion layer (GDL) with interdigitated gas flow channels (FCs), was developed in our previous research. This design led to improved performance compared to that obtained with the conventional design of a metal separator with FCs and a flat GDL. Applications of the interdigitated gas flow channels formed on the separator, however, have conventionally faced two issues associated with low performance: one occurs under high humidity conditions because of nonuniform gas flow due to accumulated water in the GDL and the other is caused by forced water discharge from the GDL under low humidity conditions. In this study, both conventional and new cell designs were tested with single cells of 1 cm2 active area, and the performances were compared at high and low humidity with various conditions of gas supply. From these results, we have found that the new design of the GDL with interdigitated channels has a clear advantage over the conventional interdigitated cell in being able to maintain high performance under conditions of both water excess and water shortage.

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Section: Resultssupporting

confidence: 88%

Section: Resultsmentioning

confidence: 86%

mentioning

confidence: 99%

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Improvement of PEFC Performance Stability under High and Low Humidification Conditions by Use of a Gas Diffusion Layer with Interdigitated Gas Flow Channels

Inoue

Sakai

Hirota

et al. 2022

J. Electrochem. Soc.

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“…Furthermore, these findings suggest that GDL and flow fields should be designed simultaneously, as even a slight misalignment of the weave holes and land such as the one observed here creates localised water flooding with extensive water retention in steady-state conditions. These complex design considerations between water management and PEMFC porous structure can also be probed with low-resolution operando experiments such as 2D neutron imaging and X-ray radiography 34 , 35 , 82 . These would supplement the numerical modelling of the super resolved images and could be used to tune and validate water management modelling for sensitivity studies.…”

Section: Resultsmentioning

confidence: 99%

Large-scale physically accurate modelling of real proton exchange membrane fuel cell with deep learning

et al. 2023

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Proton exchange membrane fuel cells, consuming hydrogen and oxygen to generate clean electricity and water, suffer acute liquid water challenges. Accurate liquid water modelling is inherently challenging due to the multi-phase, multi-component, reactive dynamics within multi-scale, multi-layered porous media. In addition, currently inadequate imaging and modelling capabilities are limiting simulations to small areas (<1 mm2) or simplified architectures. Herein, an advancement in water modelling is achieved using X-ray micro-computed tomography, deep learned super-resolution, multi-label segmentation, and direct multi-phase simulation. The resulting image is the most resolved domain (16 mm2 with 700 nm voxel resolution) and the largest direct multi-phase flow simulation of a fuel cell. This generalisable approach unveils multi-scale water clustering and transport mechanisms over large dry and flooded areas in the gas diffusion layer and flow fields, paving the way for next generation proton exchange membrane fuel cells with optimised structures and wettabilities.

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“…To optimize the mode of operation, the behavior of the water or gas inside the fuel cell under operating conditions needs to be clarified. Hence, operando measurements have been carried out for liquid water in the membrane electrode assembly (MEA) and the gas flow channels of fuel cells by direct optical systems, − X-ray imaging, , neutron imaging, − and vibrational spectroscopy. − Recently, the oxygen partial pressure ( p (O 2 )) using oxygen-sensitive dye is measured during the power generation. − Higher special and temporal resolutions are being required for those operando measurements to understand the transient behavior in PEMFC especially used for automobile applications.…”

Section: Introductionmentioning

confidence: 99%

Operando Monitoring of Oxygen Drop in Catalyst Layers Accompanied by a Water Increase in Running Proton Exchange Membrane Fuel Cells

Nishiyama

Inukai

2023

ACS Omega

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Accurate understanding of internal phenomena and their feedback is intrinsically important for improving the performance and durability of proton exchange membrane fuel cells. The oxygen partial pressure (p(O2)) at 10 μm from the cathode catalyst layer (CL) in the gas diffusion layer was measured by using an optical fiber with an oxygen-sensitive dye applied to the apex, when the current density was abruptly increased. p(O2) decreased with increasing current density at constant air utilization. This decrease in oxygen partial pressure is attributed to the increased amount of water at the CL at the cathode due to the oxygen reduction reaction and electro-osmotic drag, as previously proposed. A shortage of oxygen in the CL for 1 s was also detected by using this p(O2) monitoring. These results are consistent with the previous results obtained by operando time-resolved measurements of the water distribution in the electrolyte membranes of a running fuel cell.

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Neutron imaging of generated water inside polymer electrolyte fuel cell using newly-developed gas diffusion layer with gas flow channels during power generation

Cited by 32 publications

References 43 publications

Improvement of PEFC Performance Stability under High and Low Humidification Conditions by Use of a Gas Diffusion Layer with Interdigitated Gas Flow Channels

Improvement of PEFC Performance Stability under High and Low Humidification Conditions by Use of a Gas Diffusion Layer with Interdigitated Gas Flow Channels

Large-scale physically accurate modelling of real proton exchange membrane fuel cell with deep learning

Operando Monitoring of Oxygen Drop in Catalyst Layers Accompanied by a Water Increase in Running Proton Exchange Membrane Fuel Cells

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