Investigating the Influence of Inlet Relative Humidity on Polymer Electrolyte Membrane Fuel Cell Performance by Visualizing 4-D Water Distributions in Gas Diffusion Layers
Notice bibliographique
Résumé
The catastrophic effects of atmospheric greenhouse gases and the depletion of non-renewable resources has led to the urgency to develop clean, sustainable energy technologies to meet increasing energy demands. However, the intermittent nature of current renewable energy technologies warrants the acquisition of on-demand renewable energy through either energy production or storage methods. Polymer electrolyte membrane fuel cells (PEMFCs) are promising candidates for this task, as they utilize the most abundant element on Earth, hydrogen, to produce high amounts of power under rapid changes in load with little to no greenhouse gas emissions (1). Therefore, PEMFCs have great potential to help offset the negative impact of atmospheric pollution due to excessive carbon emissions. However, liquid water management issues associated with high power output of the fuel cell typically leads to reduced performance and durability of the fuel cell, and thereby hinders global implementation of these devices (2). To minimize these losses and improve GDL material designs, an understanding of the relationship between product liquid water distributions in the cathode GDL and transport properties of PEMFCs under varying operating conditions is highly valuable. Previous works have characterized the effect of operating temperature on liquid water pathways and distributions in GDLs by visualizing operando PEMFCs with 3D imaging techniques such as X-ray computed tomography (CT) (3). The high-speed, high-resolution capabilities of these imaging techniques enable the visualization of dynamic pore-scale activity to elucidate transport mechanisms in the GDL. In this work, the effect of inlet relative humidity on the formation and distribution of liquid water pathways in cathode GDLs is investigated by imaging a PEMFC operando with synchrotron X-ray CT at high spatial resolution, enabling the resolution of water in the individual pores of the GDL. The contribution of a microporous layer (MPL) is also explored by imaging a cell with an MPL and without. Imaging is conducted on a specialized cell designed to facilitate continuous rotation about the CT stage, enabling fast acquisition of consecutive scans to achieve high temporal resolution useful for visualizing the dynamic development of preferential water pathways. Additionally, electrochemical impedance spectroscopy was performed to quantify mass transport losses. The sequence of CT images was utilized to capture the dynamics of liquid water development as well as stabilized water distributions. Visualizing the reconstructed images shows that as current increases, water production increases, and the development of water pathways to breakthrough at the flow field interface is observed. Additionally, results show that an increase in relative humidity led to a significant increase in cathode GDL water saturation. The contribution of this study to understanding transport mechanisms in GDL materials is significant to the characterization and optimal design of materials for improved PEMFC performance. Ultimately, the goal of this work is to accelerate the worldwide adoption of PEMFCs as a sustainable, reliable solution to replace conventional carbon-emitting energy sources. 1. Alaswad et al., J. Hydrog. Energy, 41, (2016) 2. Nagai et al., J. Power Sources, 435, (2019) 3. D. Shum et al., Electrochem. Acta, 256, (2017)
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».