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Enregistrement W4285497302 · doi:10.1149/ma2022-01351436mtgabs

Channel Diameter Effect of Porous Carbon Microparticles on PEMFC Performance for Highly Active Ultra-Low Pt Catalysts

2022· article· en· W4285497302 sur OpenAlexaff
Hee‐Eun Kim, Young Jun Lee, Hyunjoo Lee

Notice bibliographique

RevueECS Meeting Abstracts · 2022
Typearticle
Langueen
DomaineEngineering
ThématiqueFuel Cells and Related Materials
Établissements canadiensKootenay Association for Science & Technology
Organismes subventionnairesnon disponible
Mots-clésProton exchange membrane fuel cellCatalysisMaterials scienceChemical engineeringCathodeMembrane electrode assemblyMesoporous materialPorosityBattery (electricity)NanotechnologyElectrodeComposite materialChemistryAnodePower (physics)Organic chemistry

Résumé

récupéré en direct d'OpenAlex

Proton exchange membrane fuel cells (PEMFCs) have received much attention as environmentally benign automotive power sources. PEMFCs can offer a large amount of electricity required for autonomous vehicles that battery-powered systems may not be able to provide. However, because PEMFC electrodes are based on expensive and scarce Pt catalysts, Pt minimization is necessary to expand the PEMFC market. To reduce Pt usage, various attempts have been made to increase the intrinsic activity of Pt catalysts, particularly at the cathode where the oxygen reduction reaction (ORR) occurs. Despite decades of progress, high ORR activity was typically reported in half-cell setups and frequently failed to show corresponding performance in single-cell. Catalysts with low Pt content perform poorly in the high-current density region because the thick catalyst layer limits mass transport. [1] In addition, low Pt loading catalysts typically suffer more in long-term operation. [2] As a result, it is critical to develop PEMFC catalysts with low Pt content that can facilitate mass transport while also exhibiting high durability. Herein, we report highly active and durable PtFe@C catalysts with ultra-low amounts of Pt (1 wt%) on channeled mesoporous carbon (CMC) particles. These CMC particles are designed to have continuous channels with open porosity and a large surface area, facilitating the mass transport behavior and maximizing cell performance. Block-copolymer particles (BCPs) with different molecular weights were used to fabricate CMC particles with pore diameters ranging from 13 to 63 nm. Two steps of pre-crosslinking and hyper-crosslinking were conducted prior to the carbonization step to preserve the porous internal structure of the BCP-based carbon support during high-temperature treatment. After depositing Pt onto the support by facile incipient wetness impregnation method followed by reduction, thin layers of carbon shell were observed to encapsulate the PtFe alloy nanoparticles. The channel diameter effect on the mass transport was studied in both half-cell and single-cell. Interestingly, from the cell performance obtained with varying channel diameters and different oxygen concentrations, we concluded that both reactant (proton and oxygen) supply and product (water) removal were greatly enhanced with larger channel size. With the largest channel diameter of 63 nm, initial mass activity in the single-cell was obtained to be 3.5 A mg Pt -1 , which is the highest value reported to date to the best of our knowledge. Cell performance under H 2 -air flow, which is the industrially relevant condition, surpassed the commercial 20 wt% Pt/C with only 1/20 of the Pt loading. The origin of enhanced cell performance upon enlarging the channel diameter was investigated by separating kinetic, ohmic (electronic and ionic charge transport), and mass transport overpotentials. Both the proton and oxygen transport resistance were confirmed to be reduced with larger channel size. Moreover, carbon shell protected Fe from getting leached out in an acidic environment, resulting in preserved catalyst structure and high durability. The outstanding performance of 51 kW/g Pt in H 2 /air condition after 30,000 cycles of accelerated degradation tests (ADTs) was observed. This work will open a new paradigm to develop PEMFC catalysts with much higher activity and durability while simultaneously minimizing Pt use. References [1] A. Kongkanand, M. F. Mathias, J . Phys. Chem. Lett. 2016 , 7 , 1127-1137. [2] R. Borup , A. Weber, Fuel Cell Performance and Durability Consortium, US DOE 2019 Annual Merit Review Proceedings, https://www.hydrogen.energy.gov/pdfs/review19/fc135_borup_2019_o.pdf (accessed: September 2021).

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: Expérimental (laboratoire)
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,476
Score d'incertitude au seuil0,729

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,006
Tête enseignante GPT0,192
Écart entre enseignants0,187 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeExpérimental (laboratoire)
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations1
Publié2022
Routes d'admission1
Résumé présentoui

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