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Enregistrement W2431096237 · doi:10.2172/1087665

Final Project Report: Development of Micro-Structural Mitigation Strategies for PEM Fuel Cells: Morphological Simulations and Experimental Approaches

2013· report· en· W2431096237 sur OpenAlexfundno aff
Silvia Wessel, David J. Harvey

Notice bibliographique

Revuenon disponible
Typereport
Langueen
DomaineEngineering
ThématiqueFuel Cells and Related Materials
Établissements canadiensnon disponible
Organismes subventionnairesMultiple System Atrophy CoalitionBallard Power SystemsGeorgia Institute of Technology
Mots-clésDurabilityProton exchange membrane fuel cellCatalysisCommercializationDegradation (telecommunications)Materials scienceDissolutionProcess engineeringEnvironmental scienceChemical engineeringEngineeringFuel cellsChemistryComposite materialBusinessElectrical engineering

Résumé

récupéré en direct d'OpenAlex

The durability of PEM fuel cells is a primary requirement for large scale commercialization of these power systems in transportation and stationary market applications that target operational lifetimes of 5,000 hours and 40,000 hours by 2015, respectively. Key degradation modes contributing to fuel cell lifetime limitations have been largely associated with the platinum-based cathode catalyst layer. Furthermore, as fuel cells are driven to low cost materials and lower catalyst loadings in order to meet the cost targets for commercialization, the catalyst durability has become even more important. While over the past few years significant progress has been made in identifying the underlying causes of fuel cell degradation and key parameters that greatly influence the degradation rates, many gaps with respect to knowledge of the driving mechanisms still exist; in particular, the acceleration of the mechanisms due to different structural compositions and under different fuel cell conditions remains an area not well understood. The focus of this project was to address catalyst durability by using a dual path approach that coupled an extensive range of experimental analysis and testing with a multi-scale modeling approach. With this, the major technical areas/issues of catalyst and catalyst layer performance and durability that were addressed are: 1. Catalyst and catalyst layer degradation mechanisms (Pt dissolution, agglomeration, Pt loss, e.g. Pt in the membrane, carbon oxidation and/or corrosion). a. Driving force for the different degradation mechanisms. b. Relationships between MEA performance, catalyst and catalyst layer degradation and operational conditions, catalyst layer composition, and structure. 2. Materials properties a. Changes in catalyst, catalyst layer, and MEA materials properties due to degradation. 3. Catalyst performance a. Relationships between catalyst structural changes and performance. b. Stability of the three-phase boundary and its effect on performance/catalyst degradation. The key accomplishments of this project are: • The development of a molecular-dynamics based description of the carbon supported-Pt and ionomer system • The development of a composition-based, 1D-statistical Unit Cell Performance model • A modified and improved multi-pathway ORR model • An extension of the existing micro-structural catalyst model to transient operation • The coupling of a Pt Dissolution model to the modified ORR pathway model • The Development A Semi-empirical carbon corrosion model • The integration and release of an open-source forward predictive MEA performance and degradation model • Completion of correlations of BOT (beginning of test) and EOT (end of test) performance loss breakdown with cathode catalyst layer composition, morphology, material properties, and operational conditions • Catalyst layer durability windows and design curves • A design flow path of interactions from materials properties and catalyst layer effective properties to performance loss breakdown for virgin and degraded catalyst layers In order to ensure the best possible user experience we will perform a staged release of the software leading up to the webinar scheduled in October 2013. The release schedule will be as follows (please note that the manual will be released with the beta release as direct support is provided in Stage 1): • Stage 0 - Internal Ballard Release o Cross check of compilation and installation to ensure machine independence o Implement code on portable virtual machine to allow for non-UNIX use (pending) • Stage 1 - Alpha Release o The model code will be made available via a GIT, sourceforge, or other repository (under discussion at Ballard) for download and installation by a small pre-selected group of users o Users will be given three weeks to install, apply, and evaluate features of the code, providing feedback on issues or software bugs that require correction prior to beta release • Stage 2 - Beta Release o The model code repository is opened to the general public on a beta release concept, with a mechanism for bug tracking and feedback from a large user group o Code will be tracked and patched for any discovered bugs or relevant feedback from the user community, upon the completion of three months without a major bug submission the code will be moved to a full version release • Stage 3 - Full Version Release o Code is version to revision 1.0 and that version is frozen in development/patching

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 machine sur la base complète

Imitation des enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,001
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Simulation ou modélisation · Signal consensuel: Simulation ou modélisation
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,006
Score d'incertitude au seuil0,020

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,001
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0000,001
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0010,001
Science ouverte0,0010,001
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0060,001

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 Opus0,091
Tête enseignante GPT0,290
Écart entre enseignants0,199 · 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 source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSimulation ou modélisation
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

Citations3
Publié2013
Routes d'admission1
Résumé présentoui

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