Understanding Membrane Degradation Mechanisms Under Heavy Duty Fuel Cell Conditions: A Multi-Disciplinary Approach
Bibliographic record
Abstract
The Automotive Partnership of Canada (APC) project on Next-Gen Heavy Duty Fuel Cell Buses is a government supported three-year project dedicated to research and product development of next generation heavy duty fuel cell buses in Canada (www.apc-hdfc.ca). The project represents a collaborative effort between Ballard Power Systems, Simon Fraser University and University of Victoria in British Columbia, Canada. The overarching objective is fundamental understanding of membrane degradation mechanisms, degradation rates, and failure modes under drive cycles and conditions that are typical for heavy duty vehicle operation. The aim is to help develop next generation fuel cell technology that is equivalent to or surpasses incumbent diesel engines in terms of durability and reliability, while reducing capital and warranty costs. In order to develop new durable membrane technologies and devise mitigation strategies to reach desired membrane lifetime, empirical and physical models need to be developed and employed. In this context, understanding the relationship between operation mode and membrane degradation under heavy duty fuel cell conditions is of vital importance. Apart from mechanical degradation such as thinning and pinhole formations, chemical and electrochemical degradation could also take place in perfluorosulfonated acid (PFSA) ionomer membranes. Due to complexity of the underlying processes, degradation mechanisms and their dependence on relevant operating conditions are not generally well established. We present results from an extensive effort that integrates multi-scale, multi-disciplinary modeling with large–scale accelerated degradation testing data. Results are analysed in view of the relative importance of various membrane degradation mechanisms via various chemical and mechanical processes. The versatile multi-scale modeling framework includes structure formation at molecular/meso-scales, water sorption characteristics, kinetics, as well as continuum modelling of chemical and mechanical degradation processes. References [1] F. de Bruijn, et al., Fuel Cells 8(1), 2008, 3–22 [2] Cheng Chen, T. F. Fuller, Modeling of Hydrogen Peroxide Formation in PEMFCs, Electrochim. Acta, 54, 3984-3995 (2009). [3] N. Macauley, L. Ghassemzadeh, C. Lim, M. Watson, J. Kolodziej, M. Lauritzen, S. Holdcroft, E. Kjeang, “Pt Band Formation Enhances the Stability of Fuel Cell Membranes”, ECS Electrochemistry Letters, 2(4) (2013) F1-F3. [4] L. Ghassemzadeh, S. Holdcroft, "Quantifying the structural changes of PFSA ionomer upon reaction with hydroxy radicals”, JACS, 2013, 135 (22) (2013), 8181-8184. [5] R. M.H. Khorasany et al., “On the Constitutive Relations for Catalyst Coated Membrane Applied to In-Situ Fuel Cell Modeling”, 2013, submitted. Fig. 1: APC project on heavy duty bus fuel cells (www.apc-hdfc.ca).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".