A Study of the Catalytic Interface for O<sub>2</sub> Electroreduction on Pt: The Interaction between Carbon Support Meso/Microstructure and Ionomer (Nafion) Distribution
Bibliographic record
Abstract
The catalytic activity of PEM fuel cell electrodes is determined by the complex physicochemical interactions among the components of the electrocatalytic interface: precious metal catalyst, support, and ionomer. In the present study, the effect of the carbon support meso- and microporosity was investigated in relation with both the Nafion content and distribution in the catalyst layer. The ionomer load was between 0.09 and 1.1 mg cm −2 in the catalyst layers prepared either by the Nafion-coated or Nafion-mixed techniques, while the Pt load was kept constant at 0.1 mg cm −2 . Three supports were investigated: Vulcan XC-72R, Denka, and graphitized carbon (GC). Employing both the BET (Brunauer−Emmett−Teller) and the BJH (Barrett−Joyner−Halenda) surface measurement techniques, a complete characterization of the support and supported catalyst (Pt/C) pore volume distribution and surface area in the micro- and mesopore size ranges was carried out. It was found that Pt nanoparticles (mean diameter between 4.1−4.9 nm by XRD) reduced the micropore volume of the carbon supports. Therefore, the supports with high BJH mesoporous area (Vulcan XC-72R and GC) yielded Pt/C catalysts with the highest electrochemically active Pt area as well. For the Denka support, characterized by the lowest BJH area, the Nafion-coated procedure gave about 7% larger electrochemically active area compared to the Nafion-mixed method. Regarding the oxygen electroreduction, the effective oxygen permeability in the catalyst layer, the intrinsic kinetic current density, and the area and mass-specific activities at 0.9 V RHE were determined as a function of support type, Nafion incorporation method, and load.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".