Determination of O<sub>2</sub>Mass Transport at the Pt | PFSA Ionomer Interface under Reduced Relative Humidity
Bibliographic record
Abstract
Oxygen mass transport resistance through the ionomer component in the cathode catalyst layer is considered to contribute overpotential losses in polymer electrolyte membrane fuel cells. Whereas it is known that water uptake, water transport, and proton conductivity are reduced upon reducing relative humidity, the effect on oxygen mass transport remains unknown. We report a two-electrode approach to determine mass transport coefficients for the oxygen reduction reaction in air at the Pt/perfluorosulfonic acid ionomer membrane interface between 90 and 30% RH at 70 °C using a Pt microdisk in a solid state electrochemical cell. Potential-step chronoamperometry was performed at specific mass-transport limiting potentials to allow for the elucidation of the oxygen diffusion coefficient (D(bO2)) and oxygen concentration (c(bO2)). In our efforts, novel approaches in data acquisition, as well as analysis, were examined because of the dynamic nature of the membrane under lowered hydration conditions. Linear regression analysis reveals a decrease in oxygen permeability (D(bO2c(bO2)) by a factor of 1.7 and 3.4 from 90 to 30% RH for Nafion 211 membrane and membranes cast from Nafion DE2020 ionomer solutions, respectively. Additionally, nonlinear curve fitting by way of the Shoup-Szabo equation is employed to analyze the entire current transient during potential step controlled ORR. We also report on the presence of an RH dependence of our previously reported time-dependency measurements for O2 mass transport coefficients.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| 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 | 0.001 | 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".