Effect of Cobalt Ion Exchange and Thermal Pretreatment of Ionomer Thin Films on Conductivity, Water Uptake and Swelling
Bibliographic record
Abstract
It is known that Cobalt (Co) can leach out from the Pt-Co alloy catalysts causing degradation of long-term fuel cell performance. Although the fundamental mechanism of performance loss is not fully understood, it has been hypothesized that the Co ion interacts with the nanothin ionomer films in the fuel cell catalyst layer by exchanging with the protons and thereby adversely affecting the performance. However, the effect of Cobalt ion, specifically and the transport properties of nanothin fluorinated ionomers films, in general is not fully known. We have studied the effect of cation(Cobalt) on spin-coated nanothin ionomers on its key properties – (i) proton conduction and water uptake which directly affects the electrochemical performance of fuel cell catalyst layers, and (ii) swelling behavior, which is an indicator of mechanical strength and thereby the durability of the ionomer. Electrochemical impedance spectroscopy (EIS) of films on interdigitated elecrodes for conductivity measurements, quartz crystal microbalance (QCM) for water uptake, and environmental ellipsometry for swelling measurement was employed, Quantification of exchanged Cobalt in nanothin films is non-trivial problem and we have used a set of x-ray techniques (EDX, XPS) for determination of cobalt in the cation exchanged films. In this work conductivity of the different ionomer thin film (~ 30 nm) were tested before and after Cobalt exchange at different temperatures (30-80 °C) and humidity (40-90 % RH) conditions. It was seen that the conductivity of the ionomer thin films decreased after Cobalt exchanged but the proton conduction of some of the non-commercial ionomers is not as strongly affected by Co ion exchange as that of the state-of-the-art Nafion ionomer. We also investigated the effect of ionomer thin film pretreatment on the conductivity of the cobalt exchanged ionomer. It was found that the the samples annealed at 160 °C and then cation exchanged by exposure to cobalt solution showed less reduction in conductivity than unannealed cation exchanged ionomer films. The presentation will share the details of the film preparation and characterization as well as the results for the conductivity, water uptake and swelling of the ionomer films. Figure 1
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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 | 0.000 | 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) | 0.001 | 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".