In-Situ x-Ray Diffraction Study of Pt(111) Oxidation during Oxygen Reduction Reaction (ORR)
Bibliographic record
Abstract
ORR is one of the most studied electrochemical reactions due to it’s tremendous fundamental and practical importance. Oxygen is common, readily accessible oxidizing agent and therefore Pt ORR cathode is part of many energy conversion devices, e.g., fuel cells. Unfortunately, slow kinetics of ORR negatively affects the performance and it is currently one of the main bottleneck in large scale fuel cells commercialization. It is partly caused by the presence of surface Pt oxides, which slow the reaction rate and trap reaction intermediates on the surface. The oxide formation and dissolution is also known to cause dissolution of Pt catalyst, which further degrades the performance. Even though the electrochemical formation of surface oxides on platinum surface has been extensively studied in the past, there are still many questions unanswered. Mainly about the detailed structure of the oxide and its growth mechanism [1 and references there-in]. Most of the studies were performed in the absence of O2, the fuel cell oxidant, and therefore they are less relevant to the fuel cell operation as gaseous O2 can modify the oxidation potentials and mechanism. Given the above, further fundamental understanding of Pt oxidation mechanism measured in-situ is clearly needed in order to determine the role of surface oxides in ORR and its effect on the fuel cell performance. Here we show the results of in-situ study of electrochemical oxide formation on Pt(111) and how it is influenced by presence of O2 during ORR. We find that oxide growth, and Pt-O site switching, is present as soon as 700 mV vs. Ag|AgCl reference electrode in 0.1M HClO4 and causes slow, irreversible roughening of the surface. When the potential is increased, the roughening is more severe and after several tens of cycles from -125 mV to 900 mV, the surface loses it’s order. This is seemingly in contradiction with widely accepted notion that cycling the Pt(111) up to 900 mV does not affect significantly surface structure. We show that the roughening is dependent on the initial state of the sample and it is an autocatalytic process. Adding oxygen into the electrolyte does not have any notable effect on the oxidation potentials or kinetics and it is in disagreement with previous results where negative shift of the oxidation onset was observed in O2 containing electrolyte [2]. This results points to the fact that OH- is dominated species during Pt electrooxidation and oxygen has only a side role. However, depending on the history of the sample, it is likely that PtO species are present on the surface and should be taken into the account in theoretical investigations. [1] Kongkanand and Ziegelbauer, Journal of Physical Chemistry C, 116 (2012) 3684-3693; [2] Matsumoto, Miyazaki, Imai, Phys. Chem. C, 115 (2011) 11163−11169.
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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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".