Carboxyl Group Enhanced CO Tolerant GO Supported Pt Catalysts: DFT and Electrochemical Analysis
Bibliographic record
Abstract
Abstract The effect of residual oxygen species in as-prepared Pt nanoparticle on partially reduced graphene oxide (Pt/PRGO) and partially reduced carboxylated-GO (Pt/PR(GO–COOH)) supports was investigated using electrochemical CO stripping and density functional theory (DFT) analysis. Pt/PRGO and Pt/PR(GO–COOH) revealed a clear negative shift in CO-stripping onset potential compared to commercial Pt/carbon black. DFT analysis confirmed that the presence of a −COOH group provides the most resistance for CO adsorption. This CO-Pt binding energy is significantly lower than that observed in the presence of an −OH group, which is the most abundant oxygen group in carbon supports. The Pt-CO dissociation energies (on a 42-atom graphene sheet) in the presence of various oxygen groups, in descending order, were OH > C═O ≈ C–O–C > COOH. Although single-bonded carbon–oxygen groups (−OH and C–O–C) are more abundant on the GO basal plane and play an important role in Pt nanoparticle nucleation and distribution on graphene sheets, the double-bonded carbon–oxygen (C═O and COOH) groups are more abundant residual species post Pt nanoparticle growth and play a vital role in enhancing CO tolerance.
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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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".