Two-Dimensional Graphdiyne-Confined Platinum Catalyst for Hydrogen Evolution and Oxygen Reduction Reactions
Bibliographic record
Abstract
Pt-based materials are the state-of-the-art catalysts for hydrogen evolution reaction (HER) and oxygen reduction reaction (ORR); however, there is still much room to improve the catalytic activity and enhance the stability of Pt-based catalysts. In this work, two-dimensional (2D) graphdiyne (GDY) with uniform distributed pores was applied to cover the Pt surface for catalyzing HER and ORR through density functional theory (DFT) calculations. The 2D confinement induced by GDY was found to improve the catalytic performance of the Pt catalyst from three aspects: (1) the 2D covering layer increases the stability of the Pt catalyst through forming the heterogeneous interface of GDY/Pt(111); (2) GDY/Pt(111) shows better catalytic activities of HER and ORR, with the smaller average overpotential values of 0.26 and 0.51 V, respectively, compared with those (0.29 V for HER, 0.62 V for ORR) on the Pt catalyst; (3) the confinement effect of GDY weakens the adsorption energy of CO to -1.81 eV (average value) from -2.14 eV on Pt(111), inhibiting CO poisoning. This work sheds new light on 2D confinement effects for HER and ORR, which opens up a new strategy for improving the catalytic performance of Pt-based catalysts.
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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 | 0.000 |
| 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".