Integrated Pt<sub><i>x</i></sub>Co<sub><i>y</i></sub>-Hierarchical Carbon Matrix Electrocatalyst for Efficient Hydrogen Evolution Reaction
Bibliographic record
Abstract
Pt-based catalysts are regarded as state-of-the-art electrocatalysts for producing clean hydrogen energy; however, their wide application is restricted by their low abundance, high cost, and poor stability. Herein, we report an integrated Pt x Co y -hierarchical carbon matrix electrocatalyst (Pt/Co@NCNTs, Pt 3 Co@NCNTs, PtCo@NCNTs, and PtCo 3 @NCNTs) that is developed using a thermally driven Co migration strategy forming alloy nanoparticles to achieve efficient hydrogen evolution reaction (HER). Benefiting from its electronic regulation effect and unique hierarchical hollow structure, the Pt 3 Co@NCNTs catalyst loaded with 11.5 wt % Pt exhibits superior catalytic performance and durability for HER compared with commercial 20 wt % Pt/C. Under both alkaline and acidic conditions, Pt 3 Co@NCNTs exhibits excellent HER activity with overpotentials of 21 and 45 mV at 10 mA cm –2, respectively. Density functional theory (DFT) results further verify that the interaction between Pt and Co in Pt 3 Co@NCNTs can modulate electronic rearrangement, optimize the d-band center, and accelerate water dissociation and *H desorption, thereby enhancing HER activity.
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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".