Engineering Relative Spatial Structure of Dual Atomic Sites with Asymmetric Coordination for High‐Performance Hydrogen Evolution Activity
Bibliographic record
Abstract
Abstract Dual‐atom catalysts (DACs), which extend single‐atom catalysts (SACs) with their dual‐site properties, are promising for mediating complex reaction intermediates. However, intricate catalytic behavior of DACs, influenced by their unique interatomic spatial structures, remains elusive and is an ongoing area of inquiry. Herein, for the first time, Pt 1 Fe 1 DACs with a controllable active‐site spatial structure is designed to systematically understand the spatial configurations in regulating the electronic structure and catalytic activity of active sites. Among these, 3D asymmetric coordinated Pt 1 Fe 1 ‐TAC (Pt‐Fe‐N2) dimer catalyst with distinctive interatomic relative spatial structure exhibits superior all‐pH hydrogen evolution reaction (HER) performance due to its strong interatomic interactions and unique electron transfer from Fe to Pt. Operando X‐ray absorption spectroscopy and theoretical calculations reveal that strong inter‐site synergistic interactions enable Pt 1 Fe 1 ‐TAC dimer catalyst with optimized reaction pathway during HER, resulting in high mass activity of 81‐fold increase compared to commercial Pt/C. Besides, an anion exchange membrane water electrolyzer employing Pt 1 Fe 1 ‐TAC dimer catalyst demonstrates 1200 h of stable operation at an industrial‐scale current density of 1000 mA cm −2 with cell voltage of 1.85 V. This research is of great significance for understanding the design of dual atomic sites with controllable spatial positions for efficient hydrogen reactions.
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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".