Surface-Bound Formate Oxyanions Destabilize Hydration Layers to Pave OH<sup>–</sup> Transport Pathways for Oxygen Evolution
Bibliographic record
Abstract
Sluggish mass transfer of OH – in alkaline oxygen evolution reaction (OER), resulting from densely packed hydrated layers at the outer Helmholtz plane (OHP), becomes one of the main bottlenecks to improve overall efficiency of electrochemical devices. Herein, we report a hydration-layer-destabilizing route by binding formate oxyanions onto the catalyst surface to form OH – transport pathways, favorable for fast OH – transport and significantly improving OER activity. The electrochemical experiments indicate that surface formate-modified NiCo hydroxide (NiCo–HCOO – ) shows increased OH – transfer kinetics, smaller overpotential, and higher turnover frequency (TOF) than that without surface formate modification. The theoretical calculations reveal that surface formate-induced hydrogen-bonding interaction with water molecules could destabilize densely packed hydrated potassium ion layers at the OHP, lowering OH – transport resistance and paving a pathway for OH – transfer. The assembled flow electrolyzer with the NiCo–HCOO – anode could operate at 400 mA cm –2 with only 2.1 V for over 300 h. This study provides an efficient strategy for designing high-activity OER electrocatalysts toward advanced energy conversion devices.
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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".