Simple and Scalable Synthetic Route for Tunable Compositions of Multimetallic Oxyfluorides as Oxygen Evolution Reaction Catalysts
Bibliographic record
Abstract
This work suggests a simple and scalable synthetic route to prepare multimetallic oxyfluorides, without requiring high temperature, high pressure, and a specific atmosphere (F 2, N 2, Ar, vacuum, etc.). For that, tunable compositions of Ni 2+ –Co 2+ –Fe 3+ -based oxyfluorides Co (1– x )/2 Ni x /2 Fe 0.5 O 0.5 F 1.5 have been prepared by calcination at moderate temperature under ambient air of Co 1– x Ni x FeF 5 (H 2 O) 7 precursors, prepared beforehand through coprecipitation at room temperature, across the whole range of the solid solution (0 ≤ x ≤ 1). Structural and thermal analyses confirmed the successful substitution for both hydrated fluoride precursors and oxyfluorides. Finally, we evaluated the electrocatalytic performance of the different Ni 2+ –Co 2+ –Fe 3+ oxyfluorides for oxygen evolution reaction. Among these, the trimetallic Co 0.25 Ni 0.25 Fe 0.5 O 0.5 F 1.5 exhibits the lowest overpotential (290 and 370 mV respectively at 10 and 100 mA cm –2 ) and the highest specific activity (3.9 A m –2 at 1.53 V vs RHE). These results highlight the need for compositional tunability to maximize performance.
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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 | 0.001 |
| 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".