Systematic Investigation of the Role of Molybdenum and Boron in NiCo-Based Alloys for the Oxygen Evolution Reaction
Bibliographic record
Abstract
Quaternary NiCoMoB electrocatalysts exhibited significantly enhanced OER performance compared to their ternary NiCoMo and NiCoB counterparts. An optimal Mo/B ratio of 1 (NiCoMoyBy) demonstrated a superior OER activity, attributed to a balance between the electronic and structural contributions from Mo and B, maximizing the electrocatalytic site density and activity. NiCoMoyBy-SA, a nanoparticle version synthesized via a surfactant-assisted method, showed further improved performance. The OER activity was evaluated by comparing overpotentials at 10 mA/cm2, with NiCoMoxB1−x, NiCoMoyBy, and NiCoMoyBy-SA exhibiting 293, 284, and 270 mV, respectively. NiCoMoyBy-SA also demonstrated the lowest onset potential (1.45 V), reflecting a superior efficiency. Chronoamperometry in 1 M pre-electrolyzed KOH at 30 °C highlighted NiCoMoyBy-SA’s stability, activating within hours at 10 mA/cm2 and stabilizing over 7 days. At 50 mA/cm2, the overpotential increased minimally (0.02 mV/h over 2 days), and even at 100 mA/cm2 for 10 days, the activity declined only slightly, affirming a high stability. These findings demonstrate NiCoMoB electrocatalysts as cost-effective, efficient OER electrocatalysts, advancing sustainable energy technologies.
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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) | 0.000 | 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".