Construction of Co<sub>2</sub>P‐Ni<sub>3</sub>S<sub>2</sub>/NF Heterogeneous Structural Hollow Nanowires as Bifunctional Electrocatalysts for Efficient Overall Water Splitting
Bibliographic record
Abstract
Abstract Designing efficient and stable transition metal‐based catalysts for electrocatalytic water splitting is vital for the development of hydrogen production. Herein, a facile synthetic strategy is developed to fabricate transition metal‐based heterogeneous structural Co2P‐Ni3S2 hollow nanowires supported on nickel foam (Co2P‐Ni3S2/NF). Owing to the multiple active sites provided by transition metal compounds, large surface area of the unique hollow nanowire morphology, and the synergistic effect of Co2P‐Ni3S2 heterostructure interfaces, Co2P‐Ni3S2/NF requires ultralow overpotentials of 110, 164 mV for HER and 331.7, 358.3 mV for OER at large current densities of 100, 500 mA cm−2 in alkaline medium, respectively. Importantly, the two‐electrode electrolyzer assembled by Co2P‐Ni3S2/NF displays a cell voltage of 1.54 V at 10 mA cm−2 and operates stably over 24 h at 100 mA cm−2, which performs better than reported transition metal‐based bifunctional electrocatalysts. This work presents a successful fabrication of transition metal‐based bifunctional HER/OER electrocatalysts at large‐current density and brings new inspiration for developing applicable energy conversion materials.
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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".