Co<sub>3</sub>O<sub>4</sub>@Cu‐Based Conductive Metal–Organic Framework Core–Shell Nanowire Electrocatalysts Enable Efficient Low‐Overall‐Potential Water Splitting
Bibliographic record
Abstract
Abstract In the work reported herein, the electrocatalytic properties of Co3O4 in hydrogen and oxygen evolution reactions have been significantly enhanced by coating a shell layer of a copper‐based metal–organic framework on Co3O4 porous nanowire arrays and using the products as high‐performance bifunctional electrocatalysts for overall water splitting. The coating of the copper‐based metal–organic framework resulted in the hybridization of the copper‐embedded protective carbon shell layer with Co3O4 to create a strong Cu−O−Co bonding interaction for efficient hydrogen adsorption. The hybridization also led to electronically induced oxygen defects and nitrogen doping to effectively enhance the electrical conductivity of Co3O4. The optimal as‐prepared core–shell hybrid material displayed excellent overall‐water‐splitting catalytic activity that required overall voltages of 1.45 and 1.57 V to reach onset and a current density of 10 mA cm−2, respectively. This is the first report to highlight the relevance of hybridizing MOF‐based co‐catalysts to boost the electrocatalytic performance of nonprecious transition‐metal oxides.
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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".