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 Co 3 O 4 in hydrogen and oxygen evolution reactions have been significantly enhanced by coating a shell layer of a copper‐based metal–organic framework on Co 3 O 4 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 Co 3 O 4 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 Co 3 O 4 . 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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 0.003 |
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 teacher head, 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".