Novel CoFe<sub>2</sub>O<sub>4</sub>/CuBi<sub>2</sub>O<sub>4</sub> heterojunction p–n semiconductor as visible‐light‐driven nanophotocatalyst for C (OH)–H bond activation
Bibliographic record
Abstract
Abstract Nanosized CoFe2O4/CuBi2O4 heterostructure was obtained by solvent‐free thermal processing and was characterized using a series of structural, physicochemical, and analytical techniques. The CuBi2O4 and CoFe2O4 nanoparticles demonstrated poor photoactivity due to their fast charge recombination and negligible visible light absorptivity, respectively. In contrast, the prepared heterojunction CoFe2O4/CuBi2O4 nanocomposite consisting of an array of nanocolumns approximately 20 nm in width displayed nearly twofold higher photocatalytic activity than CoFe2O4 or CuBi2O4 nanostructures alone toward the C (OH)–H bond activation. This nanocomposite exhibits photocatalytic efficiency as high as 98% with very high stability. The increased photocatalytic reactivity could be related to the effective Z‐scheme mechanism of photogenerated charge carrier separation between CoFe2O4 and CuBi2O4 in the nanocomposite, which reduces the electron–hole recombination. The results of this work provide a promising approach to the design and preparation of heterostructured photocatalysts for oxidation reactions.
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 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".