HIGHLY CATALYTIC<font>Ag</font>/<font>Co</font><sub>3</sub><font>O</font><sub>4</sub>NANOCATALYSTS FABRICATED FOR<font>RhB</font>DYE DEGRADATION THROUGH A SIMPLE SILVER-MIRROR REACTION UNDER VISIBLE LIGHT
Bibliographic record
Abstract
In this paper, a highly catalytic and nanosized Ag / Co3O4composite for rhodamine B ( RhB ) degradation was fabricated by using the co-precipitation method at room temperature. The Ag / Co3O4structure and catalytic properties were characterized through scanning electron microscopy (SEM), transmission electron microscopy (TEM), Brunauer–Emmett–Teller (BET) gas-sorption measurements, X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS) and UV-Vis spectroscopy. The results showed that the Co3O4nanosheets prepared by hydrothermal synthesis mainly exposed (2 2 0) and (1 1 1) facets, which played an important role in determining its catalytic oxidation performance. The Co3O4nanosheets doped with Ag nanoparticles by a simple silver-mirror reaction exhibited a stable and well-dispersed property in dye solution. Compared to the Ag and Co3O4nanostructure, the Ag nanoparticles with bigger diameter (10 nm) on Co3O4surface also readily produced surface-active oxygen species and exhibited a higher catalytic activity for the degradation of RhB solution (5 mg ⋅ L-1) under the visible light. The kinetic constant K of Ag / Co3O4catalyst for RhB degradation reaction was evaluated to 0.02724 min-1, which is relatively higher than those reported in the literatures.
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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".