Preparation and characterization of nano- and non-nanoscale Co<sub>3</sub>O<sub>4</sub>spinels obtained from different methods and study of their performance in combustion of aromatics from polluted air-A comparison with Pt/γ-Al<sub>2</sub>O<sub>3</sub>performance
Bibliographic record
Abstract
This article reports the development of oxidative precipitation (OP) method for synthesis of Co(3)O(4) as an environmental catalyst and comparison of its performance with that of obtained from conventional sol gel combustion (SG) method and industrial Pt/γ-Al(2)O(3) in remediation of toluene from air. Catalytic studies were carried out in a fixed bed reactor at 100-350°C under atmospheric pressure. Co(3)O(4) (OP) showed the highest activity in combustion of toluene. The half conversion temperature of toluene (T(50%)) was 160, 258, and 229°C on Co(3)O(4) (OP), Co(3)O(4) (SG) and Pt/γ-Al(2)O(3), respectively. The higher activity of Co(3)O(4) (OP) was ascribed to nanostructure and reducibility of catalytic sites at lower temperatures, approved by TPR results. The study confirmed that preparation method has a large influence on the chemical-physical properties and activity of the catalyst. The study indicated that oxidative precipitation method could be a promising method to synthesize environmental catalysts considering the simplicity and needless to calcine catalyst at higher temperatures.
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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".