Modified and systematic synthesis of zinc oxide‐silica composite nanoparticles with optimum surface area as a proper H<sub>2</sub>S sorbent
Bibliographic record
Abstract
The main objective of this work is to synthesize high surface area zinc oxide/silica composite nanoparticles via a facile and systematic process. Regarding the importance of surface area in application of such nanoparticles, variation of this factor was studied by change of reaction parameters including concentration of zinc acetate solution, pH, and calcination temperature via Response Surface Method combined with Central Composite Design (RSM‐CCD). Optimum conditions were obtained as a concentration of 0.013 mol · L −1 , pH of ∼8.97, and calcination temperature of 541.6 °C. Optimum nanoparticles were characterized by various analyzes such as XRD, BET, AAS, FTIR, TGA/DTA, FESEM, EDS, and TEM. Comparison of two 0.1 g/g (10 wt %) ZnO/Silica samples with the optimum (337 m 2 · g −1 ) and non‐optimum (95 m 2 · g −1 ) surface areas indicated that nanoparticles prepared at the optimum conditions with average diameter of about 18 nm showed a H 2 S adsorption capacity of about 13 mg per gram of sorbent. This value was higher than that of the non‐optimized sample (6 mg per each gram of sorbent).
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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 | 0.000 | 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 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".