Co‐doped ZnO thin films grown by pulsed electron beam ablation as model nano‐catalysts in fischer‐tropsch synthesis
Bibliographic record
Abstract
A single‐step deposition of cobalt‐doped zinc oxide (Co‐ZnO) thin film nano‐composites on three different crystalline substrates, viz., Al2O3 (c‐sapphire), silicon (100) (Si), and SiO2 (quartz) is reported, using pulsed electron beam ablation (PEBA). The results indicate that the type of substrate has no effect on Co‐ZnO films stoichiometry, morphology, microstructure, and film thickness. The findings show the presence of hexagonal close‐packed metallic Co whose content increases in the films deposited on Al2O3 and Si substrates relatively to SiO2 substrate. The potential of the films as model nano‐catalysts has been evaluated in the context of the Fischer‐Tropsch (FT) process. Fuel fractions, which have been observed in FT liquid products, are rich in diesel and waxes. Specifically, Co‐ZnO/Al2O3 nano‐catalyst shows a selectivity of ∼4%, 31%, and 65% towards gasoline, diesel, and waxes, respectively, while Co‐ZnO/SiO2 nano‐catalyst shows a selectivity of ∼12%, 51%, and 37%, for gasoline, diesel, and waxes, respectively. © 2018 American Institute of Chemical Engineers AIChE J, 64: 3332–3340, 2018
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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".