Synthesis of perovskite-based nanocomposites for deNO<sub><i>x</i></sub> catalytic activity
Bibliographic record
Abstract
Three different types of perovskite-based nanocomposites were synthesized by calcination of the same gel mixtures (molar ratio for La:Sr:Co 0.4:0.6:1.0) under different reaction conditions (unconventional method: calcination at 1000 °C and 800 °C under vacuum; and conventional method: calcination in air at 1000 °C). The obtained products were studied by multianalytic techniques including powder X-ray diffraction (PXRD), high-resolution transmission electron microscopy (HRTEM), energy dispersive X-ray spectroscopy (EDX), and X-ray photoelectron spectroscopy (XPS). NOx reduction using propene (C3H6) as a reductant in the presence of oxygen was studied using temperature-programmed surface reaction (TPSR). The analyzed results showed that multiphase products were found by the unconventional method (in the absence of oxygen), whereas the conventional method (in the presence of oxygen) yielded single-phase perovskites. The multiphase nanocomposite products prepared under vacuum at 1000 °C exhibited higher catalytic activity and higher N2 yield compared with the samples obtained under vacuum at lower temperature (800 °C) and the single-phase perovskites.
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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".