Preparation of nano‐ZIF‐8 in methanol with high yield
Bibliographic record
Abstract
Abstract This article systematically presented analysis results of factors affecting the preparation of nano‐ZIF‐8 in methanol for high yield. Samples were characterized by X‐ray diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM), Fourier transform infrared spectroscopy (FTIR), Brunauer‐Emmett‐Teller (BET) adsorption, and thermogravimetry‐differential thermal analysis (TG/DTA). Synthesized nano‐ZIF‐8 had advantages over commercial ZIF‐8 (Basolite ® Z1200 from Sigma‐Aldrich) such as a higher surface area, consisting of not only micropores like Basolite ® Z1200 but also subordinate mesopores, formed by an assembly of nano‐ZIF‐8 crystals, which was 30 nm. Specifically, for the first time, nano‐ZIF‐8 was prepared in methanol with the yield of 61.2 %.
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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) | 0.001 | 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 | 0.001 |
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".