Synthesis of ZSM‐5 by hydrothermal method with pre‐mixing in a stirred‐tank reactor
Bibliographic record
Abstract
This work proposed a synthesis route of ZSM‐5 via the hydrothermal method with premixing in a stirred tank reactor (STR). Effects of various operating conditions, including pre‐mixing time, molar ratio of SiO2/Al2O3, TPAOH (organic template agents) concentration, NaCl (alkali metal cations) concentration, crystallization temperature, and crystallization reaction time, on the average particle size (PS) and particle size distribution (PSD) were investigated. It was found that the pre‐mixing time in the STR significantly affect the formation of proto‐nuclei in premixing process and crystal growth in hydrothermal reaction process, and consequently influence the PS and PSD of the prepared ZSM‐5. ZSM‐5 with good thermal stability, a PS of 380 nm, PSD of 0.17–0.9 µm, pore diameter of 2.31 nm, pore volume of 0.19 cm3 · g−1 and specific surface area of 337.25 m2 · g−1 were obtained under the optimal conditions of a crystallization reaction time of 24 h, a crystallization temperature of 130 °C, a molar ratio of SiO2/Al2O3 of 200, a TPAOH concentration of 3.5 mol · L−1, NaCl concentration of 0.3 mol · L−1, and a pre‐mixing time of 5 h. This work indicated that the operating conditions including premixing time have a significant effect on its PS and PSD.
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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".