A multiple-assembly/one-pot-crystallization strategy for a relatively more eco-friendly synthesis of hydrothermally stable mesoporous aluminosilicates
Bibliographic record
Abstract
Mesoporous aluminosilicates (MA) with high hydrothermal stability obtained by assembly of zeolite Y precursors are attractive for the potential application in heavy oil catalytic cracking. A relatively more eco-friendly synthesis of MA with low synthesis cost and waste water discharge is particularly appealing. We report on the green synthesis of MA via a multiple-assembly/one-pot-crystallization (MA/OC) process by recycling the non-reacted reagents in the assembly mother liquor after separating the assembly solid product. This approach was achieved by exact supplementary compensation of the consumed raw materials and correct pH adjustment for the assembly liquor after each cycle of assembly. The assembly solid products in 5 cycles were collected and crystallized in one-pot in the mother liquor. Characterization results indicated that consumption of P123 and water discharge of MAOC-5 could be reduced to 51.5% and 27.3% of those of conventional MA-1. Meanwhile, the product yield of MAOC-5 is 102.66 g L−1, 4.8 times that of MA-1. This strategy suggests a relatively more eco-friendly and low cost route for the synthesis of hydrothermally stable MA.
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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 | 0.001 |
| 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".