Bibliographic record
Abstract
The search for new zeolites is of continuous interest in the field of zeolite science because of their widespread application in catalysis and adsorption-separation. To this end, considerable efforts have been devoted to the preparation of new zeolites with novel porous architectures and compositions. Taking account of the key factors governing the formation of zeolites (e.g., guest species, framework elements, construction processes, etc.), several synthetic strategies have been developed recently. These allow the discovery of many new zeolites with unprecedented structural features, such as hierarchical pores, odd-ring numbers (11-, 15-rings), extra-large pores (16-, 18-, 20-, 28-, and 30-rings), chiral pores, and extremely complex framework topologies, etc. In this review, we will present the advances in the synthesis of new zeolite structures in the last decade, which are achieved by utilization of the synthetic strategies based on pre-designed structure-directing agents, heteroatom substitution, and topotactic transformations.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".