Beta‐cyclodextrin covalent organic framework coated silica composite as chiral stationary phase for high‐performance liquid chromatographic separation
Bibliographic record
Abstract
Abstract A beta‐cyclodextrin covalent organic framework coated silica composite, namely beta‐cyclodextrin covalent organic framework@SiO 2 , was prepared by coating the beta‐cyclodextrin covalent organic framework onto a spherical aminized silica matrix and used as the chiral stationary phase for high‐performance liquid chromatography separation in both normal‐ and reversed‐phase modes. The beta‐cyclodextrin covalent organic framework@SiO 2 packed column showed good separation performance towards positional isomers such as nitrotoluene and aminophenol, and benzene homologs in the reversed‐phase high‐performance liquid chromatography mode. While chiral drug molecules including omeprazole and lansoprazole could be also enantioseparated on beta‐cyclodextrin covalent organic framework@SiO 2 packed column in the normal‐phase high‐performance liquid chromatography mode. Besides, the effects of mobile phase composition, column temperature, and other factors of high‐performance liquid chromatography separation on beta‐cyclodextrin covalent organic framework@SiO 2 packed column were studied in detail. Moreover, the stability test of the beta‐cyclodextrin covalent organic framework@SiO 2 packed column was also investigated. The results of continuous injections and monthly detection were basically identical, suggesting the excellent durability of the obtained high‐performance liquid chromatography column. This work indicated that beta‐cyclodextrin covalent organic framework@SiO 2 composite could effectively separate different compounds in high‐performance liquid chromatography normal/reversed‐phase modes, making it a promising chiral stationary phase in the field of high‐performance liquid chromatography separation.
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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) | 0.000 | 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".