Enantioseparation of 1-substituted 3-arylseleno-2-propanols onPolysaccharide Tris(3,5-dimethylphenylcarbamate)Chiral Stationary Phases
Bibliographic record
Abstract
The enantiomer separation of nine pairs of racemic 1-arylthio-3-arylseleno -2-propanols and 1-alkoxy-3-arylseleno-2-propanols was achieved with high performance liquid chromatography by using cellulose tris(3,5-dimethylphenyl carbamate) (Chiralcel OD-H) and amylose tris(3,5-dimethylphenylcarbamate) (Chiralpak AD-H) as chiral stationary phases and hexane-2-propanol or hexane-ethanol as mobile phases in various percentages.Amylose tris(3,5-dimethylphenylcarbamate) exhibited higher chiral recognition ability compared to cellulose tris(3,5-dimethylphenylcarbamate).The effects of alcohol in the mobile phase and solute structures on the retention and resolution were investigated.On the Chiralcel OD-H column,solutes elute faster with ethanol than with 2-propanol modifier as expected from the higher polarity of ethanol. However,on Chiralpak AD-H column the retention factors of all the enatiomers increase,the enantioseparation factors and resolutions dramatically change on changing 2-propanol to ethanol.The explanation may be that ethanol changes the higher order structure of amylose.The enantioseparation on the Chiralpak AD-H column is much more influenced by the kind of alcohol in the mobile phase than the Chiralcel OD-H.Under optimized conditions,baseline enantioseparation of eight pairs of racemic 1-substituted 3-arylseleno-2-propanols were obtained.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".