Retention behavior of <i>o</i>‐phthalic, 3‐nitrophthalic, and 4‐nitrophthalic acids in ion‐suppression reversed‐phase high performance liquid chromatography using acids instead of buffers as ion‐suppressors
Bibliographic record
Abstract
In reversed-phase high performance liquid chromatography, the logarithm of the retention factor, log k, is usually correlated with the logarithm of the octanol-water partition coefficient, log Kow. The k and Kow of an ionizable analyte are greatly influenced by the mobile phase pH. In this paper, log kw of diprotic o-phthalic, 3-nitrophthalic, and 4-nitrophthalic acids, are obtained by extrapolation to pure aqueous fraction of mobile phase in ion-suppression reversed-phase high performance liquid chromatography with acetic acid and perchloric acid as the ion-suppressors. The Kow values of the three analytes are calibrated according to the apparent octanol-water partition coefficient, Kow, under different pH conditions, and the log K"ow values show a much better correlation with log kw than do log Kow. The influences of two ion-suppressors, acetic and perchloric acids, on the retention behavior of these diprotic acids at different pH are contrasted. An abnormal trend is found in the k vs. pHw plot of the acetic acid system when the methanol content is low. A possible reason is that acetic acid is an even stronger organic modifier than methanol, besides being an ion-suppressor. The results make the selection of mobile phase for the separation of acidic compounds by ion-suppression reversed-phase high performance liquid chromatography direct, accurate, and practical.
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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 | 0.001 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".