Derivatization of fatty alcohol ethoxylate non‐ionic surfactants using 2‐sulfobenzoic anhydride for characterization by liquid chromatography/mass spectrometry
Bibliographic record
Abstract
A derivatization procedure has been developed for the improved characterization of fatty alcohol ethoxylate non-ionic surfactants by liquid chromatography/mass spectrometry. The end hydroxyl group of each surfactant species was converted into an oxycarbonylbenzene-2-sulfonic acid group with 2-sulfobenzoic anhydride under mild conditions. The produced sulfonic acid group allows all species, including fatty alcohols and those with less than three ethoxylates, to be uniformly ionized by electrospray ionization (ESI) mass spectrometry. Both acid and base can be used as a mobile phase additive for liquid chromatography without affecting M(n) and average ethoxylate values, although ion intensities are suppressed during the ESI process. The method was used to analyze seven commercial fatty alcohol ethoxylate non-ionic surfactants, and the determined M(n) and EO values were comparable with the results obtained by NMR. The relative ratio of different fatty alcohol based ethoxylates in a sample can also be determined using the summed mass spectral data.
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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 | 0.001 | 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) | 0.001 | 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".