Quantification of four classes of amphiphilic surfactants by solid phase extraction and spectrophotometric detection at nanomolar levels: environmental applications
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Bibliographic record
Abstract
Surfactants are natural and anthropogenic compounds commonly found in all environmental compartments and can influence cloud formation due to their surface-active properties. In this work, a new method for the sensitive and selective quantification of 4 different classes of amphiphilic surfactants was developed, based on a new solid-phase extraction (SPE) procedure with a graphitized carbon black sorbent and optimized spectrophotometric methods using commercial ion-pair reagents and liquid-liquid extraction. The sequential elution used in the SPE step enabled separate quantification of cationic, non-ionic, weak anionic and strong anionic surfactants. The spectrophotometric methods of detection of all classes of surfactants were optimized. A new method was developed for strong anionic surfactants using Toluidine blue O. Significant improvements were also made to existing methods for weak anionic and non-ionic surfactants using methylene blue and iron thiocyanate, respectively. Limits of detection of 0.08, 0.076, 0.91 and 0.20 nmol were achieved for cationic, non-ionic, weak anionic and strong anionic surfactants, respectively. A classification according to the acidity of the anionic group was proposed to distinguish synthetic surfactants (strong acids) from biosurfactants (weak acids). Issues related to interfering species, losses during filtration steps were also addressed, and a new filtration method with polyethylene frits was demonstrated to improve surfactants recoveries for aerosol analysis, with recoveries above 80 % for all types of surfactants. The procedure was applied to real environmental samples, including seawater and freshwater samples, aerosols extracts, and cloud water. Surfactants were successfully detected in all samples, with total concentrations between 12.1 nM and 495 nM for aqueous samples and between 48.4 pmol m −3 and 443 pmol m −3 for aerosol samples. Anionic surfactants were found to be the major constituents in all environmental matrices, but low concentrations of cationic and non-ionic surfactants were also detected in several samples.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.001 | 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 it