Naphthenic acids quantification in organic solvents using fluorescence spectroscopy
Bibliographic record
Abstract
Quantification of naphthenic acids in water has been traditionally performed after extraction with organic solvents followed by analytic methods that are complex and costly for preliminary research or for continuous monitoring purposes. This study examines the application of fluorescence in organic solvents as an effective alternative, and the role of organic solvents on quantification results. Nine organic solvents were used: three polar protic alcohols (methanol, ethanol, and propanol), three polar aprotic (dichloromethane, acetone, and acetonitrile) and three non-polar (hexane, toluene, and diethyl ether). The calibration curves of the polar protic solvents performed the best; they had lower light scattering and higher method sensitivity than polar aprotic and non-polar. Methanol was selected for further experiments having a strong linearity for concentrations lower than 250 mg/L (R(2) > 0.99), and a low relative standard deviation (< 10%). The method sensitivity was improved by 70% using a methanol-deionized water mixture (50:50) as a solvent. The synchronous fluorescence mode with a reduced offset value of Δλ = 10 nm demonstrated potential for fingerprinting. The fluorescence technique for quantifying total naphthenic acids directly in organic solvents is a cost-effective analytical method compatible with the solid phase extraction of the sample.
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How this classification was reachedexpand
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 | 0.001 | 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 teacher head, 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".