Micelle Assisted Thin-Film Solid Phase Microextraction: A New Approach for Determination of Quaternary Ammonium Compounds in Environmental Samples
Bibliographic record
Abstract
Determination of quaternary ammonium compounds (QACs) often is considered to be a challenging undertaking owing to secondary interactions of the analytes' permanently charged quaternary ammonium head or hydrophobic tail with the utilized labware. Here, for the first time, a micelle assisted thin-film solid phase microextraction (TF-SPME) using a zwitterionic detergent 3-[(3-cholamidopropyl)dimethylammonio]-1-propanesulfonate (CHAPS) as a matrix modifier is introduced as a novel approach for in-laboratory sample preparation of the challenging compounds. The proposed micelle assisted TF-SPME method offers suppression/enhancement free electrospray ionization of analytes in mass spectrometric detection, minimal interaction of the micelles with the TF-SPME coating, and chromatographic stationary phase and analysis free of secondary interactions. Moreover, it was found that the matrix modifier has multiple functions; when its concentration is found below the critical micelle concentration (CMC), the matrix modifier primarily acts as a surface deactivator; above its CMC, it acts as a stabilizer for QACs. Additionally, shorter equilibrium extraction times in the presence of the modifier demonstrated that micelles also assist in the transfer of analytes from the bulk of the sample to the surface of the coating. The developed micelle assisted TF-SPME protocol using the 96-blade system requires only 30 min of extraction and 15 min of desorption. Together with a conditioning step (15 min), the entire method is 60 min; considering the advantage of using the 96-blade system, if all the blades in the brush are used, the sample preparation time per sample is 0.63 min. Moreover, the recoveries for all analytes with the developed method were found to range within 80.2-97.3%; as such, this method can be considered an open bed solid phase extraction. The proposed method was successfully validated using real samples.
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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 | 0.000 | 0.000 |
| 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 | 0.001 |
| Open science | 0.001 | 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".