Piston-cylinder based micro liquid–liquid extraction with GC–qMS for trace analysis of targeted chlorinated organic compounds in water
Bibliographic record
Abstract
A fast and reliable approach for the measurement of sub parts-per-billion levels of targeted chlorinated compounds like tetrachloroethane, hexachloroethane, hexachlorobutadiene, pentachlorobenzene, and hexachlorobenzene in various water matrices such as waste water is described. The method employed a novel piston-cylinder-based micro liquid–liquid extraction technique using hexane as an extraction solvent. The device, known commercially as the MIXXOR, substantially accelerates extraction time by a factor of more than 100 times and reduces solvent consumption by a factor of 25 times when compared with the solvent extraction technique using wrist-action mechanical agitation. A recently introduced 6% cyanopropylphenyl –94% dimethylpolysiloxane capillary column offering a high degree of inertness was used for the separation of the analytes. A quadrupole mass spectrometer equipped with a triple-axis detector was also employed to enhance the instrument detection limit. With this technique, a complete separation for the analytes in water can be conducted in less than 10 min using a three-port SilFlow planar microfluidic device for back-flushing. Repeatability of retention times for all compounds were found to be less than 0.04% (n = 10). The compounds cited can be analyzed from 1 ng/mL to 10 μg/mL, with a detection limit and correlation coefficient of at least 0.5 ng/mL and 0.999, respectively. A relative precision of less than 1.2% relative standard deviation (RSD) (n = 20) at the 50 ng/mL level, with analyte recovery of greater than 99% (n = 3) from 10 ng/mL to 10 μg/mL, was obtained.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".