Polymer Inclusion Membranes with Condensed Phase Membrane Introduction Mass Spectrometry (CP-MIMS): Improved Analytical Response Time and Sensitivity
Bibliographic record
Abstract
Condensed phase membrane introduction mass spectrometry (CP-MIMS) is an online, in situ analysis technique for low volatility analytes. Analytes diffuse through a hollow fiber membrane, where they are then dissolved by a liquid (condensed) acceptor phase flowing through the membrane lumen. Permeating analytes are entrained to an atmospheric pressure ionization source for subsequent measurement by a mass spectrometer. Larger analytes, with inherently lower diffusivities, suffer from lengthy response times and lower sensitivity, limiting the use of CP-MIMS for their online, real-time measurement. We present the use of a heptane cosolvent in a methanol acceptor phase in combination with a polydimethylsiloxane (PDMS) membrane. The heptane generates an in situ polymer inclusion membrane (PIM) with the PDMS. We report improved measurement response times and greater sensitivity across a suite of analytes studied (gemfibrozil, nonylphenol, triclosan, 2,4,6-trichlorophenol, and naphthenic acids), with detection limits in the low parts per trillion (ppt) range. These improvements are attributed to increasing analyte diffusivities, as well as increased analyte partitioning across the PIM. Response times are ∼3× faster for the larger analytes studied, and calibration sensitivity is improved by up to ∼3.5× using 0.046 mole fraction heptane in the methanol acceptor. We report the use of short sample exposure times and the use of non-steady-state signals to reduce the analytical duty cycle, and illustrate that the use of a PIM provides a simple and robust variant of CP-MIMS amenable to rapid screening of analytes in complex 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".