Effects of solvent flow, dopant flow, and lamp current on dopant-assisted atmospheric pressure photoionization (DA-APPI) for LC-MS. Ionizationvia proton transfer
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Bibliographic record
Abstract
In this paper, the effects of solvent flow, dopant flow, and lamp power on proton transfer ionization in dopant-assisted (DA) atmospheric pressure photoionization (APPI) are investigated. A broad theoretical framework is presented, describing the primary photoionization process, the formation of protonated-solvent cluster ions, and the balance between analyte ion creation via proton transfer and loss via recombination. The principal experimental test system utilized methanol as the solvent, toluene as the dopant, and acridine as the analyte. Comparisons are made between acridine and a less basic compound, 9-methylanthracene (9-MA). Experimental determinations of the trends in the analyte MH + signal and the total ion current (TIC) with variations in the subject parameters are provided. Experimental results and theory demonstrate that both the analyte signal and the TIC approach asymptotic limits with increases in dopant flow and/or lamp current (two factors which dictate the rate of photoion generation). The data show that these limits are lowered at higher solvent flow rates. These results are attributed to the recombination loss process, the rate of which increases with the second power of ion concentration. We deduce that the recombination rate constant increases with solvent flow rate, a consequence of the growth of ion-solvent clusters. Cluster growth is also believed to be a factor in the dramatic loss of sensitivity for 9-MA that occurs as the solvent flow is raised, because larger protonated-solvent cluster ions have greater solvation energies and may be unreactive with compounds having low gas-phase basicity and/or low solvation energy.
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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) | 0.001 | 0.001 |
| 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 | 0.000 |
| 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 it