Comparing the fragmentation chemistry of gas-phase adducts of poly(dimethylsiloxane) oligomers with metal and organic ions
Bibliographic record
Abstract
Gas-phase ions of poly(dimethylsiloxane) oligomers were formed by electrospray ionization either by protonating them in solution with formic acid or by generating adducts of the oligomers with the metal ions Li + , Na + , K + , and Ag + as well as with the organic cations NH 4 + , CH 3 CH 2 NH 3 + , and protonated glycine, aspartic acid, and 1,2-diphenylethylamine. The collision-induced fragmentation of the oligomeric ions was strongly dependent on the nature of the charging species. Ag + adducts dissociated in a manner previously observed in secondary ion mass spectrometry experiments generating a series of linear and cyclic fragment ions, while Li + adducts fragmented to form two ions: an adduct of the metal ion with the oligomer end-group and one with the remaining oligomer. Na + and K + adducts simply dissociate to form the bare metal ion. The organic species, to varying extents, transfer the proton to the oligomer to form a protonated poly(siloxane) ion. These protonated oligomers then dissociate at very low laboratory-frame collision energy along the siloxane backbone by loss of a silanol. These backbone fragments can then lose a methyl group to form a second series of fragment ions. Suggestions for probable mechanistic pathways for these processes are presented.
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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) | 0.000 | 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) | 0.002 | 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 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".