Electrospray ionization of alkali and alkaline earth metal species. Electrochemical oxidation and pH effects
Bibliographic record
Abstract
The utility of electrospray ionization mass spectrometry (ESI-MS) for characterizing dissolved metal species has generated considerable interest in the use of this technique for metal speciation. However, the development of accurate speciation methods based on ESI-MS requires a detailed understanding of the mechanisms by which dissolved metal species are ionized during electrospray. We report how the analysis of alkali and alkaline earth metal species provides new information about some of the processes that affect electrospray ion yield. Selected metal ions and organic ligands were combined in 50 : 50 water-acetonitrile buffered with acetic acid or ammonium acetate and analyzed by flow injection ESI-MS using mild electrospray conditions. Species formed by alkali metal ions with thiol and oxygen-donating ligands were detected in acidic and neutral pH solutions. Electrochemical oxidation of N, N-diethyldithiocarbamate and glutathione during electrospray was indicated by detection of the corresponding disulfides as protonated or alkali metal species. The extent of ligand oxidation depended on solution pH and the dissociation constant of the thiol group. Tandem mass spectrometric experiments suggested that radical cations such as [NaL](+.) (where L=N,N-diethyldithiocarbamate) can be generated by in-source fragmentation of disulfide species. Greater complexation of alkali metals at neutral pH was indicated by a corresponding decrease in the relative abundance of the free metal ion. The number of alkali metal ions bound by glutathione and phthalic acid also increased with increasing pH, in accordance with thermodynamic equilibrium theory. Alkaline earth metal species were detected only in acidic solutions, the absence of 8-hydroxyquinoline complexes being attributed to their relative instability and subsequent dissociation during electrospray. Hence, accurate speciation by ESI-MS depends on experimental conditions and the intrinsic properties of each analyte. Copyright 2000 John Wiley & Sons, Ltd.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.005 | 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".