Unveiling the Power of Negative Ion Mode ESI-MS: Identify-ing Species with Remarkable Signal Intensity and Collisional Stability
Bibliographic record
Abstract
Electrospray ionization mass spectrometry has long been the standard and most prevalent ionization method in mass spectrometry to detect and analyze molecules of low volatility that are relevant biologically, environmentally, and industrially. However, only a small number of analyses are conducted in negative ion mode, which has led to a dog-matic bias toward positive ion mode despite advantageous properties of the negative polarity, including lower back-ground noise and divergent tandem mass spectrometry behavior. We hypothesized that this bias was rooted in the relatively poor ionization efficiency of anionic functional groups seen in biochemistry; to explore this notion herein we evaluated 25 ions based on three criteria: (1) signal intensity relative to a sodium dodecylsulfate internal stand-ard; (2) resistance to collision induced dissociation based on survival of the precursor ion; and (3) diagnostic tandem mass spectrometry behavior. Among these species, highly fluorous ions exhibiting weakly coordinating and hydro-phobic properties contributed to enhanced signal intensities. Trifluoromethanesulfonyl-containing ions proved to be unexpectedly labile, while tetrakis[3,5-bis(trifluoromethyl)phenyl]borate anion (23) and bis(nonafluoro-1-butane)sulfonimidate (25) were determined to be of optimal signal intensity with signal intensity ratios relative to sodium dodecylsulfate (12 + Na+) of 332.0% ± 25.0% and 939.0% ± 92.0%, respectively, as well as survival yields of 100.0% ± 0.0% and 72.6% ± 0.8% at –50 eV. To further emphasize their optimal signal intensity, ions tetrakis[3,5-bis(trifluoromethyl)phenyl]borate anion (23) and bis(nonafluoro-1-butane)sulfonimidate (25) were comparable in signal intensity across solvents of acetonitrile, methanol, isopropanol, water, and their respective 1:1 mixtures. Facile preparation of various salts of bis(nonafluoro-1-butane)sulfonimidate led to additional evaluation of cation effects where the signal intensity ratio ranged from 939.0% ± 92.0% to 3195.0% ± 145.0% across K+, NH4+, Na+, and H+ counter cations. The dogma of negative ion mode being less sensitive was then challenged by the analysis of the sig-nal intensity of ion 25 to tetra-n-butylammonium, tetra-n-butylphosphonium, and (4-methylphenyl)diphenylsulfonium cations. These experiments showed that 25 was more sensitive by between 136.2% ± 5.5% and 180.7% ± 13.8%, thereby successfully challenging the positive polarity bias.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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 | 0.000 |
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".