Molecular Weight Distributions of Heavy Aromatic Petroleum Fractions by Ag<sup>+</sup> Electrospray Ionization Mass Spectrometry
Bibliographic record
Abstract
The ability of electrospray ionization mass spectrometry (ESI MS) to analyze heavy aromatic petroleum fractions using silver nitrate as a reagent compound to form characteristic adduct ions has been examined. The complexation of aromatic compounds containing long alkyl substituents with the silver ion leads to the formation of abundant adduct ions such as [M + Ag]+ and [2M + Ag]+. The concentration of the [2M + Ag]+ ions can be reduced by increasing the sampling cone voltage. Molecular ions and other adduct ions may also be formed depending on the structure of the aromatic molecule. Results obtained from the analysis of representative heavy petroleum fractions and vacuum residues by the Ag+ ESI MS method and conventional ionization methods were in good agreement. The current method extends the applicability of electrospray ionization to the analysis of neutral hydrocarbons in heavy aromatic petroleum fractions. It is simple and compatible with widely available LC/MS instrumentation. The extreme complexity of the Ag
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
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) | 0.000 | 0.000 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.021 | 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 teacher head, 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".