Comparing Laser Desorption/Laser Ionization Mass Spectra of Asphaltenes and Model Compounds
Bibliographic record
Abstract
The molecular-mass distribution of the asphaltene fraction of petroleum is rapidly becoming more constrained, but the molecular architecture remains poorly understood. Two types of molecular structures have been proposed to be representative of asphaltenes: the “island” model and the “archipelago” model. Here, nine compounds were synthesized on the basis of pyrene, representing both types of models. These compounds were analyzed using two-step laser desorption/laser ionization mass spectrometry (L 2 MS), and the compounds were classified into three groups based on their fragmentation behavior in this typically soft ionization technique. The first two groups, denoted “highly fragmented” and “variably fragmented”, include eight of the nine studied compounds. The masses of fragment ions from the “highly fragmented” group were too small for these specific compounds to dominate the asphaltenes. The fragmentation behavior of the variably fragmented group was inconsistent with L 2 MS spectra of asphaltene samples; thus, these specific compounds can be excluded from being dominant in asphaltenes. The third group, “highly stable”, contains a single model compound with properties in the aromatics class fraction and exhibits a behavior consistent with previously observed asphaltene samples, namely, inappreciable fragmentation as a function of laser pulse energy used. Although suggestive, no definitive conclusion can be reached as to the dominant molecular architecture of asphaltenes without the study of how more model compounds behave under L 2 MS.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".