Data associated with ‘Molecular Characterization of Strongly and Weakly Interfacially Active Asphaltenes by High-Resolution Mass Spectrometry’
Bibliographic record
Abstract
Asphaltenes are a complex mixture of molecular structures with a variety of functionalities, which in turn impacts their physical properties. Discriminating between asphaltenes that are strongly and weakly interfacially active is providing new direction to mitigate asphaltene-related problems. Whole asphaltenes (WA) were extracted from a South American heavy crude oil, further fractionated into interfacially active asphaltenes (IAA) and remaining asphaltenes (RA), and molecularly characterized by positive-ion (+) atmospheric pressure photoionization (APPI) using a 9.4 tesla Fourier transform ion cyclotron mass spectrometer (FT-ICR MS). The IAA fraction was found to contain a greater abundance of heteroatoms with > 50% of IAA containing two or more heteroatoms as compared to ~30% for RA. The IAA fraction was enriched in oxygen containing species, more specifically higher-order Ox and OxSy groups that were predominantly of low DBE. Gas-phase fragmentation of RA and IAA precursor ions (m/z 650) by infrared multiphoton dissociation (IRMPD) revealed an abundance of multi-core motifs in IAA, while RA was found to be a mixture of single-core and multi-core structures. Analysis of the fragmented ions showed a prevalence of nitrogen-containing species of high DBE (aromatic molecular structures), while oxygen-containing species were most likely associated with aliphatic side chains. Extrography fractionation of RA and IAA verified the abundance of multi-core motifs in IAA which were highly-polar and of low DBE and carbon number. These ‘atypical’ structures of IAA are classified as asphaltenes as a result of their functionality and polarity rather than high aromaticity.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".