Bibliographic record
Abstract
Understanding metal ion interactions with long-chain alkanes not only is of fundamental importance in the areas of organometallic chemistry, surface chemistry, and catalysis, but also has significant implication in mass spectrometry method development for the analysis of polyethylene. Polyethylene represents one of the most challenging classes of polymers to be analyzed by mass spectrometry. In this work, reactions of several transition-metal ions including Cr+, Mn+, Fe+, Co+, Ni+, Cu+, and Ag+ with long-chain alkanes, C28H58 and C36H74, are reported. A metal powder and the nonvolatile alkane are co-deposited onto a sample target of a laser desorption/ionization (LDI) time-of-flight mass spectrometer. The metal ions generated by LDI react with the vaporized alkane during desorption. It is found that all these metal ions can form adduct ions with the long-chain alkanes. Fe+, Co+, and Ni+ produce in-source fragment ions resulting from dehydrogenation and dealkylation of the adduct ions. The post-source decay (PSD) spectra of the metal-alkane adduct ions are recorded. It is shown that PSD of Ag+ alkane adduct ions produces bare metal ions only, suggesting weak binding between this metal ion and alkane. The PSD spectra of the Fe+, Co+, and Ni+ alkane adduct ions display extensive fragmentation. Fragment ions are also observed in the PSD spectra of Cr+, Mn+, and Cu+ alkane adduct ions. The high reactivity of Fe+, Co+, and Ni+ is consistent with that observed in small alkane systems. The unusually high reactivity of Cr+, Mn+, and Cu+ is rationalized by a reaction scheme where a long-chain alkane first forms a complex with a metal ion via ion/induced dipole interactions. If sufficient internal energy is gained during the complex formation, metal ions can be inserted into C-H and C-C bonds of the alkane, followed by fragmentation. The thermal energy of the neutral alkane is believed to be the main source of the internal energy acquired in the complex. Finally, the implication of this work on mass spectrometry method development for polyethylene analysis is discussed.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".