An improved method for the analysis of the reaction products of the partial isobutane oxidation by gas chromatography using a green solvent
Bibliographic record
Abstract
In the present work, an improved GC/MS method for the analysis of the reaction products of the non-catalytic partial oxidation of isobutane at a starting temperature of 25°C has been developed and compared to a previously published method [1]. Two green GC-solvents (dimethyl carbonate (DMC), diethyl carbonate (DEC)) and several internal standards (hexane, benzene, toluene, DEC) have been tested. The separation of the products at low retention times (methanol, isobutane, isobutene) could be significantly improved. For the liquid main products t-butyl hydroperoxide (TBHP), di-t-butyl peroxide (DTBP), t-butanol (TBA), propanone and most trace products (isopropanol, isobutanal, methyl formate, isopropyl formate, t-butyl formate and some acetates - 24 compounds in total), a coefficient of determination CoD > 0.999 has been achieved. For all weighing and GC/MS measurements uncertainties have been calculated. The peaks of the peak pair t-butyl formate (CoD >0.999) and isobutanol (CoD >0.99), have been simulated and used for calibrations. DEC gave a decomposition of TBHP on the column. With DMC, a problem of peak purity of TBHP appeared but could be resolved. The use of the green solvent DMC, compared to also studied traditional solvents like heptane and toluene, proved to be very beneficial, since it also permitted to determine polar compounds, e. g. carbon dioxide and formic acid.
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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) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".