Influence of chain length and saturation on carboxylic acid pyrolysis mechanisms
Bibliographic record
Abstract
This study investigates radical-driven deoxygenation mechanisms during the non-catalytic pyrolysis of saturated and unsaturated carboxylic acids. Pyrolysis experiments were conducted at 410 °C, between 0.5 and 2 h, using carboxylic acids of varying carbon chain lengths (C6 to C18) and saturation levels, along with ketones. Feedstock conversion and deoxygenation products were quantified using GC–MS/FID for liquids and GC-TCD/FID for gases. Results demonstrated that carboxylic acid chain length significantly influences pyrolysis behavior, with significant differences in deoxygenation pathway linked to acid chain length and saturation level. Decarboxylation was the predominant pathway for short-chain carboxylic acids, whereas long-chain acids showed increased tendency towards decarbonylation. Short-chain saturated carboxylic acids favoured ketonic decarboxylation during the initial stages of pyrolysis, resulting in notable amounts of ketones and carbon dioxide. Subsequent decarbonylation of these ketones contributed to further deoxygenation, generating hydrocarbons and shorter-chain ketones via radical-driven mechanisms. In contrast unsaturated carboxylic acids underwent extensive cracking, which suppressed ketonic decarboxylation and led to reduced overall hydrocarbon yields. Additionally, mixed carboxylic acid feedstocks showed decreased conversion efficiencies, primarily due to limited intermolecular interactions necessary for effective ketonic decarboxylation. This work explores radical-driven, non-catalytic pyrolysis of fatty acids, providing a detailed mechanistic understanding of how chain length and saturation influence reaction pathway. The findings highlight key determinants of product selectivity and deoxygenation efficiency, providing valuable insights for optimizing feedstock compositions in pyrolysis-based sustainable biofuel production.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 | 0.001 |
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".