Kinetic and mechanistic aspects of furfural degradation in biorefineries
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Furfural is one of the most promising platform chemicals for a future biobased industry and can already be produced from renewable raw materials. However, its production processes suffer from yield loss and fouling problems due to degradation reactions. To increase our understanding of furfural stability, we investigated the kinetics of its degradation (i) without acid catalyst and (ii) in 10 different acids that are frequently used in biomass processing or that are naturally present in biomass hydrolysates. The batch experiments were conducted in a parallel minireactor setup at temperatures ranging from 125 to 200°C. The results showed that acid‐catalyzed furfural degradation reactions depend mainly on acid strength and give rise to a set of common degradation products (formic acid, glycolic acid, pyruvate, etc.). Sulphurous acid and lignosulphonic acid led to greater furfural degradation than expected, which appears to be driven by specific side reactions. Adding formic acid, in contrast, led to a lower degradation rate than expected. In general, we observed two distinct, competing degradation mechanisms. Selectivity for formic acid as a degradation product depends on temperature, furfural concentration, and the presence of an acid catalyst. A more detailed study of the formic acid yielding reaction showed it to be reversible, and we provide the first quantitative description of this reaction for any furan. The proposed kinetic model, together with the results presented, contributes to the development of more efficient furfural production processes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it