Thermal Decomposition of 5-(Hydroxymethyl)-2-furaldehyde (HMF) and Its Further Transformations in the Presence of Glycine
Bibliographic record
Abstract
Thermal decomposition of HMF has been so far studied indirectly through carbohydrate degradation reactions assuming HMF as the main product. Such studies, however, do not necessarily generate relevant information on HMF decomposition because many other products are generated simultaneously. Direct thermal decomposition using different concentrations of HMF in silica gel was studied using pyrolysis-GC-MS. Undiluted HMF generated four peaks corresponding to 5-methylfurfural, 2,5-furandicarboxaldehdye, HMF, and a major unknown peak at retention time of 20.73 min. The diluted HMF in silica gel (15-fold) generated only the first three peaks. The generation of the unknown peak was dependent on the concentration of HMF, indicating the possibility of a dimeric structure; furthermore, when HMF was generated from [U-13C6]glucose in the reaction mixture, the highest mass in the spectrum of the unknown peak showed the incorporation of 11 carbon atoms from the glucose. Thermal decomposition studies of HMF have also indicated that in the absence of amino acids it can mainly dimerize and the initially formed dimer can degrade to generate 5-methylfurfural and 2,5-furandicarboxaldehyde. On the other hand, thermal degradation of HMF in the presence of glycine generated Schiff base adducts of HMF, 5-methylfurfural, and 2,5-furandicarboxaldehdye in addition to 2-acetyl-5-methylfuran and a newly discovered adduct, 5-[(dimethylamino)methyl]-2-furanmethanol.
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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) | 0.000 | 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 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".