Intensification of fructose dehydration into 5‐ <scp>HMF</scp> and subsequent oxidation to 2,5‐ <scp>FDCA</scp> using ultrasound
Bibliographic record
Abstract
Abstract Ultrasound‐assisted dehydration of fructose into 5‐hydroxymethylfurfural (5‐HMF) and subsequent oxidation to furandicarboxylic acid (2, 5‐FDCA) is studied in the current work with the main objective being to elucidate the effectiveness of ultrasound for intensified synthesis. The effect of reaction parameters like ultrasound power, duty cycle, reaction time, reaction temperature, solid to solvent ratio, and fructose concentration on the dehydration of fructose into 5‐HMF has been studied. Optimized conditions established were ultrasonic power of 140 W, duty cycle of 60%, reaction time of 60 min, temperature of 100°C, and fructose:dimethylsulfoxide (DMSO) ratio of 3:100 (g/mL), which resulted in the highest 5‐HMF yield of 96% and fructose conversion of 100%. The conventional method carried out at optimized conditions resulted in only 13.5% as 5‐HMF yield. The obtained 5‐HMF was further oxidized to FDCA using Pd/C as the catalyst, H 2 O/DMSO as solvent, and K 2 CO 3 as a base also using ultrasonic irradiation at 140 W power and 22 kHz frequency in the presence and absence of O 2 as oxidant. 100% conversion of 5‐ HMF was obtained in 30 min and 4 h using ultrasound in the presence of O 2 and in absence of O 2 , respectively. 75% conversion of 5‐HMF was observed using the conventional method in 5 h in the presence of O 2 . Overall, the intensification benefits of using ultrasound at both steps of synthesis has been successfully elucidated.
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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 | 0.001 |
| 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 | 0.000 |
| 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".