Extraction and purification of paeonol from <scp>M</scp> outan <scp>C</scp> ortex by a combined method of steam distillation and antisolvent recrystallization to reduce energy consumption and carbon dioxide emissions
Bibliographic record
Abstract
Abstract This study aimed to obtain paeonol with high purity by using the combination of steam distillation and antisolvent recrystallization (ASR) and to reduce the energy consumption and CO 2 emission in the preparation process. First, different experimental parameters were optimized by response surface methodology (RSM). Under the optimal conditions, the purity and yield of the as‐obtained paeonol were about 98% and 56.97%, respectively. The physicochemical properties of purified paeonol were tested, showing consistency with those of standard paeonol. The energy consumption and CO 2 emission of the preparation process of ASR and single‐solvent recrystallization were also investigated. Results showed that the energy consumption and CO 2 emission of ASR were about 4.41 J/mg and 0.006 kg/mg, respectively, which were 6.89 J/mg and 0.0095 kg/mg lower than those of ethanol recrystallization, respectively, and 50.22 J/mg and 0.0144 kg/mg lower than methanol those of recrystallization, respectively. The above results showed that ASR could obtain paeonol with high purity in a high‐efficiency, low‐energy, and environmentally protective manner.
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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".