Microreactor technology for synthesis of ethyl methyl oxalate from diethyl oxalate with methanol and its kinectics
Bibliographic record
Abstract
Abstract This study focused on the performances and kinetics of the transesterification reaction of diethyl oxalate with methanol to prepare ethyl methyl oxalate via microreactor technology. The conversion of 79.8% of diethyl oxalate (DEO) and the selectivity of 65.9% of ethyl methyl oxalate (EMO) was obtained under the following optimized conditions: the mole ratio of methanol to diethyl oxalate was 3.3:1, the temperature was 35°C, the K2CO3 catalyst concentration was 15 mg/mL, and the residence time was 2.30 minutes. In the temperature range of 25°C to 38°C, the simplified dynamic model was found to obtain the reaction order (α = 2.30), frequency factor (k0 = 2.377 × 105), and apparent activation energy (E = 31.86 kJ/mol). The macroscopic dynamic equation was derived from the experimental result of the transesterification reaction of two feedstocks, which can be obtained through a series of calculations.
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.
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 | 0.000 |
| 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) | 0.001 | 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 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".