An Intensified Green Process for the Coproduction of DMC and DMO by the Oxidative Carbonylation of Methanol
Bibliographic record
Abstract
Dimethyl carbonate (DMC) is an eco-friendly and sustainable compound with widespread industrial applications. Various extensive routes have been exploited in the chemical industry to produce DMC. However, these routes have several environmental and energy drawbacks. In this study, a promising novel industrial scheme for the synthesis of DMC via the oxidative carbonylation of vaporized methanol with dimethyl oxalate (DMO) as a byproduct is investigated. A methanol conversion of 81.86% and a DMC selectivity of 83.47% were achieved using an isothermal fixed-bed reactor at 130 °C. The DMC is withdrawn at a purity of >99 mol% via pressure-swing azeotropic distillations. Heat integration was performed to optimize energy consumption, reducing the energy requirements by 28%. An economic evaluation was performed for estimating the profitability via cash-flow diagrams, predicting a payback period of 3.7 years. The proposed green process exhibits several benefits, including high profitability and being environmentally friendly. It also eliminates the use or production of hazardous materials, and it enhances safety characteristics.
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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".