Modelado y simulación de una columna de destilación por lotes para recuperar epóxido de limoneno
Bibliographic record
Abstract
Aspen Plus and MATLAB software simulation tools were employed for modeling, simulation and optimization of a distillation process to recover limonene epoxide from a liquid mixture containing limonene + acetonitrile + water + limonene epoxide. This mixture is obtained from limonene epoxidation over PW-Amberlite using aqueous hydrogen peroxide as oxidant and acetonitrile as solvent. Analyses of residue curve maps indicate that batch distillation columns of inverse configuration are adequate to separate limonene epoxide. The model parameters, i.e., the number of stages (8) and the reflux ratio (3,1) were determined by steady state simulations with short-cut models and rigorous models from Aspen Plus. Aspen Plus simulation of the batch distillation operation showed that it is possible to recover up to 95 % limonene epoxide with a molar fraction of 0,97 after 7,5 h. For comparison purposes, the batch distillation operation was also simulated with a semi-rigorous MATLAB model and similar results were obtained.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".