Production of gasohol by azeotropic distillation
Bibliographic record
Abstract
Abstract A new azeotropic distillation process is presented to produce gasohol in an adequate concentration of bioethanol and isooctane, which emulates the properties of gasoline ready to use in conventional combustion engines. Since the mixing step is eliminated, there are significant economic savings which imply a competitive price of bioethanol. A comparison is provided with the traditional bioethanol dehydration process, extractive distillation. Both processes were simultaneously designed and optimized with differential evolution with a Tabu list algorithm (DETL) in order to reduce the total annual cost (TAC). Results showed that when obtaining E10 biofuel, a blend of up to 10% ethanol and 90% unleaded isooctane, via azeotropic distillation, over 40% of the TAC is saved compared to obtaining pure alcohol dehydrating through extractive distillation. Moreover, the reduction in carbon dioxide emissions results in an average of 27%.
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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".