Water Removal from Ethanol Vapor by Adsorption on Canola Meal after Protein Extraction
Bibliographic record
Abstract
In this paper, biosorbents based on canola meal obtained after protein extraction were developed to adsorb water from ethanol–water vapor mixture in a pressure swing adsorption (PSA) process. It was demonstrated that through the process over 99 wt % fuel grade ethanol was achieved from lower grade feeds containing 80–95 wt % ethanol at 90–110 °C and 136–243 kPa. The breakthrough curve technique was used to investigate the adsorption dynamics and equilibrium. The effects of temperature, pressure, vapor feed concentration, and adsorbent particle size on water and ethanol uptake and separation factor were examined. External water mass transfer coefficients were also calculated. The model based on Dubinin–Polanyi potential theory fit the water adsorption isotherms reasonably well. The mean free energy of water adsorption was calculated to be 0.04 kJ/mol, and heat of adsorption was −35.81 kJ/mol, which indicated the physical nature of the adsorption. Water saturated canola meal biosorbents were regenerated at 90 °C under vacuum and reused.
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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 | 0.001 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".