Carboxylic acid recovery from Fischer–Tropsch aqueous product by fractional freezing
Bibliographic record
Abstract
Abstract About half of the product from iron-based high-temperature Fischer–Tropsch synthesis is an aqueous product containing dissolved oxygenates. Volatile oxygenates can be recovered by distillation, but the bulk of the carboxylic acids remain in the water, which is called acid water. Fractional freezing was explored as a process for producing a more concentrated carboxylic acid solution from which the carboxylic acids could be recovered as petrochemical products, while concomitantly producing a cleaner wastewater. Solid–liquid equilibrium data were collected for aqueous solutions of acetic acid, propionic acid, and butyric acid. A synthetic Fischer–Tropsch acid water mixture (0.70 wt% acetic acid, 0.15 wt% propionic acid, and 0.15 wt% butyric acid) was prepared and the liquid phase concentrations of the acid species at solid–liquid equilibrium were determined. Control experiments with material balance closure on each of the carboxylic acid species were performed at selected conditions. Having more than one carboxylic acid species present in the mixture meaningfully changed the solid–liquid equilibrium versus temperature of the system. The carboxylic acids partitioned between the solid phase and the liquid phase and a practical design would require multiple duty-controlled solid–liquid equilibrium stages, with most of the separation taking place in the temperature range 0 to − 5 °C.
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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) | 0.000 | 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 | 0.001 |
| 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 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".