Salting-Out Induced Aggregation for Selective Separation of Vanadyl-oxide Tetraphenyl-porphyrin from Heavy Oil
Bibliographic record
Abstract
This work presents a technique for separating vanadyl-oxide tetraphenyl-porphyrin, VOTPP, from heavy oil. This technique involves sequential separation of heavy oil and VOTPP from a solvent mixture of (4:1) volume ratio tetrahydrofuran, THF, and methanol upon stepwise addition of 1.0 M aqueous NaCl solution. Nevertheless, the salting-out of VOTPP from the solvent mixture was not NaCl specific, and many electrolytic solutions produced the same effect. The leftover concentration of heavy oil and VOTPP was determined using UV–vis spectroscopy following the Beer–Lambert law. Two bands were targeted, one at 549 nm and another at 700 nm. Both bands were assigned for heavy oil, and one, α band, at 549 nm was assigned for VOTPP. Accordingly, the leftover concentration of VOTPP was back calculated once the concentration of heavy oil was obtained from the absorbance measurement at 700 nm. Optimum separation required lower volume percent of NaCl at lower heavy oil concentration, and 10 vol % NaCl provided the best window for separation at 100 ppm heavy oil, while 20 vol % was needed for 1000 and 2000 ppm heavy oil.
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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) | 0.000 | 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".