Metal Porphyrin Adsorption onto Asphaltene in Pentane Solution: A Comparison between Vanadyl and Nickel Etioporphyrins
Bibliographic record
Abstract
In the solvent deasphalting process, it is necessary to study the interaction between metal porphyrins and asphaltene for improving demetallization efficiency (vanadyl or nickel). Therefore, the main aim of this study is to investigate the adsorption kinetics and thermodynamics of nickel etioporphyrins onto Canadian oil sands bitumen vacuum tower bottom (VTB) asphaltene, and to compare the results with that of vanadyl etioporphyrins onto VTB asphaltene in pentane. Asphaltene was characterized by transmission electron microscopy (TEM), N 2 adsorption, and X-ray diffraction technique (XRD). The results showed that vanadyl/nickel porphyrins were adsorbed onto the VTB asphaltene. The adsorption rate varied as the dosage of asphaltene, the concentration of vanadyl/nickel porphyrins, and the adsorption temperature changed. By comparison of the pseudo-first-order adsorption kinetics model of the two adsorption processes, the adsorption rate for nickel octaethylporphyrin (Ni-OEP) was faster than that for vanadyl octaethylporphyrin (VO-OEP). Furthermore, the equilibrium adsorption capacity of Ni-OEP was greater than that of VO-OEP. Moreover, the adsorption equilibriums of vanadyl/nickel porphyrins both wonderfully fitted to the Freundlich isotherm. In addition, the Δ G ° and Δ H ° values of two adsorption processes had regressed at different temperatures. Compared with Ni-OEP, in the same conditions it was easier for VO-OEP to be adsorbed and more heat was released in the process.
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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".