Flocculation of Silica Particles from a Model Oil Solution: Effect of Adsorbed Asphaltenes
Bibliographic record
Abstract
The removal of solid particulates from crude oils and hydrocarbon streams is a common challenge in refining. In this study, we investigate the role of adsorbed and precipitated asphaltenes in flocculation and sedimentation of particles from a model oil. Silica particles (1 μm) were suspended in a reacted pitch material (5 wt %) dissolved in toluene to give a model oil (O). In toluene solution, the silica suspension was stabilized by the asphaltenes in the pitch. The settling rates of silica and asphaltene flocs after dilution with n -pentane as the solvent (S) were studied for a range of solvent/oil (S/O) ratios. The onset of asphaltene precipitation was determined to occur at a S/O of 0.43 by weight. At S/O < 0.33, the removal efficiency of silica particles from the oil phase by sedimentation was poor. Above this ratio, however, the concentration of silica remaining in the supernatant decreased. For instance, for S/O = 0.33, the supernatant contained 0.09 ± 0.01 wt % silica as compared to around 4 wt % originally. There was no significant difference in the removal efficiency whether the silica particles were hydrophilic or hydrophobic. Fourier transform infrared (FTIR) spectroscopy in the region of 2800−3000 cm −1 showed hydrocarbon adsorption on the surface of the silica before the onset of asphaltene precipitation; however, the amount of adsorption increased significantly beyond this point. The rapid flocculation of the silica particles at 0.33 < S/O < 0.43 was attributed to adsorbed asphaltenes on the silica surfaces.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 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".