Investigation of the Antifouling Mechanism of Electroless Nickel–Phosphorus Coating against Sand and Bitumen
Bibliographic record
Abstract
Antifouling coatings have attracted much attention in applications of industrial equipment and systems. The accumulation of foulants on downhole equipment used in the steam-assisted gravity drainage process for oil sand extraction reduces the recovery efficiency of bitumen and causes failures of the equipment. Applying suitable coatings is expected to endow antifouling property to the related substrate surface. Understanding the interaction mechanism between foulants and antifouling coating is critical for the evaluation and prediction of antifouling performance. In this work, antifouling coating consisting of Ni and P was prepared on the L80 carbon steel substrate, which is a commonly used material in downhole equipment. The surface properties (e.g., morphology and surface energy) of the Ni–P coating and pristine L80 substrates were characterized. The intermolecular and surface forces between typical foulants (e.g., silica and bitumen-coated silica) and Ni–P coated and uncoated L80 substrates were directly measured using the atomic force microscope colloidal probe technique to investigate the fouling mechanisms and predict the fouling behaviors of the foulants at the nanoscale. It was found that the Ni–P coating possessed lower surface energy, weaker attractive van der Waals interaction, and smaller adhesion to both silica and bitumen as compared to the uncoated L80 substrate. Bulk soaking experiments were also conducted accordingly which further demonstrated the antifouling performance of Ni–P coating against silica and bitumen, agreeing well with the surface force measurements. This work has improved the fundamental understanding of fouling behaviors of silica and bitumen and the antifouling mechanism of Ni–P coating at the nanoscale, with potential applications in many related processes in chemical and petroleum industries. The methodologies employed in this work can be readily extended for investigating fouling and antifouling mechanisms of different materials in various engineering fields.
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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".