Effect of Passive Film on Corrosion Behavior of Passivated Electroless Ni-P Coating
Bibliographic record
Abstract
In heavy oil wells, carbon steel casing and tubing often suffers from severe corrosion due to the presence of corrosive gases, chlorine compounds and solid particles in the corrosive medium. An electroless Ni-P coating (EN coating) has been applied to the carbon steel surface, which presents better corrosion resistance than the substrate. However, defects such as microscopic pores, as the corrosion paths, will be inevitably present in EN coating, which can cause the corrosion of carbon steel substrate despite the coating. To solve this problem, passivation treatment can be used to create a passive film on EN coating surface and improve the corrosion resistance of the coating. However, erosion-corrosion also occurs when solid particles are suspended in the corrosive medium, and the erosion-corrosion mechanism of the passivated Ni-P coating is not known. In this work, a passive film was formed on the EN coating in the K2Cr2O7-containing bath with and without an applied passivation potential. The corrosion properties of passive films were evaluated by means of electrochemical measurements and compared to the non-passivated EN coating. SEM, XPS, and EDS were employed to analyze the chemical composition and surface morphology of the films. The results showed an obvious passive region of passive film on EN coating in the potential range of -0.1 – 0.45 V (vs. SCE). The corrosion current of the passivated EN coating through chemical passivation treatment (CPT) was reduced by 61 % than that of non-passivated EN coating film, while it was reduced by 79 % through a combination of CPT and electrochemical passivation treatment (EPT) with an applied passivation potential of 0.2V (vs. SCE). These results demonstrate how EPT can significantly improve the corrosion resistance of the passive film. Erosion-corrosion of passivated EN coatings through CPT and EPT was studied under an applied passivation potential by means of a single particle impingement technique. The transient current response to disruption of the passive film was obtained at different impact angles and velocities, which was the result of different damaged surface area produced by solid particle impingement. Correspondingly, the hydrodynamic effects on erosion-corrosion of passivated EN coating were predictable with a theoretical model based on kinetic analysis.
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 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 | 0.001 |
| 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 | 0.001 |
| 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".