High Temperature Oxidation Behaviour of Nickel Based Nanostructured Composite Coatings
Bibliographic record
Abstract
The electrodeposition of nanostructured composite coatings involves the co-deposition of nanosized oxide particles such as TiO2, Al2O3 and Y2O3 into a corrosion resistant metal matrix such as nickel to improve the high temperature oxidation and erosion resistance of nickel coatings. The technique has several advantages over other methods for producing nanostructured composite coatings such as thermal metal spraying. Some of the main advantages are lower cost for equipment setup and lower material cost and the ease with which the process can be controlled. Although electrodeposited nanostructured coatings are being developed for various aerospace and marine applications, they have not yet been considered for protecting surfaces of components and piping that is used in technologies for the oil sands industry such as the In-Situ Combustion (ISC) process. The challenge with in-situ combustion oil production is that the combination of high temperature combustion gases and the presence of moving sand particles create an extremely severe environment in which high oxidation and erosion rates are expected. As a result there is a need to develop function specific coatings that can withstand both high temperatures and erosive environments in the oil sands industry. This paper presents results of high temperature oxidation behaviour of nickel coatings containing two types of nanosized oxide dispersions (TiO2 and Al2O3). High temperature oxidation tests were conducted in dry air for 500°C and 700°C. The oxidized specimens were examined by metallographic surface analysis and surface composition techniques such as Scanning Electron Microscopy (SEM), Wavelength Dispersive X-Ray Spectroscopy (WDS). The effects of nanosized oxide particles on high temperature oxidation behavior of nickel coatings have been studied. The results show an improvement in the high temperature oxidation resistance of nickel coatings dispersed with Al2O3 and TiO2.
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 | 0.000 |
| 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".