High Temperature Oxidation Behaviour of Nickel Based Nanostructured Composite Coatings
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Bibliographic record
Abstract
The electrodeposition of nanostructured composite coatings involves the co-deposition of nanosized oxide particles such as TiO 2 , Al 2 O 3 and Y 2 O 3 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 (TiO 2 and Al 2 O 3 ). 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 Al 2 O 3 and TiO 2 .
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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 it