Hot-corrosion behaviour of CNT reinforced Cr <sub>3</sub> C <sub>2</sub> -NiCr coatings working under high-temperature sprayed by HVOF method
Bibliographic record
Abstract
The thermal power plant boiler tubes experience degradation of their surfaces due to oxidation and molten salt corrosion while working at elevated temperatures. The formation of protective coating layers can overcome such surface degradation. In the current research, protective coated layers composed of Cr 3 C 2 -25% NiCr/Carbon nanotube coatings are deposited on the ASTM SA-213T12 boiler tube substrate by the High-Velocity Oxy-Fuel (HVOF) thermal method. The coating powder Cr 3 C 2 -25%NiCr is reinforced with 3, 5 and 7 wt% of Multi-Wall Carbon Nano-Tube (MWCNT) prior to deposition. The uncoated and coated specimens are evaluated for hot corrosion behaviour in the molten salt environment (Na 2 SO 4 + 60%V 2 O 5 ) for 50 cycles, constituting 1 h of heating at 600 °C. Thermogravimetric analysis is used to investigate the kinetics of hot corrosion behaviour in both coated and uncoated samples. Coatings are characterized with the help of X-ray diffraction and Scanning Electron Microscope/Energy Dispersive Spectroscopy (SEM/EDS) techniques. Microstructural investigations with the help of SEM/EDS and X-ray diffraction of coated and uncoated samples revealed that 7 wt% of CNT coated samples minimized the voids and pores of the coatings, leading to better interlocking with the substrate surface. Furthermore, it is observed in the studies that the appreciable corrosion resistance of 7 wt% of CNT composite coatings is higher than 3 and 5 wt% of CNT-coated and uncoated samples.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".