Experimental investigation and parameter optimization of Cr2O3 atmospheric plasma spray nanocoatings
Bibliographic record
Abstract
In this research, Cr2O3 ceramic nano-sized powder particles were prepared using ball milling and then were granulated to reach the proper size for spraying. Afterward, Cr2O3 nano-coatings were deposited by atmospheric plasma spraying (APS) process onto stainless steel substrates. To optimize APS parameters, spraying was carried out under six conditions with different parameters. Microstructures of the elemental/milled powder and coatings were characterized via a field emission scanning electron microscope (FESEM) equipped with energy-dispersive spectroscopy (EDS). In this research, Cr2O3 coatings were deposited under different spraying conditions to understand the effect of APS parameters on the splat formation, deposition efficiency, and porosities of the coatings. After parameter optimization, spraying was performed under a high deposition efficiency of 46.0±1.3%. The optimized Cr2O3 coatings showed porosity content, Knoop microhardness, and adhesive strengths of 8.7±2.2%, 823±27 HK0.2, and 49±4 MPa, respectively; making them a good candidate for industrial use.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.000 |
| 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".