Synchrotron X-ray spectromicroscopy analysis of wear tested graphene-containing alumina coatings
Bibliographic record
Abstract
Thermally sprayed Al2O3 coatings containing graphene nano platelets (GNP) have been shown to exhibit improved wear resistance. To understand the positive influence of GNP on wear properties, scanning transmission X-ray microscopy (STXM) analyses were performed to determine the structural and chemical changes that occur on the GNP and alumina matrix after wear tests. STXM results acquired at the C K-edge showed that the GNP are aligned parallel to the specimen surface in the as-sprayed coatings. GNP flakes are also observed at the tribo-surface of the wear tested sample. The results obtained at the Al K-edge show that the aluminum oxide below the wear track becomes amorphous during the wear test and carbon is dissolved in it. Wear tests performed on thermally sprayed pure alumina samples (without GNP) and on sintered bulk alumina prove that neither the presence of GNP nor the porosity in the coating are responsible for the amorphization of the alumina matrix. The results discussed in this work advance the fundamental understanding of graphene-containing composites, which is considered very important to exploit the unique advantages of graphene in technological applications.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".