Multilayered Fibre-Matrix Interphases Derived From the Electrophoretic Deposition of Ceramic Nano-Powders
Bibliographic record
Abstract
Abstract A significant challenge within the manufacturing of Ceramic Matrix Composites (CMCs) is the creation of the fibre-matrix interphase which enables the damage tolerant behavior of CMCs. Chemical vapour deposition (CVD) has been a highly successful approach for fabricating fibre-matrix interphases; however, CVD requires capital intensive facilities and hazardous precursors. This work examines electrophoretic deposition (EPD) as an alternative route for the production of fibre-matrix interphases. Four multilayered fibre-matrix interphases (SiC/Al2O3, BN/ZrO2, ZrC/85wt%Al2O3-15wt%ZrO2, and SiC/Si3N4/SiC) were produced through multi-staged electrophoretic deposition of ceramic nano-powders upon SiC fibre bundles. A 25-2 factorial design of experiments is utilized to explore the effect of different levels of the following variables: electric field strength, duration, surfactant, solids loading and binder. Following deposition of the fibre-matrix interphase the fibre bundles are thinly coated with a SiC matrix through a reactive melt infiltration technique. The resultant microcomposites are then subjected to tensile loading until failure to determine which coating and deposition combination are the most likely to yield favorable tensile properties. Additional microscopy is performed to determine the uniformity and thickness of the coatings. The results are then examined to evaluate the suitability of electrophoretic deposition as a production technique for fibre-matrix interphase coatings in CMCs.
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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 | 0.000 | 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".