A TEM study of nanostructures and interfaces in the hot-press sintered ZrB2–SiC–Si3N4 composites
Bibliographic record
Abstract
A fully dense ZrB2–30 vol% SiC composite containing 5 wt% Si3N4 and 4 wt% phenolic resin (1.6 wt% carbon) was sintered using the hot-pressing route under the external pressure of 10 MPa at 1900 ºC for 2 h. The microstructural evolution and interfacial phenomena were scrutinized using advanced microscopy facilities such as high-resolution transmission electron microscopy (HRTEM) and field emission scanning electron microscopy (FESEM). The FESEM images showed the ZrB2 and SiC grains without any evidence of Si3N4. The formation of the hexagonal BN (hBN) phase was proven in the sintered composite. The hBN nanosheets had a graphite-like morphology with an average thickness of 20 nm. This phase has a perpendicular orientation to the pressure direction and prevents abnormal ZrB2 grain growth. Two types of ZrB2/SiC interfaces were detected, which exhibited an amorphous phase along with the grain boundary and a clean/smooth interface, resulting from the Si3N4 addition. HRTEM and inverse fast Fourier transform (IFFT) observations disclosed that the d-spacing value in the ZrB2 grain (0.335 nm) is higher than those reported in the literature. Furthermore, it was found that the exerted pressure during the sintering distorted atomic planes. The presence of numerous dislocations within the ZrB2 grains confirmed dislocation creep as the main densification mechanism.
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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".