STRUCTURES AND MECHANICAL PROPERTIES OF MODULATED <font>ZrB</font><sub>2</sub>/<font>W</font> AND <font>ZrB</font><sub>2</sub>/<font>WN</font><sub>x</sub> NANOMULTILAYERS
Bibliographic record
Abstract
ZrB 2, W , WN x coatings and ZrB 2/ W , ZrB 2/ WN x multilayered coatings have been synthesized by ion beam assisted deposition at room temperature. X-ray diffraction (XRD), XP-2 surface profiler, scanning electron microscopy (SEM) and nano indenter were employed to investigate the influence of modulation periods and N + beam bombardment on microstructure and mechanical properties of the coatings. The low-angle XRD patterns and cross-sectional SEM indicate a well-defined composition modulation and layer structure of the multilayers. The multilayers with modulation periods ranging from 9 to 16 nm without N + bombardment possessed higher hardness and elastic modulus than the rule-of-mixtures value of monolithic ZrB 2 and W coatings. The highest hardness was 24 GPa. N + bombardment to growing multilayers gave a significant contribution to mechanical property enhancement. When modulation period is 9.6 nm, ZrB 2/ WN x multilayer with 200 eV N + bombardment reveals the highest hardness (30.2 GPa) and elastic modulus. This hardest multilayer also showed the improved residual stress and fracture resistance.
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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".