Bibliographic record
Abstract
The low-temperature (200°C) environmental degradation in water of tetragonal zirconia polycrystals doped with 3mol% yttria (3Y-TZP) was effectively prevented by a carbonitriding heat treatment process in which the sintered samples of 3Y-TZP were buried in a uniformly mixed powder of ZrN and graphite at 1400°C to 1600°C for 2 to 8 hours. This surface modification of the sintered samples resulted in a surface layer that was stabilized by both nitrogen and carbon ions. the effect on phase stability of the introduction of both nitrogen and carbon ions into tetragonal zirconia was compared with the individual effect of nitrogen or carbon ions. the stronger surface stability is attributed to the simultaneous effects of nitrogen and carbon ions since nitrogen and carbon ions occupy totally different sites in the zirconia lattice. It is found that the potential decrease in bulk strength due to the growth of the grains in the interior had been minimized when a relatively lower heat treating temperature of 1400°C is applied for the carbonitriding than for the individual gas nitriding or carburizing processes (300°C lower than gas nitriding temperature and 100°C lower than carburizing temperature). the thickness of surface transformed layer was observed to increase by a parabolic rate law which shows that the carbonitriding process is controlled by diffusion. the shorter time that is needed to obtain the same thickness surface stabilized layer than for the individual gas nitriding or carburizing process makes the process more attractive for commercial application.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".