THE EFFECT OF THE PRE-CRYSTALLISATION DEFECT SIZE ON THE STRENGTH LIMITATION IN LITHIUM SILICATE GLASS CERAMICS
Bibliographic record
Abstract
The objective of this study was to explore how the size of pre-crystallisation defects affects the strength of a lithium disilicate glass ceramic.A total of seven groups of lithium disilicate glass-ceramic (IPS e.max ® CAD) disc shape specimens (thickness 1.1 ± 0.1mm) were fabricated (n = 15).Each group corresponded to the varying severity of controlled surface defects made by a Vickers hardness indenter in a partially crystallised state.All the discs followed the manufacturer specified crystallisation process.The controlled defects were analysed with the use of optical microscopy and atomic force microscopy in both the partially crystallised phase and after crystallisation.The bi-axial flexural strength (BFS) was measured using a ball-on-ring configuration after crystallisation.A one-way ANOVA revealed a significant difference (p = 0.028).The post-hoc Tukey test revealed a significant difference (p < 0.01) existed between the 0.2 kg and 2 kg indentation groups, with no other pairwise differences.The survivability plots highlight the low BFS outliers occurring in the 1.0 and 2.0 kg static load groups.The Atomic Force Microscopy shows apparent differences before and after crystallisation.The crystallisation process helps to mitigate the strength limiting defects, but it also has a limit.Therefore, it is necessary to minimise the surface defects generated through the pre-crystallisation manufacturing procedures.
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 | 0.001 |
| 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".