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Record W4362559071 · doi:10.13168/cs.2023.0010

THE EFFECT OF THE PRE-CRYSTALLISATION DEFECT SIZE ON THE STRENGTH LIMITATION IN LITHIUM SILICATE GLASS CERAMICS

2023· article· en· W4362559071 on OpenAlexafffund
Kristýna Hynková

Bibliographic record

VenueCeramics - Silikaty · 2023
Typearticle
Languageen
FieldMaterials Science
TopicAdvanced ceramic materials synthesis
Canadian institutionsUniversity of Alberta
FundersChina Scholarship CouncilUniverzita Palackého v OlomouciUniversity of Alberta
KeywordsCrystallizationMaterials scienceLithium disilicateComposite materialVickers hardness testCeramicIndentationGlass-ceramicFlexural strengthIndentation hardnessMicrostructureChemical engineering

Abstract

fetched live from OpenAlex

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.090
Threshold uncertainty score0.723

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.010
GPT teacher head0.245
Teacher spread0.235 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2023
Admission routes2
Has abstractyes

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