ArticleDental materials : official publication of the Academy of Dental Materials2025
Fractal analysis in different regions of a fracture surface in a dental glass-ceramic.
Article in Dental materials : official publication of the Academy of Dental Materials, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
- Fatigue in Dental Ceramics: A Call for Standardized Testing and Emerging Manufacturing Technologies.Materials (Basel, Switzerland) · 2026Article
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6 authors.
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Abstract
objectivesPrevious studies have reported the fractal dimension of dental ceramic fracture surfaces from mist and hackle regions. The aim of this study was to determine and compare the fractal dimensional increment between the mirror, mist, and hackle regions of lithium disilicate fracture surfaces.
methodsNine bar-shaped specimens were prepared from lithium disilicate glass-ceramic. One face of each specimen was indented using a Knoop diamond at 10 N followed by loading in 4-point flexure until failure at a loading rate of 12.6 MPa/s to avoid environmental slow crack growth. Fracture surfaces were replicated in epoxy, and an atomic force microscope (AFM) was used to scan the replicas. Noise in scans was reduced by Laplace transform filter. The FRACTALS software was used to determine the fractal dimensional increment (D*) by the Minkowski cover algorithm.
resultsMedian D values (25 %, 75 % quartiles) from mirror, mist, and hackle regions were 2.14 (2.12, 2.14), 2.14 (2.12, 2.15), and 2.14 (2.12, 2.15), respectively. A multilevel mixed model with clustering on repeated measures showed that the fractal dimension between the mirror-mist (p = 0.51), mist-hackle (p = 0.90), and mirror-hackle (p = 0.43) regions are not significantly different. SIGNIFICANCE: Fractal dimension in mirror, mist, and hackle regions of the fracture surface were not significantly different in lithia disilicate glass-ceramics. Any portion of the primary fracture surface can be analyzed using fractal analysis to investigate the conditions present at the time of failure.
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