The Fracture Load as a Function of the Material Thickness: The Key to Computing the Strength of Monolithic All-Ceramic Materials?

The thickness of a material has a significant impact on its fracture load. The aim of the study was to find and describe a mathematical relationship between the material thickness and the fracture load for dental all-ceramics. In total, 180 specimens were prepared from a leucite silicate ceramic (ESS), a lithium disilicate ceramic (EMX), and a 3Y-TZP zirconia ceramic (LP) in five thicknesses (0.4, 0.7, 1.0, 1.3, and 1.6 mm; n = 12). The fracture load of all specimens was determined using the biaxial bending test according to the DIN EN ISO 6872. The regression analyses for the linear, quadratic, and cubic curve characteristics of the materials were conducted, and the cubic regression curves showed the best correlation (coefficients of determination (R2): ESS R2 = 0.974, EMX R2 = 0.947, LP R2 = 0.969) for the fracture load values as a function of the material thickness. A cubic relationship could be described for the materials investigated. Applying the cubic function and material-specific fracture-load coefficients, the respective fracture load values can be calculated for the individual material thicknesses. These results help to improve and objectify the estimation of the fracture loads of restorations, to enable a more patient- and indication-centered situation-dependent material choice.

Predictable esthetics in hybrid and resin-based CAD/CAM restorative materials: Translucency as a function of material thickness.

AIM: The CAM of esthetically pleasing monolithic dental restorations presents with specific challenges. One vital parameter to consider is the translucency of the materials. Previous studies have proven a correlation between translucency and material thickness for various all-ceramic materials. The aim of the present study was to assess and define the relationship between thickness and translucency in modern resin-based restorative materials. MATERIALS AND METHODS: Specimens fabricated from two resin nano-ceramics (Cerasmart, Lava Ultimate), a polymer-infiltrated ceramic network (Vita Enamic), and a polymethyl methacrylate (Telio CAD) were examined, representing these different material classes. For each material, 12 specimens (n = 12) were fabricated in five thicknesses (0.4, 0.7, 1.0, 1.3, and 1.6 mm; N = 240). The translucency was measured with a spectrophotometer. The total light transmittance for each specimen was calculated applying specialized software. Regression curves were fitted to the results and their coefficient of determination (R2) fit was determined. RESULTS: Logarithmic regression curves showed the best R2 approximation (Cerasmart: R2 = 0.994; Vita Enamic: R2 = 0.978; Lava Ultimate: R2 = 0.997; Telio CAD: R2 = 0.997) to the light transmission values. CONCLUSIONS: The results of the present study indicate that the translucency of resin-based materials can be calculated using a mathematic approach to estimate their optical behavior. Cerasmart, Lava Ultimate, Vita Enamic, and Telio CAD exhibit a logarithmic relationship between material thickness and translucency. By determining material-specific coefficients for this logarithmic function, the resulting translucency can be computed for any given material thickness.

Predictable esthetics in all-ceramic restorations: Translucency as a function of material thickness.

BACKGROUND: The esthetic outcome of a dental restoration largely depends on the translucency of the materials used, especially for monolithic restorations. Research has been published reporting a correlation between translucency and material thickness. However, no mathematical formula has been described yet. The aim of the present study was to determine the mathematical relationship between material thickness and translucency of three dental ceramic materials. MATERIAL AND METHODS: Three representative all-ceramic materials were taken out of the group of silicate ceramics (IPS Empress CAD LT), lithium X-silicate ceramics (IPS e.max CAD LT), and oxide ceramics (Lava Plus HT). Sixty specimens with five different thicknesses (0.4, 0.7, 1.0, 1.3, and 1.6 mm; N = 60, n = 12) were produced out of each ceramic (N = 180). A spectrophotometer was used to measure the transmittance coefficient tc[%] for each wavelength within the visible light spectrum, and the total light transmittance (T%) was calculated for each specimen. Linear, exponential, and logarithmic regression curves were fitted to the results. RESULTS: The logarithmic regression curves exhibited the best correlation (R2; IPS Empress CAD LT, R2 = 0.996; IPS e.max CAD LT, R2 = 0.987; Lava Plus HT, R2 = 0.907) to the transmittance values. CONCLUSION: Within the limitations of the present study, the transmittance behavior of silicate ceramics, lithium-X-silicate ceramics, and oxide ceramics can be described by a logarithmic equation. The findings of this study therefore suggest that the optical behavior might be calculable by a mathematical approach.

Arithmetic Relationship between Fracture Load and Material Thickness of Resin-Based CAD-CAM Restorative Materials.

Data on the long-term behavior of computer-aided designed/computer-aided manufactured (CAD-CAM) resin-based composites are sparse. To achieve higher predictability on the mechanical behavior of these materials, the aim of the study was to establish a mathematical relationship between the material thickness of resin-based materials and their fracture load. The tested materials were Lava Ultimate (LU), Cerasmart (GC), Enamic (EN), and Telio CAD (TC). For this purpose, 60 specimens were prepared, each with five different material thicknesses between 0.4 mm and 1.6 mm (N = 60, n = 12). The fracture load of all specimens was determined using the biaxial flexural strength test (DIN EN ISO 6872). Regression curves were fitted to the results and their coefficient of determination (R2) was computed. Cubic regression curves showed the best R2 approximation (LU R2 = 0.947, GC R2 = 0.971, VE R2 = 0.981, TC R2 = 0.971) to the fracture load values. These findings imply that the fracture load of all tested resin-based materials has a cubic relationship to material thickness. By means of a cubic equation and material-specific fracture load coefficients, the fracture load can be calculated when material thickness is given. The approach enables a better predictability for resin-based restorations for the individual patient. Hence, the methodology might be reasonably applied to other restorative materials.