3D Digital Image Correlation Analysis of the Shrinkage Strain in Four Dual Cure Composite Cements

Abstract

The introduction of resin-based cements and an adhesive-bonding system in daily dental practice has given the opportunity to increase the retention of previously conventional cemented restorations and the optimal results in esthetic. This experimental study employed the 3D Digital Image Correlation Method (3D-DIC) for detecting shrinkage strain in four dual cured composite cements. The aim was to visualize measure, analyze, and compare strain fields in four resin-based cements using the 3D-DIC method. A total of 72 samples were divided into 4 groups considering variations in sample types, diameter, and thickness. Four types of composite cements: RelyX U200 (3 M ESPE, St. Paul, MN, USA), MaxCem Elite (Kerr, Orange, CA, USA), Multilink Automix (Ivoclar Vivadent, Schaan, Liechtenstein), and SeT PP (SDI, Australia) were used. Each type had diameters of 3 mm, 4 mm, and 5 mm, respectively, combined with two different values of thickness: 1 mm and 2 mm. Thickness had an important role on strain detected in all tested materials showing higher strain in samples with 2 mm thickness compared to 1 mm samples. Shrinkage strain values were the highest in Set PP samples indicated the possibility of undesirable de-bonding.

Polymerization Shrinkage, Hygroscopic Expansion, Elastic Modulus and Degree of Conversion of Different Composites for Dental Application

“…The mercury capilar dilatometer is an efficient example to obtain shrinkage data, however it is too complex and limited to measure chemical composites, as it has to be prepared before its placement into the dilatometer [31]. Some authors calculated the volumetric shrinkage by the linear contraction, assuming that the composite material has an isotropic behavior [32], however this is not what happens for all cases. Therefore, the development of studies that characterize different properties from the available dental biomaterials could provide suitable data to better predict the clinical behavior of dental restorations.…”