Optimising dental restorative composites: Numerical and statistical analysis of polymerization shrinkage and elastic modulus effects.

Light-cured resin-based dental restorative composites face challenges from polymerization shrinkage, which induces stress, potentially leading to microleakage, debonding, and recurrent caries. The elastic modulus (E) of these composites also influences stress distribution, with high-stress concentrations potentially leading to fractures in restored teeth. While finite element analysis (FEA) has been used to understand stress distribution, there is a lack of comprehensive studies exploring the combined effects of volumetric polymerization shrinkage (PS%) and E on restored molars. No research has addressed the influence of these factors on stress intensity at crack tips during mastication after shrinkage. This study investigates how variations in E and PS% affect the stress distribution at the restoration-enamel junctions (REJ) and restoration under mastication stimuli and shrinkage. Additionally, the study examines the impact of E and PS% on the stress intensity factor at the crack tip of a restored molar tooth. A 3D model of an upper molar was created from scanned images, converted into a mesh using 10-node tetrahedral elements, and analysed with finite element methods. The values of E ranged from 5 GPa to 25 GPa, and PS% ranged from 1 % to 5 %. Results showed that maximum principal stress varied with different E and PS% values, with the lowest stress occurring at E = 5 GPa and PS% = 1 % and the highest at E = 25 GPa and PS% = 5 %. Changes in these parameters also affected the locations of peak principal stress. Additionally, stress intensity factors decreased with increasing E but rose with higher PS%. Changes in E and PS% influence where and how much the principal stresses occur at the REJ and during restoration in response to shrinkage and mastication stimuli. This highlights the crucial role of material properties in the performance and durability of restorations, providing evidence-based insights that could guide material selection for MOD-restored molar teeth, ultimately enhancing restoration longevity and clinical outcomes.