This study utilized a statistical nanoindentation analysis technique (SNT) to measure the amount of organic and inorganic constituents of twenty different brands of dental resin-based composites (RBCs) and tested whether… Click to show full abstract
This study utilized a statistical nanoindentation analysis technique (SNT) to measure the amount of organic and inorganic constituents of twenty different brands of dental resin-based composites (RBCs) and tested whether their macro-property such as flexural modulus could be approximated by the proportions of constituents' micromechanical signatures using various rules of mixtures. The probability density function (PDF) of constitutive moduli per RBC brand were measured for three groups, comprised of different indent arrays and inter-indent spacings. SNT was then applied to deconvolute each PDF, from which the effective filler (μF) and matrix (μM) moduli and filler (VF) and matrix (VM) volume fractions per RBC brand were computed. VF and VM values obtained via SNT were strongly correlated with VF and VM obtained via Thermogravimetric Analysis and Archimedes method. The "observed" flexural modulus (EcFS) measured under macro-experiment were well associated with "predicted" effective modulus (EcEff) measured under nano-experiment, thereby establishing that global modulus was strongly affected by the constituents' micromechanics. However, the "predicted" EcEff were proportionally higher than the "observed" EcFS. VF was a confounder to EcFS and EcEff, whereby the influence of VF on both modular ratios (EcFS/μM and EcEff/μM) was best modeled by an exponential regression.
               
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