Evaluating Various Preparation Protocols on the Shear Bond Strength of Repaired Composite

ABSTRACT Introduction The aim of this study is to evaluate the effect of different combinations of various surface treatments on the shear bond strength (SBS) of repaired composite resin. Materials and methods A total of 122 composite samples were prepared from Filtek Z350 XT. Samples were light cured and stored for 6 weeks. Surface treatment of old composite was done in five groups: Group I: bur roughening + phosphoric acid etching, group II: bur roughening + hydrofluoric acid etching + silane coupling agent, group II: air abrasion + phosphoric acid etching, group IV: air abrasion + phosphoric acid etching + silane coupling agent, group V: air abrasion + hydrofluoric acid etching + silane coupling agent. Bonding agent was applied to all surface-treated old composites and light cured. The fresh composite resin was bonded to treated surfaces and cured and stored in water at 37°C for 6 weeks. Shear bond strength was measured by a universal testing machine. Results Shear bond strength values of all groups were not statistically significant except for group V, which showed statistically significant higher SBS than group III. Conclusion Techniques with readily available materials at the clinic can attain similar SBS to more elaborate technique involving potentially hazardous materials. How to cite this article Al-Asmar AA, Hatamleh KS, Hatamleh M, Al-Rabab'ah M. Evaluating Various Preparation Protocols on the Shear Bond Strength of Repaired Composite. J Contemp Dent Pract 2017;18(3):182-187. </jats:sec

Mathematical Modelling for Predicting Thermal Properties of Selected Limestone

Due to a lack of geotechnical and geothermal studies on Jordanian limestone, this paper aims to provide the thermal properties, including thermal conductivity, thermal diffusivity, and specific heat, using the Hot Disk Transient Plane Source (TPS) 2200 method. It also aims to provide a set of mathematical models through which the thermal properties can be indirectly predicted from the rocks’ physical and engineering properties. One hundred cylindrical rock specimens with a height of 20 cm and a diameter of 10 cm were extracted and prepared. The results showed that the thermal conductivity values ranged between (1.931–3.468) (W/(m × k)), thermal diffusivity (1.032–1.81) (mm2/s), and specific heat (1.57–2.563) ((MJ)/(m3 × K)). The results also suggest a direct relationship between conductivity and diffusivity and an inverse relationship between conductivity and specific heat. On the other hand, the results indicate the direct relationship between the conductivity and diffusivity, and the inverse relationship between the specific heat and density, hardness, sound velocity, and rock strength; the opposite happens when the rock’s porosity is considered. Simple regression, multivariate regression, and the backpropagation–artificial neural network (BP–ANN) approach were utilized to predict the thermal properties of limestone. Results indicated that the ANN model provided superior prediction performance compared to other models