Impact of Orthodontic Adhesive Magnets on Degree of Conversion and the kinetics of polymerization
Journal Title: Al-Bahir Journal for Engineering and Pure Sciences - Year 2023, Vol 3, Issue 2
Abstract
The purpose of this study was to investigate the effects of storing uncured photopolymerized dental adhesive in a magnetic field on their kinetics of polymerization and degree of conversion (DC%). Method: Vage Ortho Uv orthodontic adhesive was used in this experiment. Under constant frequency (50 Hz), the applied magnetic field was used at two different intensities (fixed at 0.01 T and 0.05 T) for 5 min each. Using Fourier transform infrared spectroscopy (FTIRATR), the degree of conversion (DC%) and polymerization kinetics were assessed. Results: There was a clear improvement in the results when compared to the control, the DC% mean tends to increase as MF increases starting at 0.05 T. Conclusions: The DC% of the Vega ortho Uv assessed orthodontic adhesive is influenced by the MF. Uncured orthodontic adhesive that has been exposed to MF for five minutes improves the changed bond angles or causes bond elongations, both of which would cause molecular deformation.
Authors and Affiliations
Saud khalil Al hauly, Mazin Ahmed, Sarmad S. S. Al Qassar
Detection of Data over wireless mobile channels based on Maximum Likelihood Technique
Next generation wireless systems are characterized by very high transmission bit rates which gives rise to severe Intersymbol interference (ISI) and this makes the detection process very challenging. Hence, assessment o...
Green synthesis of Nickel Oxide Nanoparticles using Syzygium Aromatic Extract: Characterization and Biological Applications
Retraction of “Fabrication and Characterization of Wood Fiber Reinforced Polymer Composites”
Retraction of “Fabrication and Characterization of Wood Fiber Reinforced Polymer Composites”
A New Generalized Gamma-Weibull Distribution and its Applications
Best Neural Network Approximation by using Bernstein Polynomials with GRNN Learning Application
Bernstein polynomials are one of the first and main tools for function approximation. On the other hand, neural networks have many useful applications in approximation and other fields as well. In this paper, we study h...