journal article·2012-10

Iodonium salt improves the dentin bonding performance in an experimental dental adhesive resin

Fernanda B. Leal, Giana S. Lima, Fabrício M. Collares, Susana M. Samuel, Cesar L. Petzhold, Evandro Piva, Fabrício A. Ogliari

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Abstract

The aim of this study was to evaluate the influence of an iodonium salt on the immediate and long-term microtensile bond strength to dentin of an experimental dental two-step, self-etching adhesive system. A model dental adhesive resin was formulated using bisphenol A glicidyl dimethacrylate (Bis-GMA), triethylene glicol dimethacrylate (TEGDMA), and hydroxyethyl methacrylate (HEMA), which was polymerized using four combinations of photo-initiators and coinitiators. A group using only camphorquinone (CQ), two binary systems (CQ and ethyl 4-dimethylamine benzoate (CQ+EDAB), CQ and diphenyliodonium hexafluorphosphate (CQ+DPIHFP)) and a ternary system (CQ+EDAB+DPIHFP) was investigated. Clearfil SE Bond (CSEB) was used as a commercial reference. Bond strength to bovine dentin was assessed through microtensile bond tests measured in MPa in a universal testing machine. The beam specimens were stored in distilled water at 37 °C for 24 h and 1 year. Two-way ANOVA and Student–Newman–Keuls` post-hoc tests were used to compare means of groups ( α=5%) and failure modes classified under magnification. After 24 h, the ternary system showed a bond strength similar to that of the binary system CQ+EDAB and the commercial material. After 1 year of storage, the μTBS values of the group CQ+EDAB+DPIHFP showed a bond strength significantly higher ( p<0.05) than those of the CQ, CQ+DPIHFP, and CQ+EDAB groups and no difference from that of the CSEB group. The ternary photo-initiator system with iodonium salt maintained increased bond strength to dentin of model self-etching adhesive systems after 1 year of aging.
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Research context

OpenAlex topics: Dental materials and restorations · Dental Research and COVID-19 · Photopolymerization techniques and applications

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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