Effects of surface glazing on the mechanical and biological properties of 3D printed permanent dental resin materials.

Purpose This study aimed to determine the surface glazing effect on the mechanical and biological properties of three-dimensional printed dental permanent resins.Methods Specimens were prepared using Formlabs, Graphy Tera Harz permanent, and NextDent C&B temporary crown resins. Specimens were divided into three groups: samples with untreated surfaces, glazed surfaces, and sand-glazed surfaces.

Effect of air abrasion, acid etching, and aging on the shear bond strength with resin cement to 3Y-TZP zirconia.

This study investigates the effect of acid etching treatment on the surface microstructure, surface roughness, and surface contact angle of zirconia and compares the effects of air abrasion, different etching times, and aging on the shear bond strength (SBS) of resin cement on the zirconia surface. 480 specimens (9 × 10 × 10 mm) were divided into as-sintered and air-abraded groups, and each group was further subdivided into six groups based on etching time (0, 3, 5, 10, 20, and 30 min). The etching solution comprised hydrofluoric acid 25%, sulfuric acid 16%, hydrogen peroxide, methyl alcohol, and purified water.

Effects of heat-treatment methods on cytocompatibility and mechanical properties of dental products 3D-printed using photopolymerized resin.

Purpose: The purpose of this study was to test heat-treatment methods for improving the cytocompatibility of dental 3D printable photopolymer resins.

Methods: Nextdent C&B resin and a digital light processing 3D printer were used to print all specimens, which were divided into seven groups as follows: 1-month storage at controlled room temperature, 20 to 25 °C (RT), 24-hour storage at RT, 24-hour storage in RT water, 1-min immersion in 80 °C water, 1-min immersion in 100 °C water, 5-min immersion in 100 °C water, and autoclaving. Cell viability tests, cytotoxicity tests, and confocal laser scanning microscopy were performed to analyze the cytocompatibility of the 3D-printed resin.

Effects of the Washing Time and Washing Solution on the Biocompatibility and Mechanical Properties of 3D Printed Dental Resin Materials.

Three-dimensional (3D) printing technology is highly regarded in the field of dentistry. Three-dimensional printed resin restorations must undergo a washing process to remove residual resin on the surface after they have been manufactured. However, the effect of the use of different washing solutions and washing times on the biocompatibility of the resulting resin restorations is unclear.

A Comparison of Accuracy of Different Dental Restorative Materials between Intraoral Scanning and Conventional Impression-Taking: An In Vitro Study.

The properties of underlying substrates influence the quality of an intraoral scan, but few studies have compared the outcomes using common restorative materials. In this study, we aimed to compare the accuracy of digital and conventional impressions recorded for four different dental materials as the substrates. Experimental crowns were produced with a metallic surface (gold or cobalt-chromium alloy (Co-Cr)) or without a metallic surface (zirconia or PMMA (polymethyl methacrylate)).

Effects of Groove Sealing of the Posterior Occlusal Surface and Offset of the Internal Surface on the Internal Fit and Accuracy of Implant Placements Using 3D-Printed Surgical Guides: An In Vitro Study.

This study evaluated the internal fit and the accuracy of the implant placement position in order to determine how the surface shape of the tooth and the offset influence the accuracy of the surgical guide. The acquired digital data were analyzed in three dimensions using 3D inspection software. The obtained results confirmed that the internal fit was better in the groove sealing (GS) group (164.

Sleeve insert scan body to predict implant placement position by using implant surgical guides: A dental technique.

In studies that assessed the accuracy of implant surgical guides, evaluations were based on the placement position of the implant by using a manufactured surgical guide. However, such assessments could involve errors that may occur during implant placement. Therefore, evaluating the 3-dimensional accuracy of the fabrication of the implant surgical guide itself is not enough.

Evaluation of the Color Stability of 3D-Printed Crown and Bridge Materials against Various Sources of Discoloration: An In Vitro Study.

Recent advances in three-dimensional (3D) printing have introduced new materials that can be utilized for dental restorations. Nonetheless, there are limited studies on the color stability of restorations using 3D-printed crowns and bridge resins. Herein, the color stability of conventional computer-aided design/computer-aided manufacturing (CAD/CAM) blocks and 3D-printing resins was evaluated and assessed for their degrees of discoloration based on material type, colorant types (grape juice, coffee, curry, and distilled water (control group)), and storage duration (2, 7, and 30 days) in the colorants.

Effects of Post-Curing Time on the Mechanical and Color Properties of Three-Dimensional Printed Crown and Bridge Materials.

Three-dimensional (3D) printing is increasingly being utilized in the dental field. After fabricating a prosthesis using a 3D printed resin, a post-curing process is required to improve its mechanical properties, but there has been insufficient research on the optimal post-curing conditions. We used various 3D printed crown and bridge materials in this study, and evaluated the changes in their properties according to post-curing time by evaluating the flexural strength, Weibull modulus, Vickers hardness, color change, degree of conversion, and biocompatibility.

Transfer Learning via Deep Neural Networks for Implant Fixture System Classification Using Periapical Radiographs.

In the absence of accurate medical records, it is critical to correctly classify implant fixture systems using periapical radiographs to provide accurate diagnoses and treatments to patients or to respond to complications. The purpose of this study was to evaluate whether deep neural networks can identify four different types of implants on intraoral radiographs. In this study, images of 801 patients who underwent periapical radiographs between 2005 and 2019 at Yonsei University Dental Hospital were used.