Flexural strength, flexural modulus and microhardness of milled vs. fused deposition modeling printed Zirconia; effect of conventional vs. speed sintering.

BACKGROUND: Various methods can be used for creating zirconia dental restorations, including 3-dimensional (3D) printing and computer-aided design/ computer-aided manufacturing (CAD/CAM) milling. The fused deposition modeling (FDM) printing method for zirconia presents numerous advantages, albeit research on the mechanical properties of these materials and resultant restorations remains scarce. Such developments are undeniably intriguing and warrant further investigation. The objective of the present study was to evaluate the impact of the sintering firing cycle (Conventional vs. Speed sintering) on the flexural strength, flexural modulus, and Vickers Microhardness of milled vs. FDM printed zirconia. METHODS: A total of 60 bars (2 × 5 × 27 mm) were fabricated for flexural strength testing, along with 40 discs (12 × 1.5 mm) for Vickers microhardness testing. Half of the specimens underwent conventional sintering, while the other half underwent a speed sintering cycle. The flexural strength and modulus were determined by a three-point bending test in a universal testing machine. The microhardness of the specimens was evaluated using a Vickers microhardness tester. Statistical analysis was performed using a two-way ANOVA test with a post-hoc Tukey test (p < 0.05). RESULTS: CAD/CAM milled zirconia had significantly higher flexural strength and modulus than FDM-printed zirconia. The sintering process did not significantly affect the flexural strength or modulus of milled or FDM-printed zirconia. The milled speed sintering group had significantly higher values in the Vickers microhardness test compared to the other groups. CONCLUSIONS: The mechanical properties of FDM-printed zirconia specimens were not found to be comparable to those of milled zirconia. Speed sintering cycle may produce milled zirconia restorations with similar flexural strength and modulus to conventional sintering, and even higher Vickers Microhardness values.

Revolutionizing CAD/CAM-based restorative dental processes and materials with artificial intelligence: a concise narrative review.

Artificial intelligence (AI) is increasingly prevalent in biomedical and industrial development, capturing the interest of dental professionals and patients. Its potential to improve the accuracy and speed of dental procedures is set to revolutionize dental care. The use of AI in computer-aided design/computer-aided manufacturing (CAD/CAM) within the restorative dental and material science fields offers numerous benefits, providing a new dimension to these practices. This study aims to provide a concise overview of the implementation of AI-powered technologies in CAD/CAM restorative dental procedures and materials. A comprehensive literature search was conducted using keywords from 2000 to 2023 to obtain pertinent information. This method was implemented to guarantee a thorough investigation of the subject matter. Keywords included; "Artificial Intelligence", "Machine Learning", "Neural Networks", "Virtual Reality", "Digital Dentistry", "CAD/CAM", and "Restorative Dentistry". Artificial intelligence in digital restorative dentistry has proven to be highly beneficial in various dental CAD/CAM applications. It helps in automating and incorporating esthetic factors, occlusal schemes, and previous practitioners' CAD choices in fabricating dental restorations. AI can also predict the debonding risk of CAD/CAM restorations and the compositional effects on the mechanical properties of its materials. Continuous enhancements are being made to overcome its limitations and open new possibilities for future developments in this field.