CAD-CAM resin composites: Effective components for further development.

Objective: This paper summarizes the effective components of computer-aided design and computer-aided manufacturing (CAD-CAM) resin composites that contribute to achieving greater mechanical properties and further development.

Methods: In silico multi-scale analysis, in silico nonlinear dynamic finite element analysis (FEA), and artificial intelligence (AI) were used to explore the effective components of CAD-CAM resin composites. The effects of the filler diameter and silane coupling ratio on the mechanical properties of CAD-CAM resin composites have been clarified through multi-scale analysis.

In vitro analysis of durability of S-PRG filler-containing composite crowns for primary molar restoration.

Objective: To evaluate the reliability, maximum principal stress, shear stress, and crack initiation of a computer-aided design/computer-aided manufacturing (CAD/CAM) resin composite (RC) incorporating surface pre-reacted glass (S-PRG) filler for primary molar teeth.

Methods: Mandibular primary molar crowns fabricated by experimental (EB) or commercially available CAD/CAM RCs (HC) were prepared and cemented to a resinous abutment tooth using an adhesive resin cement (Cem) or a conventional glass-ionomer cement (CX). These specimens were subjected to a single compressive test (n = 5/each) and the step-stress accelerated life testing (SSALT) (n = 12/each).

Development of artificial intelligence model for supporting implant drilling protocol decision making.

Purpose This study aimed to develop an artificial intelligence (AI) model to support the determination of an appropriate implant drilling protocol using cone-beam computed tomography (CBCT) images.Methods Anonymized CBCT images were obtained from 60 patients. For each case, after implant placement, images of the bone regions at the implant site were extracted from 20 slices of CBCT images.

Color matching ability of resin composites incorporating supra-nano spherical filler producing structural color.

Objective: The aim of this study was to evaluate the optical properties of supra-nano spherical fillers with different diameters and the color matching ability of resin composites (RC) incorporating these fillers.

Methods: Two types of SiO-ZrO nano fillers with different diameters (150nm and 260nm) were used. The size distribution of each filler was measured and filler morphology was observed.

Multi-scale analysis of the influence of filler shapes on the mechanical performance of resin composites using high resolution nano-CT images.

Objective: The aim of this study was to investigate the criteria for predicting the fracture initiation of resin composites (RCs) at the micro-scale and assess the influence of filler shapes on the flexural properties of RCs by combining nano-CT imaging and in silico multi-scale analysis.

Methods: Experimental RCs composed of irregular-shaped (IS) silica filler (31.2 vol%/50.

In vitro/in silico investigation of failure criteria to predict flexural strength of composite resins.

The aim of this study was to investigate a failure criterion to predict flexural strengths of composite resins (CR) by three-dimensional finite element analysis (3D-FEA). Models of flexural strength for test specimens of CR and rods comprising a three-point loading were designed. Calculation of Young's moduli and Poisson's ratios of CR were conducted using a modified McGee-McCullough model.

Multi-scale analysis of the effect of nano-filler particle diameter on the physical properties of CAD/CAM composite resin blocks.

The objective of this study was to assess the effect of silica nano-filler particle diameters in a computer-aided design/manufacturing (CAD/CAM) composite resin (CR) block on physical properties at the multi-scale in silico. CAD/CAM CR blocks were modeled, consisting of silica nano-filler particles (20, 40, 60, 80, and 100 nm) and matrix (Bis-GMA/TEGDMA), with filler volume contents of 55.161%.