Spray-drying-assisted fabrication of CaF2/SiO2 nanoclusters for dental restorative composites.

OBJECTIVE: The objective of this study is to develop novel CaF2/SiO2 nanoclusters (NCs) fillers, which can endow the dental resin composites (DRCs) with excellent mechanical properties, stable and sustained fluoride ion release, and good antibacterial activity. METHODS: The CaF2/SiO2 NCs were efficiently fabricated by assembling CaF2/SiO2 nanoparticles (NPs) as building blocks with a spray-drying technology. CaF2/SiO2 NCs with different SiO2 coating amounts (20 wt%, 50 wt% and 80 wt%) were incorporated into the DRCs at the filler content of 55 wt% for the measurement of mechanical properties including flexural strength, flexural modulus, compressive strength, and hardness. The effect of the filling amount of CaF2/50SiO2 NCs (50 represents 50 wt% SiO2 coating amount) in the DRCs was investigated, while CaF2/50SiO2 NPs were adopted as comparison group. The fluoride ion release and antibacterial activity of the DRCs with the optimal mechanical performances were evaluated. Furthermore, the statistical analyses were performed for mechanical properties. RESULTS: Spherical CaF2/50SiO2 NCs with an average size of 2.4 µm were obtained at the feed rate of 7.4 mL/min and the CaF2/50SiO2 NPs solid content of 2 wt% in the suspension. The optimum comprehensive performances of the DRCs can be achieved by filling 55 wt% CaF2/50SiO2 NCs. Compared with CaF2/50SiO2 NPs, the filling amount of CaF2/50SiO2 NCs was increased by 5 wt% (50-55 wt%), and under the same filling amount of 50 wt%, the flexural strength, flexural modulus, compressive strength, and hardness of the DRCs containing CaF2/50SiO2 NCs were improved by 9.8%, 17.7%, 7.5% and 69.8%, respectively. Furthermore, the DRCs filled with 50 wt% CaF2/50SiO2 NCs exhibited more cumulative F-release by 126% and more stable F-release rate than the counterpart filled with 50 wt% CaF2/50SiO2 NPs after immersed for 1800 h. And 55 wt% CaF2/50SiO2 NCs filled DRCs could inhibit the growth of S. mutans, reaching an antibacterial ratio of 93%. SIGNIFICANCE: The spray-dried CaF2/50SiO2 NCs are promising fillers for the development of high-performance multifunctional DRCs.

Mechanical behavior and reinforcement mechanism of nanoparticle cluster fillers in dental resin composites: Simulation and experimental study.

OBJECTIVES: In dental resin composites (DRCs), the structure of fillers has a great impact on the mechanical behavior. The purpose of this study is to gain an in-depth understanding of the reinforcement mechanism and mechanical behavior of DRCs with nanoparticle clusters (NCs) fillers, thereby providing a guidance for the optimal design of filler structures for DRCs. METHODS: This work pioneers the use of discrete element method (DEM) simulations combined with experiments to study the mechanical behavior and reinforcement mechanism of DRCs with NCs fillers. RESULTS: The uniaxial compressive strength (UCS) of NCs-reinforced DRCs have an improvement of 9.58 % and 15.02 % in comparison with nanoparticles (NPs) and microparticles (MPs), respectively, because of the ability of NCs to deflect cracks and absorb stress through gradual fracturing. By using NCs and NPs as co-fillers, the internal defects of DRCs can be reduced, resulting in a further improvement of UCS of DRCs by 6.21 %. Furthermore, the mechanical properties of DRCs can be effectively improved by increasing the strength of NCs or reducing the size of NCs. SIGNIFICANCE: This study deepens the understanding of relationship between filler structure and mechanical behavior in DRCs at the mesoscale and provides an avenue for the application of DEM simulations in composite materials.

Efficient prediction of the packing density of inorganic fillers in dental resin composites for excellent properties.

OBJECTIVE: The purpose of this study is to develop a mathematical model for efficient prediction of the packing density of different filler formulations in dental resin composites (DRCs), and to study properties of DRCs at the maximum filler loading (MFL), thereby providing an effective guidance for the design of filler formulations in DRCs to obtain excellent properties. METHODS: The packing density data generated by discrete element model (DEM) simulation were used to re-derive the parameters of 3-parameter model. The modifier effect was also induced to modify the 3-parameter model. DRCs with 10 filler formulations were selected to test properties at the MFL. The packing densities of binary and ternary mixes in DRCs were calculated by 3-parameter model to explore the regularity of composite packing. RESULTS: The predicted packing density was validated by simulation and experimental results, and the prediction error is within 1.40 vol%. The optimization of filler compositions to obtain a higher packing density is beneficial to enhancing the mechanical properties and reducing the polymerization shrinkage of DRCs. In binary mixes, the maximum packing density occurs when the volume fraction of small fillers is 0.35-0.45, and becomes higher with the reduction of particle size ratio. In ternary mixes, the packing density can reach the maximum value when the volume fractions of large and small fillers are in the 0.5-0.75 and 0.15-0.4 ranges, respectively. SIGNIFICANCE: The modified 3-parameter model can provide an effective method to design the multi-level filler formulations of DRCs, thereby improving the performance of the materials.

Antibacterial activity and reinforcing effect of SiO2-ZnO complex cluster fillers for dental resin composites.

The accumulation of bacteria at the margin of dental resin composites is the main reason for secondary caries, which may further cause failure of prosthodontics. Therefore, antibacterial activity is highly required. However, the addition of antibacterial agents or fillers weakens the mechanical or aesthetic properties of composites. In this work, regular-shaped SiO2-ZnO complex clusters (CCs) constructed by spray-drying technology can enhance the antibacterial activity while maintaining the mechanical and aesthetic properties of dental resin composites. The results show that the regular shape and closely packed structure of nanoparticle clusters were not corrupted by the introduction of ZnO particles. As compared to resin composites filled with SiO2 nanoparticle clusters, the comprehensive performances of composites containing SiO2-ZnO CCs were further improved, and the composites filled with 70 wt% Si66Zn4 (CCs composed of 66/70 SiO2 and 4/70 of ZnO) exhibited superior antibacterial capability (antibacterial ratio >99.9%) and acceptable depth of cure, degree of conversion, and biocompatibility. The cooperation of different fillers is highly essential for resin composites to achieve enhanced multifunctional performance.

A new method for predicting the maximum filler loading of dental resin composites based on DEM simulations and experiments.

OBJECTIVE: The inorganic fillers in dental resin composites can enhance their mechanical properties and reduce polymerization shrinkage. When the usage amount of inorganic fillers is closed to maximum filler loading (MFL), the composites will usually achieve optimal performances. This study aims to develop a method that can predict the MFL of dental resin composites for the optimization of filler formulations. METHODS: A method based on discrete element method (DEM) simulations and experiments was firstly developed to predict the MFL of spherical silica particles for single-level and multi-level filling. RESULTS: The results indicate that the presence of modifier can increase the MFL, and the MFL increment can be exponentially changed with the content of the modifier. Compared with the single-level filling, the addition of secondary fillers is beneficial to increase the MFL, and the increment can be affected by the particle size and size ratio. The prediction results show a good agreement with the experiment results. SIGNIFICANCE: The accuracy of prediction results indicates a great potential of DEM simulations as a numerical experimental method in studying the MFL, and provides an effective method for the optimization of filler formulations.