State Key Laboratory of Organic-Inorganic Composites, Beijing University of Chemical Technology, Beijing, 100029, China; Research Center of the Ministry of Education for High Gravity Engineering and Technology, Beijing University of Chemical Technology, Beijing, 100029, China.
School of Automation, China University of Geosciences, Wuhan 430074, China.
Dent Mater. 2021 Dec;37(12):1806-1818. doi: 10.1016/j.dental.2021.09.010. Epub 2021 Sep 24.
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.
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.
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.
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.
本研究旨在开发一种数学模型，以高效预测不同填料配方在牙科树脂复合材料（DRC）中的堆积密度，并研究 DRC 在最大填料负载（MFL）下的性能，从而为设计 DRC 中的填料配方以获得优异性能提供有效指导。
使用离散元模型（DEM）模拟生成的堆积密度数据重新推导三参数模型的参数，并引入改性剂效应来修正三参数模型。选择 10 种填料配方的 DRC 进行 MFL 下性能测试。通过三参数模型计算 DRC 中二元和三元混合物的堆积密度，以探索复合材料堆积的规律。
预测的堆积密度通过模拟和实验结果得到验证，预测误差在 1.40 体积%以内。优化填料组成以获得更高的堆积密度有利于提高 DRC 的力学性能和降低聚合收缩。在二元混合物中，当小粒径填料的体积分数为 0.35-0.45 时，堆积密度最大，且随着粒径比的减小而增加。在三元混合物中，当大粒径和小粒径填料的体积分数分别在 0.5-0.75 和 0.15-0.4 范围内时，堆积密度可达到最大值。
修正后的三参数模型可以为 DRC 的多级填料配方设计提供有效方法，从而提高材料的性能。
