Suppr超能文献

一种基于 DEM 模拟和实验的预测牙科树脂复合材料最大填充量的新方法。

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

机构信息

State Key Laboratory of Organic-Inorganic Composites, Beijing University of Chemical Technology, Beijing, 100029, PR China; Research Center of the Ministry of Education for High Gravity Engineering and Technology, Beijing University of Chemical Technology, Beijing, 100029, PR China.

Research Center of the Ministry of Education for High Gravity Engineering and Technology, Beijing University of Chemical Technology, Beijing, 100029, PR China.

出版信息

Dent Mater. 2020 Dec;36(12):e375-e385. doi: 10.1016/j.dental.2020.09.005. Epub 2020 Sep 24.

Abstract

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.

摘要

目的

牙科树脂复合材料中的无机填料可以提高其机械性能并降低聚合收缩。当无机填料的用量接近最大填料负载量(MFL)时,复合材料通常会达到最佳性能。本研究旨在开发一种可预测牙科树脂复合材料 MFL 的方法,以优化填料配方。

方法

首先开发了一种基于离散元法(DEM)模拟和实验的方法,用于预测单级和多级填充中球形二氧化硅颗粒的 MFL。

结果

结果表明,改性剂的存在可以提高 MFL,并且改性剂含量与 MFL 增量之间可以呈指数关系变化。与单级填充相比,添加二次填料有利于提高 MFL,并且增量会受到粒径和粒径比的影响。预测结果与实验结果吻合较好。

意义

预测结果的准确性表明 DEM 模拟作为研究 MFL 的数值实验方法具有很大的潜力,并为优化填料配方提供了一种有效的方法。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验