Chrome Extension
WeChat Mini Program
Use on ChatGLM

Denture Base Poly(methyl Methacrylate) Reinforced with SrTiO3/Y2O3: Structural, Morphological and Mechanical Analysis

POLYMER COMPOSITES(2025)

Univ Belgrade | North Carolina Cent Univ

Cited 0|Views4
Abstract
This study presented the use of SrTiO3/Y2O3 nanoparticles for the reinforcement of dental poly(methyl methacrylate) (PMMA) to enhance its mechanical properties important for everyday use of denture base materials. The average crystallite size of prepared nanoparticles was 19.9 nm. The influence of 0.5, 1.0, and 1.5 wt% SrTiO3/Y2O3 loading on absorbed impact energy, microhardness and tensile properties was investigated. Scanning electron microscopy of the composite fracture surface revealed multiple toughening mechanisms, with agglomerates directly included in the crack pinning, indicating improvement in mechanical performance. Dynamic mechanical analysis proved that agglomerates improved the elastic behavior of PMMA and confirmed the absence of a residual monomer. After the incorporation of SrTiO3/Y2O3, the mechanical properties of composites showed a high increase compared to neat PMMA. The optimal concentration of nanoparticles was 1 wt%, for which the microhardness, modulus of elasticity, and absorbed impact energy were higher by 218.4%, 65.8% and 135.6%, respectively. With such a high increase, this research showed that SrTiO3/Y2O3 represents an efficient filler which use does not have to be limited to dental materials. Highlights SrTiO3/Y2O3 hybrid nanoparticles were prepared. PMMA-SrTiO3/Y2O3 composite showed increase in impact resistance up to 135.4%. Elastic behavior of PMMA was improved. With 1 wt% of SrTiO3/Y2O3, microhardness increased by 218.4%.
More
Translated text
Key words
impact resistance,microhardness,polymer composite,SrTiO3/Y2O3
求助PDF
上传PDF
Bibtex
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
  • Pretraining has recently greatly promoted the development of natural language processing (NLP)
  • We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
  • We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
  • The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
  • Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Upload PDF to Generate Summary
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper

要点】:本研究利用SrTiO3/Y2O3纳米颗粒增强聚甲基丙烯酸甲酯(PMMA),显著提高了其机械性能,创新点在于使用了新型纳米颗粒并确定了最佳浓度为1 wt%。

方法】:通过在PMMA中添加不同比例(0.5、1.0和1.5 wt%)的SrTiO3/Y2O3纳米颗粒,并使用扫描电镜和动态机械分析等手段评估了复合材料的机械性能。

实验】:在实验中,作者制备了平均晶粒大小为19.9 nm的纳米颗粒,并测试了不同浓度下PMMA-SrTiO3/Y2O3复合材料的吸收冲击能量、微硬度和拉伸性能。实验结果表明,在1 wt%纳米颗粒浓度下,复合材料的微硬度、弹性模量和吸收冲击能量分别提高了218.4%、65.8%和135.6%。实验使用的数据集为作者自行制备的PMMA-SrTiO3/Y2O3复合材料。