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HDGEBA/PAMS 混合热固性材料形态发展机制:蒙特卡罗模拟与激光扫描共聚焦显微镜研究

Mechanism of Morphology Development in HDGEBA/PAMS Hybrid Thermosets: Monte Carlo Simulation and LSCM Study.

作者信息

González María G, Pozuelo Javier, Cabanelas Juan C, Serrano María B, Baselga Juan

机构信息

Department of Materials Science and Engineering and Chemical Engineering, IAAB, University Carlos III of Madrid, 28911 Leganés, Spain.

出版信息

Polymers (Basel). 2022 Dec 8;14(24):5375. doi: 10.3390/polym14245375.

Abstract

Reactive combinations of aliphatic epoxy resins and functional polysiloxanes form a class of hybrid thermosetting materials with properties that may come from both the organic and the inorganic phases. The two typically immiscible phases form a suspension whose morphology, composition, and thermal properties vary with curing time. The aim of this research was to elucidate the mechanism by which morphology changed with time and to simulate it through Metropolis-Monte Carlo. The selected system was hydrogenated epoxy (HDGEBA) and a synthetic polyaminosiloxane (PAMS). It was studied by DSC, FTnIR, gel point, viscometry, and in-situ laser scanning confocal microscopy. A mechanism for morphology generation was proposed and simulated, exploring a wide range of values of the "a priori" relevant variables. The essential features were captured by simulations with a reasonable agreement with experimental data. However, the complete process was more complex than the geometrical approach of the simulation. The main deviations that were found and qualitatively explained are: (i) the induction period on the rate of coalescence, and (ii) PAMS-rich domain average size increases faster than predictions.

摘要

脂肪族环氧树脂与功能性聚硅氧烷的反应性组合形成了一类杂化热固性材料,其性能可能源于有机相和无机相。这两个通常不互溶的相形成一种悬浮液,其形态、组成和热性能随固化时间而变化。本研究的目的是阐明形态随时间变化的机制,并通过 metropolis - 蒙特卡洛方法对其进行模拟。所选体系为氢化环氧树脂(HDGEBA)和一种合成聚氨基硅氧烷(PAMS)。通过差示扫描量热法(DSC)、傅里叶变换红外光谱法(FTnIR)、凝胶点、粘度测定以及原位激光扫描共聚焦显微镜对其进行了研究。提出并模拟了形态生成的机制,探索了“先验”相关变量的广泛取值范围。模拟捕捉到了基本特征,与实验数据有合理的一致性。然而,完整的过程比模拟的几何方法更为复杂。发现并定性解释的主要偏差有:(i)聚并速率的诱导期,以及(ii)富含PAMS的区域平均尺寸增长速度比预测的快。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/598b/9788219/1f5c3ce53247/polymers-14-05375-g001.jpg

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