Artificial Neural Network Prediction and Mechanism Analysis for Migration of Environmental Contaminant Cyclic Organosiloxane Oligomer from Silicone Rubber
Artificial Neural Network Prediction and Mechanism Analysis for Migration of Environmental Contaminant Cyclic Organosiloxane Oligomer from Silicone Rubber
复制标题
硅橡胶环境污染物环状有机硅氧烷低聚物迁移的人工神经网络预测及机理分析
DOI：
10.1021/acs.iecr.9b01320
复制
发表时间：
2019-06-26
影响因子：
4.2
通讯作者：
Wang, Xiujuan
中科院分区：
文献类型：
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作者：
Thu, Aung Myat;Song, Meng;Wang, Xiujuan
环状有机硅氧烷低聚物分子从硅橡胶到食品模拟物中的迁移测试作为三个因素的函数进行：温度、时间和食品模拟物类型（即，正己烷、正庚烷和乙醇）。提出了一种反向传播人工神经网络（BP-ANN）来研究偏移特性，平均预测精度为0.997。人工神经网络的分析表明，高温和正己烷环境加速了硅橡胶中环状有机硅氧烷低聚物分子的迁移。采用分子动力学模拟从分子水平上阐明了迁移机理。结果表明，高温和正己烷条件导致体系的相互作用能、自由体积分数和扩散系数较高，差溶度参数较低，加速了分子转移过程，对材料的安全性构成威胁。这些基础研究提供了一个全面的联合国。
Migration testing of cyclic organosiloxane oligomer molecules from silicone rubber into food simulants was performed as a function of three factors: temperature, time, and food simulant type (i.e., n-hexane, n-heptane, and ethyl alcohol). A back-propagation artificial neural network (BP-ANN) was proposed to study the migration properties with an average prediction accuracy of 0.997. The analysis of the ANN indicated that high-temperature and n-hexane environments accelerate the migration of cyclic organosiloxane oligomer molecules from silicone rubber. A molecular dynamics simulation was employed to illustrate the migration mechanism at the molecular level. The results indicated that the high-temperature and n-hexane condition led to a high interaction energy, fractional free volume, and diffusion coefficient and a low difference solubility parameter of the system, which accelerate the molecules transfer process and threaten the safety of the materials. These fundamental studies provide a comprehensive un...