Suppr超能文献

使用组合计算技术预测芳香族聚苯并恶嗪的玻璃化转变温度。

Using combined computational techniques to predict the glass transition temperatures of aromatic polybenzoxazines.

机构信息

Department of Chemistry, University of Surrey, Guildford, Surrey, United Kingdom.

出版信息

PLoS One. 2013;8(1):e53367. doi: 10.1371/journal.pone.0053367. Epub 2013 Jan 10.

Abstract

The Molecular Operating Environment software (MOE) is used to construct a series of benzoxazine monomers for which a variety of parameters relating to the structures (e.g. water accessible surface area, negative van der Waals surface area, hydrophobic volume and the sum of atomic polarizabilities, etc.) are obtained and quantitative structure property relationships (QSPR) models are formulated. Three QSPR models (formulated using up to 5 descriptors) are first used to make predictions for the initiator data set (n = 9) and compared to published thermal data; in all of the QSPR models there is a high level of agreement between the actual data and the predicted data (within 0.63-1.86 K of the entire dataset). The water accessible surface area is found to be the most important descriptor in the prediction of T(g). Molecular modelling simulations of the benzoxazine polymer (minus initiator) carried out at the same time using the Materials Studio software suite provide an independent prediction of T(g). Predicted T(g) values from molecular modelling fall in the middle of the range of the experimentally determined T(g) values, indicating that the structure of the network is influenced by the nature of the initiator used. Hence both techniques can provide predictions of glass transition temperatures and provide complementary data for polymer design.

摘要

分子操作环境软件(MOE)用于构建一系列苯并恶嗪单体,获得与结构相关的各种参数(例如水可及表面积、负范德华表面积、疏水性体积和原子极化率之和等),并制定定量结构性质关系(QSPR)模型。首先使用三个 QSPR 模型(使用多达 5 个描述符)对引发剂数据集(n=9)进行预测,并与已发表的热数据进行比较;在所有的 QSPR 模型中,实际数据和预测数据之间高度一致(整个数据集的偏差在 0.63-1.86 K 内)。水可及表面积是预测 T(g)的最重要描述符。同时使用 Materials Studio 软件套件对苯并恶嗪聚合物(减去引发剂)进行分子建模模拟,提供 T(g)的独立预测。分子建模预测的 T(g)值位于实验确定的 T(g)值范围内的中间,表明网络的结构受所用引发剂的性质影响。因此,这两种技术都可以提供玻璃化转变温度的预测,并为聚合物设计提供补充数据。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/081d/3542367/970eedde6901/pone.0053367.g001.jpg

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