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首页> 外文期刊>Chemical Engineering Research & Design: Transactions of the Institution of Chemical Engineers >Temperature dependent surface tension estimation using COSMO-RS sigma moments
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Temperature dependent surface tension estimation using COSMO-RS sigma moments

机译：温度相关的表面张力的评估使用COSMO-RSσ的时刻

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In this work, a nonlinear multivariate QSPR model based on the COSMO-RS sigma moments was presented for the estimation of the temperature dependent surface tension of various organic compounds in wide surface tension (0.07-45.08 mN m(-1)) and temperature (283-373 K) range. 1500 data points were used to establish, validate and test the model. An artificial neural network was developed, optimized and used as regression model. The prediction power of the new model was validated with an external data set, with a squared correlation coefficient of R-2 =0.963 and a mean absolute error of MAE =0.81 mN m(-1). The factor sensitivity and importance analyses show that all of the proposed five COSMO-RS sigma moments and the temperature are significant input variables of the ANN model and the kind of skewness of the sigma-profile, the electrostatic interaction energy and the hydrogen bonding acceptor function are the most sensitive and important molecular descriptors used in the new nonlinear multivariate QSPR model. (C) 2014 The Institution of Chemical Engineers. Published by Elsevier B.V. All rights reserved.
机译：在这项工作中,非线性多元分子结构模型提出了基于COSMO-RS西格玛的时刻估计的温度依赖性各种有机化合物的表面张力广泛的表面张力(0.07 - -45.08 mN m (1))温度范围(283 - 373 K)。被用于建立、验证和测试吗模型。开发、优化和作为回归模型。验证与外部数据集,平方相关系数r2 = 0.963平均绝对误差美= 0.81 mN m(1)。因素敏感性和重要性分析显示所有的提议五COSMO-RSσ时刻和温度输入非常重要ANN模型的变量和的偏态的sigma-profile静电相互作用能和氢键受体功能是最敏感的重要的分子描述符中使用新的非线性多变量模型部分。化学工程师学会。爱思唯尔帐面价值保留所有权利。

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