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使用状态方程和经验模型对芒果姜提取物中酚类物质在超临界二氧化碳中的溶解度进行建模。

Modelling solubility of phenolics of mango ginger extract in supercritical carbon dioxide using equation of state and empirical models.

作者信息

Murthy Thirupathihalli Pandurangappa Krishna, Manohar Balaraman

机构信息

Department of Biotechnology, MS Ramaiah Institute of Technology, Bangalore, 560054 India.

Department of Food Engineering, CSIR-Central Food Technological Research Institute, Mysore, 570020 India.

出版信息

J Food Sci Technol. 2015 Sep;52(9):5557-67. doi: 10.1007/s13197-014-1667-1. Epub 2014 Dec 11.

Abstract

Solubility of phenolics of mango ginger extract in supercritical carbon dioxide was studied at 40-60 °C and 100-350 bar. Critical temperature, critical pressure and critical volume of caffeic acid, the principal component of the extract were calculated using group contribution methods and compared with the values obtained by CHEMDRAW®. Vapor pressure of caffeic acid was predicted by Reidel method. Solubility prediction in supercritical carbon dioxide was studied using two different equation of states (EOS) models and eight empirical models. Peng-Robinson EOS predicted the solubility very well with average deviation of 0.68 % from the experimental solubility. Empirical equations based on the simple error minimization using non-linear regression method which do not require complex physiochemical properties was also found suitable to predict the solubility at different extraction conditions. Jouyban et al. model showed very less deviation (2.25 %) for predicted solubility values from the experiment.

摘要

在40 - 60°C和100 - 350巴的条件下,研究了芒果姜提取物中酚类物质在超临界二氧化碳中的溶解度。使用基团贡献法计算了提取物主要成分咖啡酸的临界温度、临界压力和临界体积,并与通过CHEMDRAW®获得的值进行了比较。采用赖德法预测了咖啡酸的蒸气压。使用两种不同的状态方程(EOS)模型和八个经验模型研究了在超临界二氧化碳中的溶解度预测。彭 - 罗宾逊状态方程对溶解度的预测效果很好,与实验溶解度的平均偏差为0.68%。还发现基于使用非线性回归方法进行简单误差最小化的经验方程,不需要复杂的物理化学性质,适合预测不同萃取条件下的溶解度。乔伊班等人的模型预测溶解度值与实验值的偏差非常小(2.25%)。

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