详细信息

两种特性的涂料类有机混合物闪点模型预测  ( EI收录)  

Flash point prediction of two coating organic mixtures with different characteristics

文献类型:期刊文献

中文题名:两种特性的涂料类有机混合物闪点模型预测

英文题名:Flash point prediction of two coating organic mixtures with different characteristics

作者:陆强[1];霍欣[2];任凯玥[1];边嘉雯[1];吴欣荣[1];沈晓波[1]

机构:[1]华东理工大学资源与环境工程学院,上海200237;[2]中国科学技术大学火灾科学国家重点实验室,安徽合肥230026

年份:2021

卷号:35

期号:5

起止页码:798

中文期刊名:高校化学工程学报

外文期刊名:Journal of Chemical Engineering of Chinese Universities

收录:CSTPCD;;EI(收录号:20214611143558);Scopus;北大核心:【北大核心2020】;CSCD:【CSCD2021_2022】;

基金:国家自然科学基金(22078095);上海市级大学生创新创业项目(S19100-10251)。

语种:中文

中文关键词:涂料;混合溶剂;闪点;UNIFAC;超额Gibbs自由能

外文关键词:coating;solvent mixture;flash point;UNIFAC;excess Gibbs free energy

摘要:为了简化与扩展热力学推导的闪点预测模型,提出由UNIFAC活度系数模型与二元汽液平衡的实验得出二元互溶溶液的超额Gibbs自由能,评判区分溶液的理想与非理想性的方法。选择实用的2种涂料类有机混合物配方成分的二元与三元混合溶液,实验研究闪点变化规律,并与Raoult定律、活度系数模型(Wilson、NRTL、UNIQUAC)和UNIFAC模型的预测值比较。结果表明:理想性物系可直接由Raoult定律预测闪点(平均绝对误差AAD<1.0℃);而非理想性物系适宜用3种活度系数模型(AAD<2.5℃)或UNIFAC模型(AAD<1.0℃)预测闪点。可为涂料类有机混合物的火灾爆炸危险性控制提供可靠闪点预测数据。
In order to simplify and extend thermodynamic flash point prediction models, UNIFAC model and binary vapor-liquid equilibrium experimental data were used to evaluate nonideal behaviors of mixtures through excess Gibbs free energy. The ternary systems and their corresponding binary pairs prepared with the organic compounds(p-xylene + butyl acetate + n-butanol and p-xylene + butyl acetate + cyclohexanone) of two practical coating formulations were selected to study flash point variation, and the measured flash point data were compared with the predictions based on Raoult’s law, activity coefficient models(Wilson, NRTL,UNIQUAC) and UNIFAC model. The results reveal that Raoult’s law can be directly applied to the flash point ure range 30-750 mm mercury [J].systems with average absolute deviation(AAD) less than 1.0 ℃. However, for the nonideal systems, three activity coefficient models or UNIFAC model are acceptable for AAD being less than 2.5 ℃ and 1.0 ℃, respectively. This study provides reliable flash point prediction data for fire and explosion prevention of coating organic mixtures.

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