Optimization of the process of acylation of para-(1-methylcyclohexyl) phenol with acetic acid in the presence of the nano-catalytic system

G. Haydarli, R. Jafarov, Ch. K. Rasulov, A.R. Manafova
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Abstract

Determining the theoretical optimal conditions for the acylation of para-(1-methylcyclohexyl) phenol with acetic acid creates the basis for evaluating the prospects of this process. For the carring out the acylation process, para-(1-methylcyclohexyl) phenol (AP) and acetic acid (AcOH) were used as a feedstock. To determine the optimal conditions for the acylation reaction of AP with the help of AcOH in a pilot plant, the effects of temperature, molar ratio of initial compounds, reaction time on the yield and selectivity of the target product were studied. The study of the acylation reaction was carried out in the temperature range of 120-1600C, the reaction time was 20-50 minutes, the molar ratio of AP:AcOH was within 1:0.5÷3. To develop a regression model of the process, it is necessary to identify the functional relationship between the process parameters and use it for further process prediction. Considering that the number of experiments is m=12, and the input variables are n=3, the functional connection can be represented as a non-linear polynomial. To determine the coefficients of the equation, the S-plus 2000 Professional program was used, which allows us to automatically calculate statistical analysis data: quadratic effect coefficients, regression model coefficients and pair correlation coefficients. Applying Student's criterion, significant and insignificant coefficients of the equation were found. To test the adequacy of the model, the Fisher criterion was used, which makes it possible to prove the adequacy of the description of the response surface by regression equations.
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纳米催化体系存在下对-(1-甲基环己基)苯酚与乙酸酰化工艺的优化
确定对-(1-甲基环己基)苯酚与乙酸酰化反应的理论最佳条件,为评价该工艺的前景奠定了基础。以对-(1-甲基环己基)苯酚(AP)和乙酸(AcOH)为原料进行酰化反应。为了确定在中试装置中AcOH辅助下AP酰化反应的最佳条件,研究了反应温度、初始化合物的摩尔比、反应时间对目标产物收率和选择性的影响。酰化反应的研究在120-1600C的温度范围内进行,反应时间为20-50分钟,AP:AcOH的摩尔比在1:0.5÷3以内。为了建立工艺的回归模型,有必要确定工艺参数之间的函数关系,并将其用于进一步的工艺预测。考虑实验次数m=12,输入变量n=3,函数连接可以表示为非线性多项式。方程系数的确定采用S-plus 2000 Professional程序,该程序可自动计算统计分析数据:二次效应系数、回归模型系数和对相关系数。应用学生准则,发现方程的系数有显著性和不显著性。为了检验模型的充分性,采用Fisher准则,从而可以证明回归方程对响应面描述的充分性。
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