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Conversion of methanol to light olefins on SAPO-34 kinetic modeling and reactor design.

机译:根据SAPO-34动力学模型和反应器设计,将甲醇转化为轻质烯烃。

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In this work, the reaction scheme of the MTO process was written in terms of elementary steps and generated by means of a computer algorithm characterizing the various species by vectors and Boolean relation matrices. The number of rate parameters is very large. To reduce this number the rate parameters related to the steps on the acid sites of the catalyst were modeled in terms of transition state theory and statistical thermodynamics. Use was made of the single event concept to account for the effect of structure of reactant and activated complex on the frequency factor of the rate coefficient of an elementary step. The Evans-Polanyi relation was also utilized to account for the effect of the structure on the change in enthalpy. The structure was determined by means of quantum chemical software.; The number of rate parameters of the complete reaction scheme to be determined from experimental data is thus reduced from 726 to 30. Their values were obtained from the experimental data of Abraha by means of a genetic algorithm involving the Levenberg-Marquardt algorithm and combined with sequential quadratic programming. The retained model yields an excellent fit of the experimental data. All the parameters satisfy the statistical tests as well as the rules of carbenium ion chemistry. The kinetic model also reproduces the experimental data of Marchi and Froment, also obtained on SAPO-34. Another set of their data was used to introduce the deactivation of the catalyst into the kinetic equations.; This detailed kinetic model was used to investigate the influence of the operating conditions on the product distribution in a multi-bed adiabatic reactor with plug flow. It was further inserted into riser and fluidized bed reactor models to study the conceptual design of an MTO reactor, accounting for the strong exothermicity of the process. Multi-bed adiabatic and fluidized bed technologies show good potential for the industrial process for the conversion of methanol into olefins.
机译:在这项工作中,MTO过程的反应方案是按照基本步骤编写的,并通过计算机算法生成,该算法通过矢量和布尔关系矩阵表征各种物种。速率参数的数量非常大。为了减少该数目,根据过渡态理论和统计热力学对与催化剂的酸性位点上的步骤有关的速率参数进行建模。使用单事件概念来解释反应物和活化的配合物的结构对基本步骤速率系数的频率因子的影响。 Evans-Polanyi关系也被用来说明结构对焓变的影响。结构是通过量子化学软件确定的。因此,由实验数据确定的完整反应方案的速率参数的数量从726个减少到30个。它们的值是通过涉及Levenberg-Marquardt算法的遗传算法并结合顺序从Abraha的实验数据中获得的二次编程。保留的模型可以很好地拟合实验数据。所有参数均满足统计检验以及碳正离子化学规则。动力学模型还再现了也在SAPO-34上获得的Marchi和Froment的实验数据。他们的另一组数据被用来将催化剂的失活引入动力学方程。该详细的动力学模型用于研究操作条件对带塞流的多床绝热反应器中产物分布的影响。进一步将其插入提升管和流化床反应器模型中,以研究MTO反应器的概念设计,这说明了该过程的强烈放热性。多床绝热和流化床技术对于将甲醇转化为烯烃的工业过程显示出良好的潜力。

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