Statistical design and modeling of the process of methane partial oxidation using V-MCM-41 catalysts and the prediction of the formaldehyde production

被引:35
作者
Du, Guoan
Yang, Yanhui
Qiu, Wei
Lim, Sangyun
Pfefferle, Lisa
Haller, Gary L.
机构
[1] Yale Univ, Dept Chem Engn, New Haven, CT 06520 USA
[2] Nanyang Technol Univ, Sch Chem & Biomed Engn, Singapore 639798, Singapore
[3] Yale Univ, Dept Stat, New Haven, CT 06520 USA
基金
美国国家航空航天局;
关键词
design of experiment; multiple regression model; regression; V-MCM-41; partial oxidation of methane;
D O I
10.1016/j.apcata.2006.06.037
中图分类号
O64 [物理化学(理论化学)、化学物理学];
学科分类号
070304 ; 081704 ;
摘要
As a simplified approach to optimize the production of formaldehyde from partial oxidation of methane, this paper illustrates the application of statistical multivariate analysis and prediction through a multi-regression model, as well as the optimization of the processing parameters in the complex reaction process. This approach is advantageous, especially when experimental evaluation and optimization of a process is time consuming and expensive. By carrying out a finite number of experiments, statistical modeling in this work shows reasonable good prediction ability in terms of methane conversion, formaldehyde selectivity, and space time yield (STYHCHO). Moreover, not only are the synergistic effects between reaction parameters revealed, but also a comprehensive understanding of the whole production process over variation of the all reaction parameters (within the phase space represented by the experimental grid) are allowed. (c) 2006 Elsevier B.V. All rights reserved.
引用
收藏
页码:1 / 13
页数:13
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