Optimization of Cu oxide catalyst for methanol synthesis under high CO2 partial pressure using combinatorial tools

被引：15

作者：

Omata, K ^{[1
]}

Hashimoto, M ^{[1
]}

Watanabe, Y ^{[1
]}

Umegaki, T ^{[1
]}

Wagatsuma, S ^{[1
]}

Ishiguro, G ^{[1
]}

Yamada, M ^{[1
]}

机构：

[1] Tohoku Univ, Grad Sch Engn, Dept Appl Chem, Sendai, Miyagi 9808579, Japan

来源：

APPLIED CATALYSIS A-GENERAL | 2004年 / 262卷 / 02期

基金：

日本学术振兴会;

关键词：

methanol synthesis; combinatorial catalysis; artificial neural network; high-throughput screening;

D O I：

10.1016/j.apcata.2003.11.028

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：

In one-stage dimethyl ether synthesis from syngas, a hybrid catalyst with Cu-based oxide and solid acid is used. An active catalyst for methanol formation with high resistant to carbon dioxide is essential for high efficiency of the process. Besides Cu, Zn and Al, four promising additives were selected and the composition of the seven elements was optimized. Combinatorial tools with high-throughput screening under pressure using 96 well microplates and a data mining technique was used to discover a new catalyst with high tolerance for carbon dioxide. The activity of the catalyst optimized under 30% CO2 (Cu0.459Zn0.184Al0.175Cr0.000B0.181Zr0.001Ga0.000O1.179) was 270g-MeOH/(kg-cat. h) at 1 MPa, 498 K, and H-2/CO/CO2/N-2 = 43/22/30/5, which is much higher than 190g-MeOH/(kg-cat. h) of the catalyst optimized under 5% CO2 (Cu0.472Zn0.t24Al0.165Cr0.000B0.207Zr0.026Ga0.006O1.215). (C) 2003 Elsevier B.V. All rights reserved.

引用

页码：207 / 214

页数：8

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