Catalyst development for methanol synthesis using parallel reactors for high-throughput screening based on a 96 well microplate system

被引:13
|
作者
Omata, K [1 ]
Watanabe, Y [1 ]
Umegaki, T [1 ]
Hashimoto, M [1 ]
Yamada, M [1 ]
机构
[1] Tohoku Univ, Grad Sch Engn, Dept Appl Chem, Aoba Ku, Sendai, Miyagi 9808579, Japan
关键词
combinatorial chemistry; high-throughput screening; genetic algorithm; neural network; 96 well microplate; methanol synthesis;
D O I
10.1627/jpi.46.328
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
combinatorial approach is widely used for homogeneous and heterogeneous catalyst development. The main key technologies are "combinatorial chemistry (CC)" for material preparation and "high-throughput screening (HTS)" for rapid assay using automated and/or robotic equipment. A HTS reactor with 96 parallel lines was designed and manufactured to optimize the Cu-Zn catalyst for methanol synthesis. A neural network (NN) was constructed from the "catalyst composition-activity" dataset obtained by the HTS reactor. The catalyst composition was optimized by a genetic algorithm combined with the trained NN. Active Cu-Zn catalysts for methanol synthesis under CO2 rich syngas were discovered by these combinatorial tools.
引用
收藏
页码:328 / 334
页数:7
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