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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.
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页码:328 / 334
页数:7
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