论文信息 - Design of CO2 hydrogenation catalyst by an artificial neural network

Design of CO2 hydrogenation catalyst by an artificial neural network

An artificial neural network (ANN) is firstly applied to CO2 hydrogenation catalyst design. CO2 catalytic hydrogenation activity is represented as a function of the catalyst composition and reaction condition. After training, the network can predict CO2 catalytic hydrogenation activity and design CO2 hydrogenation catalyst successfully. The estimated results are in good agreement with the experimentally observed ones.

[1] F. Solymosi,et al. Hydrogenation of CO2 to CH4 over alumina-supported noble metals , 1980 .

[2] Yan Liu,et al. Study of bimetallic Cu–Ni/γ-Al2O3 catalysts for carbon dioxide hydrogenation , 1999 .

[3] D. Trimm. Design of industrial catalysts , 1980 .

[4] T. Fujitani,et al. Development of an active Ga2O3 supported palladium catalyst for the synthesis of methanol from carbon dioxide and hydrogen , 1995 .

[5] Zhang Suo,et al. Characterization of TiO2-, ZrO2- and Al2O3-supported iron catalysts as used for CO2 hydrogenation , 1997 .