Screening Using Artificial Neural Network of Additives for Cu-Zn Oxide Catalyst for Methanol Synthesis from Syngas     Methanol synthesis  Neural network  Physicochemical property       font style='font-size:12px;'> 2009/7/24

The activity of Cu-Zn oxide catalysts for methanol synthesis from syngas varies depending on the additives to the oxide, and optimum composition is sensitive to the reaction conditions. An artificial ...

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Development of a Co-MgO Catalyst for High-pressure Dry Reforming of Methane Based on Design of Experiment, Artificial Neural Network and Grid Search     Methane dry reforming  Combinatorial catalysis  Design of experiment       font style='font-size:12px;'> 2009/7/24

Dry reforming of methane is a potentially important process to convert the greenhouse gases carbon dioxide and methane simultaneously to syngas (CO + H2). The most serious problem with the dry reform...

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Optimization of Cu-based Oxide Catalyst for Methanol Synthesis Using a Neural Network Trained by Design of Experiment     Combinatorial chemistry  High-throughput screening  Neural network       font style='font-size:12px;'> 2009/7/23

Cu-Zn oxide catalyst for methanol synthesis was optimized using an activity map by neural network method. The catalyst composition was determined randomly and the training data were measured in a hig...

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Optimization of Cu-based Oxide Catalyst for Methanol Synthesis by the Activity Map Envelope Derived from a Neural Network     Combinatorial chemistry  High-throughput screening  Genetic algorithm       font style='font-size:12px;'> 2009/7/23

The combinatorial approach is a successful tool for material development and for heterogeneous catalyst development. Combinatorial tools were developed consisting of a high-throughput screening react...

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