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http://dx.doi.org/10.7464/ksct.2022.28.3.218

Optimization for Ammonia Decomposition over Ruthenium Alumina Catalyst Coated on Metallic Monolith Using Response Surface Methodology  

Choi, Jae Hyung (Green Materials & Process R&D Group, Korea Institute of Industrial Technology)
Lee, Sung-Chan (Green Materials & Process R&D Group, Korea Institute of Industrial Technology)
Lee, Junhyeok (Green Materials & Process R&D Group, Korea Institute of Industrial Technology)
Kim, Gyeong-Min (Green Materials & Process R&D Group, Korea Institute of Industrial Technology)
Lim, Dong-Ha (Green Materials & Process R&D Group, Korea Institute of Industrial Technology)
Publication Information
Clean Technology / v.28, no.3, 2022 , pp. 218-226 More about this Journal
Abstract
As a result of the recent social transformation towards a hydrogen economy and carbon-neutrality, the demands for hydrogen energy have been increasing rapidly worldwide. As such, eco-friendly hydrogen production technologies that do not produce carbon dioxide (CO2) emissions are being focused on. Among them, ammonia (NH3) is an economical hydrogen carrier that can easily produce hydrogen (H2). In this study, Ru/Al2O3 catalyst coated onmetallic monolith for hydrogen production from ammonia was prepared by a dip-coating method using a catalyst slurry mixture composed of Ru/Al2O3 catalyst, inorganic binder (alumina sol) and organic binder (methyl cellulose). At the optimized 1:1:0.1 weight ratio of catalyst/inorganic binder/organic binder, the amount of catalyst coated on the metallic monolith after one cycle coating was about 61.6 g L-1. The uniform thickness (about 42 ㎛) and crystal structure of the catalyst coated on the metallic monolith surface were confirmed through scanning electron microscopy (SEM) and X-ray diffraction (XRD) analysis. Also, a numerical optimization regression equation for NH3 conversion according to the independent variables of reaction temperature (400-600 ℃) and gas hourly space velocity (1,000-5,000 h-1) was calculated by response surface methodology (RSM). This model indicated a determination coefficient (R2) of 0.991 and had statistically significant predictors. This regression model could contribute to the commercial process design of hydrogen production by ammonia decomposition.
Keywords
Ammonia decomposition; Hydrogen; Ruthenium alumina; Metallic monolith; Response surface methodology;
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Times Cited By KSCI : 1  (Citation Analysis)
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