Sensitivity analysis and artificial neural network-based optimization for low-carbon H2 production via a sorption-enhanced steam methane reforming (SESMR) process integrated with separation process-Reference-Cited by-同舟云学术

Sensitivity analysis and artificial neural network-based optimization for low-carbon H2 production via a sorption-enhanced steam methane reforming (SESMR) process integrated with separation process

Published:2022-01 Issue:2 Volume:47 Page:820-847
ISSN:0360-3199
Container-title:International Journal of Hydrogen Energy
language:en
Short-container-title:International Journal of Hydrogen Energy

Author:

Vo Nguyen Dat,Kang Jun-Ho,Oh Dong-Hoon,Jung Min Young,Chung Kyounghee,Lee Chang-Ha

Funder

National Research Foundation of Korea

Korea Ministry of Science and ICT

Ministry of Science, ICT and Future Planning

Publisher

Elsevier BV

Subject

Energy Engineering and Power Technology,Condensed Matter Physics,Fuel Technology,Renewable Energy, Sustainability and the Environment

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