Robotics & Machine Learning Daily News2024,Issue(MAY.22) :61-62.

Reports on Machine Learning from Southeast University Provide New Insights (Digi tal Twins Based On Machine Learning for Optimal Control of Chemical Looping Hydr ogen Generation Processes)

Robotics & Machine Learning Daily News2024,Issue(MAY.22) :61-62.

Reports on Machine Learning from Southeast University Provide New Insights (Digi tal Twins Based On Machine Learning for Optimal Control of Chemical Looping Hydr ogen Generation Processes)

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Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Current study results on Machine Learn ing have been published. According to news reporting originating from Nanjing, P eople’s Republic of China, by NewsRx correspondents, research stated, “For a che mical looping hydrogen generation system, the set of input gas flow rate needed to be adjusted on the reactivity of oxygen carriers, in order to guarantee gas c onversion and to obtain higher hydrogen purity. However, the oxygen carriers oft en decayed upon repeated cycles, leading to pressing need for dynamic alignment between oxygen carrier reactivity and process parameters.”

Key words

Nanjing/People’s Republic of China/Asi a/Chalcogens/Cyborgs/Elements/Emerging Technologies/Gases/Hydrogen/Inorga nic Chemicals/Machine Learning/Southeast University

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

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