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A Review Of Enhancement Of Biohydrogen Productions By Chemical Addition Using A Supervised Machine Learning Method, Yiyang Liu, Jinze Liu, Hongzhen He, Shanru Yang, Yixiao Wang, Jin Hu, Huan Jin, Tianxiang Cui, Gang Yang, Yong Sun
A Review Of Enhancement Of Biohydrogen Productions By Chemical Addition Using A Supervised Machine Learning Method, Yiyang Liu, Jinze Liu, Hongzhen He, Shanru Yang, Yixiao Wang, Jin Hu, Huan Jin, Tianxiang Cui, Gang Yang, Yong Sun
Research outputs 2014 to 2021
In this work, the impact of chemical additions, especially nano‐particles (NPs), was quan-titatively analyzed using our constructed artificial neural networks (ANNs)‐response surface methodology (RSM) algorithm. Fe‐based and Ni‐based NPs and ions, including Mg2+, Cu2+, Na+, NH4+, and K+, behave differently towards the response of hydrogen yield (HY) and hydrogen evolution rate (HER). Manipulating the size and concentration of NPs was found to be effective in enhancing the HY for Fe‐based NPs and ions, but not for Ni‐based NPs and ions. An optimal range of particle size (86–120 nm) and Ni‐ion/NP concentration (81–120 mg L−1) existed for HER. Meanwhile, the manipulation …