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Physics-informed neural network-based serial hybrid model capturing the hidden kinetics for sulfur-driven autotrophic denitrification process.
Zou, Xu; Guo, Hongxiao; Jiang, Chukuan; Nguyen, Duc Viet; Chen, Guang-Hao; Wu, Di.
Affiliation
  • Zou X; Department of Civil and Environmental Engineering, Water Technology Center, Hong Kong Branch of Chinese National Engineering Research Center for Control & Treatment of Heavy Metal Pollution, The Hong Kong University of Science and Technology, Hong Kong, China.
  • Guo H; Department of Civil and Environmental Engineering, Water Technology Center, Hong Kong Branch of Chinese National Engineering Research Center for Control & Treatment of Heavy Metal Pollution, The Hong Kong University of Science and Technology, Hong Kong, China.
  • Jiang C; Department of Civil and Environmental Engineering, Water Technology Center, Hong Kong Branch of Chinese National Engineering Research Center for Control & Treatment of Heavy Metal Pollution, The Hong Kong University of Science and Technology, Hong Kong, China.
  • Nguyen DV; Centre for Environmental and Energy Research, Ghent University Global Campus, Incheon, Republic of Korea; Department of Green Chemistry and Technology, Centre for Advanced Process Technology for Urban REsource recovery (CAPTURE), Ghent University, Ghent, Belgium.
  • Chen GH; Department of Civil and Environmental Engineering, Water Technology Center, Hong Kong Branch of Chinese National Engineering Research Center for Control & Treatment of Heavy Metal Pollution, The Hong Kong University of Science and Technology, Hong Kong, China. Electronic address: ceghchen@ust.hk
  • Wu D; Department of Civil and Environmental Engineering, Water Technology Center, Hong Kong Branch of Chinese National Engineering Research Center for Control & Treatment of Heavy Metal Pollution, The Hong Kong University of Science and Technology, Hong Kong, China; Centre for Environmental and Energy
Water Res ; 243: 120331, 2023 Sep 01.
Article in En | MEDLINE | ID: mdl-37454462
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Bioreactors / Denitrification Type of study: Prognostic_studies Language: En Journal: Water Res Year: 2023 Document type: Article Affiliation country: China Country of publication: United kingdom
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Bioreactors / Denitrification Type of study: Prognostic_studies Language: En Journal: Water Res Year: 2023 Document type: Article Affiliation country: China Country of publication: United kingdom