Modification of graphite felt doped with nitrogen and boron for enhanced removal of dimethyl phthalate in peroxi-coagulation system and mechanisms

Ding, Jing; Dong, Langang; Geng, Yuxuan; Huang, Huibin; Zhao, Guangyu; Jiang, Junqiu; Qiu, Shan; Yuan, Yixing; Zhao, Qingliang

doi:10.1007/s11356-020-08384-1

Environ Sci Pollut Res

2020

DOI: 10.1007/s11356-020-08384-1

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Modification of graphite felt doped with nitrogen and boron for enhanced removal of dimethyl phthalate in peroxi-coagulation system and mechanisms

Jing Ding

Langang Dong

Yuxuan Geng

et al.

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Cited by 15 publications

References 57 publications

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Artificial neural network model for extracting knowledge from the electro‐Fenton process for acid mine wastewater treatment

Maurya,

Narayana,

Paturi

et al. 2024

CLEAN Soil Air Water

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In this study, artificial neural networks (ANNs) were employed to analyze the complex interactions between electro‐Fenton (EF) process variables (plate spacing, current intensity [CI], initial pH, aeration rate) and the Fe(II) and Mn(II) removal efficiency from wastewater. After experimenting with 69 different ANN architectures, the 4‐8‐8‐2 architecture was identified as more efficient, achieving higher accuracy (adj. R2 of 0.93 for Fe(II) and 0.96 for Mn(II)) than the published model. The research provides valuable insights into the correlation between EF process parameters and removal efficiency, guiding the optimization of wastewater treatment processes. Sensitivity analysis revealed that CI significantly affects Mn(II) and Fe(II) removal efficiency. A user‐friendly graphical interface was created based on the synaptic weights of the best model to enable practical predictions. It is designed to be accessible even to users without programing experience.

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Artificial neural network model for extracting knowledge from the electro‐Fenton process for acid mine wastewater treatment

Maurya,

Narayana,

Paturi

et al. 2024

CLEAN Soil Air Water

View full text Add to dashboard Cite

show abstract

Application of modified graphite felt as electrode material: a review

Chen

Ren

et al. 2022

Carbon Lett.

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Fast fluorescent blood sugar sensing using phenylboronic acid functionalized N, S-doped carbon dots

Wang,

Fan,

Zhang

et al. 2024

Carbon Lett.

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Modification of graphite felt doped with nitrogen and boron for enhanced removal of dimethyl phthalate in peroxi-coagulation system and mechanisms

Cited by 15 publications

References 57 publications

Artificial neural network model for extracting knowledge from the electro‐Fenton process for acid mine wastewater treatment

Artificial neural network model for extracting knowledge from the electro‐Fenton process for acid mine wastewater treatment

Application of modified graphite felt as electrode material: a review

Fast fluorescent blood sugar sensing using phenylboronic acid functionalized N, S-doped carbon dots

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