Predicting microbial fuel cell biofilm communities and power generation from wastewaters with artificial neural network

被引：8

作者：

Lim, Chiy En ^{[1
]}

Chew, Chien Ley ^{[2
]}

Pan, Guan-Ting ^{[3
]}

Chong, Siewhui ^{[1
]}

Arumugasamy, Senthil Kumar ^{[1
]}

Lim, Jun Wei ^{[4
,5
]}

Al-Kahtani, Abdullah A. ^{[6
]}

Ng, Hui-Suan ^{[7
]}

Abdurrahman, Muslim ^{[8
]}

机构：

[1] Univ Nottingham Malaysia, Fac Sci & Engn, Dept Chem & Environm Engn, Jalan Broga, Semenyih 43500, Selangor, Malaysia

[2] Sime Darby Res Sdn Bhd, Lot 2664,Jalan Pulau Carey, Pulau Carey 42960, Selangor, Malaysia

[3] Murdoch Univ, Coll Sci Hlth Engn & Educ, 90 South St, Murdoch, WA 6150, Australia

[4] Univ Teknol PETRONAS, Inst Selfsustainable Bldg, HICoE Ctr Biofuel & Biochem Res, Dept Fundamental & Appl Sci, Perak Darul Ridzuan 32610, Malaysia

[5] Saveetha Inst Med & Tech Sci, Saveetha Sch Engn, Dept Biotechnol, Chennai 602105, India

[6] King Saud Univ, Coll Sci, Dept Chem, POB 2455, Riyadh 11451, Saudi Arabia

[7] Univ Cyberjaya, Ctr Res & Grad Studies, Cyberjaya 63000, Selangor, Malaysia

[8] Univ Islam Riau, Dept Petr Engn, Jl Kaharuddin Nasution 113, Pekanbaru 28284, Indonesia

来源：

INTERNATIONAL JOURNAL OF HYDROGEN ENERGY | 2024年 / 52卷

关键词：

Microbial fuel cell; MFC; Artificial neural network; Power generation; Wastewater; Machine learning; ELECTRICITY PRODUCTION; EXOELECTROGENIC BACTERIA; INOCULUM;

D O I：

10.1016/j.ijhydene.2023.08.290

中图分类号：

O64 [物理化学（理论化学）、化学物理学];

学科分类号：

070304 ; 081704 ;

摘要：

Artificial neural network (ANN) was used to predict the biofilm communities present in the microbial fuel cells (MFCs), as well as the power generation from wastewater treatment. The ANN model was able to predict the total abundances of seven exoelectrogenic bacteria-associated genera, viz. Anaeromyxobacter, Bacillus, Clostridium, Comamonas, Desulfuromonas, Geobacter, and Pseudomonas for the MFCs based on the physicochemical properties of the sludge inocula, with accuracies in the range of 62 similar to 92%. An additional ANN model was developed to integrate the biofilm results and predict the power generation from wastewater, with an accuracy of 84% when validating with literature studies. The results show that ANN is a useful tool for predicting the biofilm communities and power generation from MFCs, thus avoiding the necessity of conducting complex biofilm metagenome analysis, and greatly aiding future parametric investigation and scale-up studies. (c) 2023 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.

引用

页码：1052 / 1064

页数：13

共 42 条

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