Enhanced removal of copper (Cu²⁺) by microalgae-bacteria consortium: Mechanistic insights, physiological responses, and artificial neural network (ANN)-based prediction

Enhanced removal of copper (Cu²⁺) by microalgae-bacteria consortium: Mechanistic insights, physiological responses, and artificial neural network (ANN)-based prediction

Copper (Cu) is a typical heavy metal pollutant that poses serious threats to aquatic ecosystems by damaging algal physiology and inducing oxidative stress. To mitigate its negative effects, this study explored more effective bioremediation strategies using the vgreen alga Scenedesmus quadricauda an...

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Bibliographic Details
Main Authors: Dehua, Zhao, Sze Wan, Poong, Tau Chuan, Ling, Sai Hin, Lai, Phaik Eem, Lim, Gek Cheng, Ngah
Format: Article
Language:en
Published: Elsevier B.V. 2025
Subjects:
T Technology (General)
TA Engineering (General). Civil engineering (General)
TC Hydraulic engineering. Ocean engineering
TD Environmental technology. Sanitary engineering
Online Access:http://ir.unimas.my/id/eprint/50527/1/paper%207.pdf
http://ir.unimas.my/id/eprint/50527/
https://www.sciencedirect.com/science/article/pii/S2213343725051346
https://doi.org/10.1016/j.jece.2025.120437
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Internet

http://ir.unimas.my/id/eprint/50527/1/paper%207.pdf
http://ir.unimas.my/id/eprint/50527/
https://www.sciencedirect.com/science/article/pii/S2213343725051346
https://doi.org/10.1016/j.jece.2025.120437

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