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Flocculation of Chlorella vulgaris with alum and pH adjustment.

Jian-Jiang ZhongAlireza Moosavi Zenooz
Published in: Biotechnology and applied biochemistry (2021)
Microalgae, a group of photosynthetic microorganisms, are a promising feedstock for biodiesel production, but their biomass retrieval is a challenging task. Flocculation is a feasible method for dewatering and harvesting microalgae biomass. In the current study, the effect of alum flocculation on Chlorella vulgaris biomass retrieval has been studied. Alum structural changes with pH were led to a full factorial design to address the effect of this chemical structure changes at different pH values. It is observed that the best flocculation efficiency could be achieved in the natural pH value of C. vulgaris growth medium (8.2) with less than 0.5 g/L flocculant addition, which would lead to the flocculation efficiency of more than 90%. An ensemble architecture of neural networks successfully employed for flocculation modeling.
Keyphrases
  • neural network
  • anaerobic digestion
  • wastewater treatment
  • sewage sludge
  • machine learning
  • risk assessment