Department of Chemical Engineering, Payame Noor University, Tehran, Iran.
Department of Chemical Engineering, Amirkabir University of Technology, Tehran, Iran.
Biotechnol Appl Biochem. 2022 Jun;69(3):1112-1120. doi: 10.1002/bab.2182. Epub 2021 Jun 3.
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.
微藻是一群光合微生物，是生物柴油生产的有前途的原料，但它们的生物质回收是一项具有挑战性的任务。絮凝是一种可行的脱水和收获微藻生物质的方法。在本研究中，研究了明矾絮凝对普通小球藻生物质回收的影响。随着 pH 值的变化，明矾的结构发生变化，采用完全因子设计来解决不同 pH 值下这种化学结构变化的影响。结果表明，在普通小球藻生长培养基的自然 pH 值（8.2）下，添加少于 0.5g/L 的絮凝剂即可达到最佳的絮凝效率，超过 90%的絮凝效率。神经网络集成架构成功应用于絮凝建模。
