abstract: Electro-Selective Fermentation (ESF) combines Selective Fermentation (SF) and a Microbial Electrolysis Cell (MEC) to selectively degrade carbohydrate and protein in lipid-rich microalgae biomass, enhancing lipid wet-extraction. In addition, saturated long-chain fatty acids (LCFAs) are produced via β-oxidation. This dissertation builds understanding of the biochemical phenomena and microbial interactions occurring among fermenters, lipid biohydrogenaters, and anode respiring bacteria (ARB) in ESF. The work begins by proving that ESF is effective in enhancing lipid wet-extraction from Scenedesmus acutus biomass, while also achieving “biohydrogenation” to produce saturated LCFAs. Increasing anode respiration effectively scavenges short chain fatty acids (SCFAs) generated by fermentation, reducing electron loss. However, the effectiveness of ESF depends on biochemical characteristics of the feeding biomass (FB). Four different FB batches yield different lipid-extraction performances, based on the composition of FB’s cellular structure. Finally, starting an ESF reactor with a long solid retention time (SRT), but then switching it to a short SRT provides high lipid extractability and volumetric production with low lipid los. Lipid fermenters can be flushed out with short a SRT, but starting with a short SRT fails achieve good results because fermenters needed to degrading algal protective layers also are flushed out and fail to recover when a long SRT is imposed. These results point to a potentially useful technology to harvest lipid from microalgae, as well as insight about how this technology can be best managed. / Dissertation/Thesis / Doctoral Dissertation Civil, Environmental and Sustainable Engineering 2019
Identifer | oai:union.ndltd.org:asu.edu/item:55646 |
Date | January 2019 |
Contributors | Liu, Yuanzhe (Author), Rittmann, Bruce E (Advisor), Torres, Cesar I (Committee member), Krajmalnik-Brown, Rosa (Committee member), Arizona State University (Publisher) |
Source Sets | Arizona State University |
Language | English |
Detected Language | English |
Type | Doctoral Dissertation |
Format | 160 pages |
Rights | http://rightsstatements.org/vocab/InC/1.0/ |
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