Matching Items (3)
Description
Microalgae-derived lipids are good sources of biofuel, but extracting them involves high cost, energy
expenditure, and environmental risk. Surfactant treatment to disrupt Scenedesmus biomass was evaluated
as a means to make solvent extraction more efficient. Surfactant treatment increased the recovery of fatty
acid methyl ester (FAME) by as much as 16-fold vs. untreated

Microalgae-derived lipids are good sources of biofuel, but extracting them involves high cost, energy
expenditure, and environmental risk. Surfactant treatment to disrupt Scenedesmus biomass was evaluated
as a means to make solvent extraction more efficient. Surfactant treatment increased the recovery of fatty
acid methyl ester (FAME) by as much as 16-fold vs. untreated biomass using isopropanol extraction, and
nearly 100% FAME recovery was possible without any Folch solvent, which is toxic and expensive. Surfactant
treatment caused cell disruption and morphological changes to the cell membrane, as documented by
transmission electron microscopy and flow cytometry. Surfactant treatment made it possible to extract wet
biomass at room temperature, which avoids the expense and energy cost associated with heating
and drying of biomass during the extraction process. The best FAME recovery was obtained from highlipid
biomass treated with Myristyltrimethylammonium bromide (MTAB)- and 3-(decyldimethylammonio)-
propanesulfonate inner salt (3_DAPS)-surfactants using a mixed solvent (hexane : isopropanol = 1 : 1, v/v)
vortexed for just 1 min; this was as much as 160-fold higher than untreated biomass. The critical micelle
concentration of the surfactants played a major role in dictating extraction performance, but the growth
stage of the biomass had an even larger impact on how well the surfactants disrupted the cells and
improved lipid extraction. Surfactant treatment had minimal impact on extracted-FAME profiles and,
consequently, fuel-feedstock quality. This work shows that surfactant treatment is a promising strategy for
more efficient, sustainable, and economical extraction of fuel feedstock from microalgae.
Created2015-10-20
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Description
Chloroform and methanol are superior solvents for lipid extraction from photosynthetic microorganisms, because they can overcome the resistance offered by the cell walls and membranes, but they are too toxic and expensive to use for large-scale fuel production. Biomass from the photosynthetic microalga Scenedesmus, subjected to a commercially available pre-treatment

Chloroform and methanol are superior solvents for lipid extraction from photosynthetic microorganisms, because they can overcome the resistance offered by the cell walls and membranes, but they are too toxic and expensive to use for large-scale fuel production. Biomass from the photosynthetic microalga Scenedesmus, subjected to a commercially available pre-treatment technology called Focused-Pulsed® (FP), yielded 3.1-fold more crude lipid and fatty acid methyl ester (FAME) after extraction with a range of solvents. FP treatment increased the FAME-to-crude-lipid ratio for all solvents, which means that the extraction of non-lipid materials was minimized, while the FAME profile itself was unchanged compared to the control. FP treatment also made it possible to use only a small proportion of chloroform and methanol, along with isopropanol, to obtain equivalent yields of lipid and FAME as with 100% chloroform plus methanol.
ContributorsLai, Yenjung Sean (Author) / Parameswaran, Prathap (Author) / Li, Ang (Author) / Baez, Maria (Author) / Rittmann, Bruce (Author) / Biodesign Institute (Contributor) / Swette Center for Environmental Biotechnology (Contributor)
Created2014-12-01
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Description
Over the past few years, the Internet of Things (IoT) has become an essential element of daily life. At the core of IoT are the densely deployed heterogeneous IoT sensors, such as RFID tags, cameras, temperature sensors, pressure sensors. These sensors work collectively to sense and capture intricate details of

Over the past few years, the Internet of Things (IoT) has become an essential element of daily life. At the core of IoT are the densely deployed heterogeneous IoT sensors, such as RFID tags, cameras, temperature sensors, pressure sensors. These sensors work collectively to sense and capture intricate details of the surroundings, enabling the provision of highly detailed and comprehensive information. This fine-grained information encompasses a wide range of critical parameters that contribute to intelligent decision-making processes. Therefore, the security and privacy of heterogeneous IoT systems are indispensable. The heterogeneous nature of IoT systems poses a number of security and privacy challenges, including device security and privacy, data security and privacy, communication security, and AI and machine learning security. This dissertation delves into specific research issues related to device, communication, and data security, addressing them comprehensively. By focusing on these critical aspects, this work aims to enhance the security and privacy of heterogeneous IoT systems, contributing to their reliable and trustworthy operation. Specifically, Chapter 1 introduces the challenges and existing solutions in heterogeneous IoT systems. Chapter 2 presents SmartRFID, a novel UHF RFID authentication system to promote commodity crypto-less UHF RFID tags for security-sensitive applications. Chapter 3 presents WearRF-CLA, a novel CLA scheme built upon increasingly popular wrist wearables and UHF RFID systems. Chapter 4 presents the design and evaluation of PhyAuth, a PHY message authentication framework against packet-inject attacks in ZigBee networks. Chapter 5 presents NeighborWatch, a novel image-forgery detection framework for multi-cameras system with OFoV. Chapter 6 discusses the future work.
ContributorsLi, Ang (Author) / Zhang, Yanchao YZ (Thesis advisor) / Fan, Deliang DF (Committee member) / Xue, Guoliang GX (Committee member) / Reisslein, Martin MR (Committee member) / Arizona State University (Publisher)
Created2023