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- Member of: ASU Regents' Professors Open Access Works
- Member of: Mason, Marc
ContributorsDubie, Norman (Author)
Created2015-09-01
Description
There are places that rest tangibly on the Earth's surface, and places that flourish only in the imagination, and places that site their existence within a moral geography, and a few places, not many, Bor Island among them, that manage to fuse all these settings together. In truth, Bor belongs with that long tradition of island Arcadias that have attracted Western thinkers since well before Thomas More in 1516 gave them the name they now have: Utopia. What makes Bor Island unique is that its informing theme is fire.
ContributorsPyne, Stephen (Author) / College of Liberal Arts and Sciences (Contributor) / School of Life Sciences (Contributor)
Created2014-11-30
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 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.
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.
ContributorsLai, Yenjung Sean (Author) / De Francesco, Federica (Author) / Aguinaga, Alyssa (Author) / Parameswaran, Prathap (Author) / Rittmann, Bruce (Author) / Biodesign Institute (Contributor) / Swette Center for Environmental Biotechnology (Contributor)
Created2015-10-20
Description
The impact of finite dielectric-covered ground-plane edge diffractions on the amplitude patterns of circular apertures is investigated. The model is based on the Geometrical Optics (GO) and the Uniform Theory of Diffraction (UTD) for an impedance wedge. The circular aperture antenna is mounted on square and circular finite ground planes that are coated with a thin lossy dielectric layer. The predictions based on the GO/UTD model are validated by comparisons to experimental results and simulated data.
ContributorsAboserwal, Nafati (Author) / Balanis, Constantine (Author) / Birtcher, Craig (Author) / Ira A. Fulton School of Engineering (Contributor) / School of Electrical, Computer and Energy Engineering (Contributor)
Created2014-11-30
Description
This paper presents a multiscale modeling approach to simulating the self-sensing behavior of a load sensitive smart polymer material. A statistical spring-bead based network model is developed to bridge the molecular dynamics simulations at the nanoscale and the finite element model at the macroscale. Parametric studies are conducted on the developed network model to investigate the effects of the thermoset crosslinking degree on the mechanical response of the self-sensing material. A comparison between experimental and simulation results shows that the multiscale framework is able to capture the global mechanical response with adequate accuracy and the network model is also capable of simulating the self-sensing phenomenon of the smart polymer. Finally, the molecular dynamics simulation and network model based simulation are implemented to evaluate damage initiation in the self-sensing material under monotonic loading.
ContributorsZhang, Jinjun (Author) / Koo, Bonsung (Author) / Liu, Yingtao (Author) / Zou, Jin (Author) / Chattopadhyay, Aditi (Author) / Dai, Lenore (Author) / Ira A. Fulton School of Engineering (Contributor) / School for the Engineering of Matter, Transport and Energy (Contributor)
Created2015-08-01