Deposition of silver nanoparticles in geochemically heterogeneous porous media: predicting affinity from surface composition analysis.

dc.contributor.advisorWiesner, Mark R
dc.contributor.advisorHsu-Kim, Heileen
dc.contributor.advisorFerguson, P Lee
dc.contributor.authorLin, Shihong
dc.date.accessioned2011-05-20T19:13:06Z
dc.date.issued2011
dc.departmentCivil and Environmental Engineering
dc.description.abstractThe transport of uncoated silver nanoparticles (AgNPs) in a porous medium composed of silica glass beads modified with a partial coverage of iron oxide (hematite) was studied and compared to that in a porous medium composed of unmodified glass beads (GB). At a pH lower than the point of zero charge (PZC) of hematite, the affinity of AgNPs for a hematite-coated glass bead (FeO-GB) surface was significantly higher than that for an uncoated surface. There was a linear correlation between the average nanoparticle affinity for media composed of mixtures of FeO-GB and GB collectors and the relative composition of those media as quantified by the attachment efficiency over a range of mixing mass ratios of the two types of collectors, so that the average AgNPs affinity for these media is readily predicted from the mass (or surface) weighted average of affinities for each of the surface types. X-ray photoelectron spectroscopy (XPS) was used to quantify the composition of the collector surface as a basis for predicting the affinity between the nanoparticles for a heterogeneous collector surface. A correlation was also observed between the local abundances of AgNPs and FeO on the collector surface.
dc.identifier.urihttps://hdl.handle.net/10161/3775
dc.languageeng
dc.language.isoen_US
dc.subjectGeological Phenomena
dc.subjectHydrodynamics
dc.subjectHydrogen-Ion Concentration
dc.subjectIron
dc.subjectMetal Nanoparticles
dc.subjectPhotoelectron Spectroscopy
dc.subjectPorosity
dc.subjectSilver
dc.subjectSodium Hydroxide
dc.subjectSurface Properties
dc.titleDeposition of silver nanoparticles in geochemically heterogeneous porous media: predicting affinity from surface composition analysis.
dc.typeMaster's thesis
duke.embargo.months12
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pubs.organisational-groupDuke Science & Society
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pubs.organisational-groupNicholas School of the Environment
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pubs.organisational-groupNicholas School of the Environment
pubs.organisational-groupEarth and Ocean Sciences
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pubs.organisational-groupNicholas School of the Environment
pubs.organisational-groupEnvironmental Sciences and Policy
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pubs.organisational-groupPratt School of Engineering
pubs.organisational-groupDuke
pubs.organisational-groupPratt School of Engineering
pubs.organisational-groupCivil and Environmental Engineering
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pubs.organisational-groupTrinity College of Arts & Sciences
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pubs.organisational-groupTrinity College of Arts & Sciences
pubs.organisational-groupChemistry
pubs.publication-statusPublished

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