Aqueous Aggregation and Surface Deposition Processes of

Sep 15, 2014 - Engineered, superparamagnetic, iron oxide nanoparticles (IONPs) have significant potential as platform materials for environmental sens...
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Aqueous Aggregation and Surface Deposition Processes of Engineered Superparamagnetic Iron Oxide Nanoparticles for Environmental Applications Wenlu Li, Di Liu, Jiewei Wu, Changwoo Kim, and John Dyer Fortner Environ. Sci. Technol., Just Accepted Manuscript • Publication Date (Web): 15 Sep 2014 Downloaded from http://pubs.acs.org on September 29, 2014

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Environmental Science & Technology

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Aqueous Aggregation and Surface Deposition

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Processes of Engineered Superparamagnetic Iron

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Oxide Nanoparticles for Environmental Applications

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Wenlu Li, Di Liu, Jiewei Wu, Changwoo Kim, and John D. Fortner*

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Department of Energy, Environmental, and Chemical Engineering

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Washington University in St. Louis

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St. Louis, Missouri 63130, USA

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Submitted to

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Environmental Science and Technology

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July 31th, 2014

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*To whom correspondence should be addressed:

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John D. Fortner: Tel: +1-314-935-9293; Fax: +1-314-935-5464; Email: [email protected]

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ABSTRACT

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Engineered, superparamagnetic, iron oxide nanoparticles (IONPs) have significant potential as

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platform materials for environmental sensing, imaging and remediation due to their unique size,

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physicochemical and magnetic properties.

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chemistry of the materials is crucial for such applications in the aqueous phase, and in particular,

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for porous matrixes with particle-surface interaction considerations.

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superparamagnetic, highly monodispersed 8 nm IONPs were synthesized and transferred into

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water as stable suspensions (remaining monodispersed) by way of an interfacial oleic acid

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bilayer surface.

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interactions (deposition and release) were quantitatively investigated and described

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systematically as a function of ionic strength (IS) and type with time-resolved dynamic light

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scattering (DLS), zeta potential, and real-time quartz crystal microbalance with dissipation

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monitoring (QCM-D) measurements. The critical coagulation concentration (CCC) for oleic

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acid bilayer coated iron oxide nanoparticles (OA-IONPs) were determined to be 710 mM for

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NaCl (matching DLVO predictions) and 10.6 mM for CaCl2, respectively. For all conditions

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tested, surface deposition kinetics showed stronger, more favorable interactions between OA-

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IONPs and polystyrene surfaces compared to silica, which is hypothesized to be due to increased

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particle-surface hydrophobic interactions (when compared to silica surfaces).

To this end, controlling the size and surface

In this study,

Once stabilized and characterized, particle-particle and model surface

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KEYWORDS

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Iron oxide nanoparticles (IONPs), nanoparticle aggregation, nanoparticle deposition,

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nanoparticle stability, environmental sensing, hydrophobic interactions, Quartz Crystal

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Microbalance with Dissipation (QCM-D)

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INTRODUCTION

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The vision of applying finely divided materials, or even nanoscale materials for simultaneous

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sensing, mapping and remediating of targeted, complicated environments has recently gained

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increasing attention, concurrent with advances in related material sciences.1-4 In particular,

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magnetic based nanoparticles (magnetite and maghemite) provide unique advantages to such

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applications due to their size (2 to 100 nm) and tunable physicochemical properties. To this

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point, engineered magnetite (Fe3O4) based nanostructures, differ substantially from it’s bulk

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phase counterpart due to greatly enhanced specific surface area, reactivity, and magnetic

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response (e.g., superparamagnetic properties are observed for single domain particles within a

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size range of ca. 6-20 nm compared to bulk phase ferromagnetism).5 Such properties underpin

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this class of materials’ potential in therapeutic, biological and environmental imaging,6-10

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remediation11-15 and sensing technologies.1, 2, 4, 16-19

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Ultimately though, for many of these applications to be successful, engineered materials such

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as these must not only process intrinsic, novel functionality but must also allow for controlled

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physical placement (e.g., within a desired volume or at a specific target interface). As an

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example, single domain, superparamagnetic iron oxide (magnetite) based nanoparticles have

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significant potential as T2 type nuclear magnetic resonance (NMR) imaging contrast agents7, 20

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and are being explored for enhanced environmental (subsurface) imaging.4,

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technologies are aimed at extending and refining hydrocarbon detection in oil-field rocks and

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even for NAPL (nonaqueous phase liquids) sensing (and remediation) in contaminated systems.2,

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3, 23

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nanoscale materials can be transported through low porosity media,2, 22, 24 potentially reaching

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non-aqueous liquid phases/interface targets (e.g., oil-water-interfaces), at which point they can

10, 21, 22

Such

Further, based on material size (< 20 nm) and dispersivity, it is possible that monodispersed

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be responsive and potentially even functional.22-24 However, to date, the bottleneck for such

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applications is largely due to particle (in)stability challenges.10, 24-26 As the aggregation state

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changes (based on the surface energy of suspended nanoparticles), transportation of

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nanoparticles through low porous media is increasingly limited and final deposition ‘misses the

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mark’. Normally, the stability of the nanoparticles is controlled by the surface chemistries

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involved27 and in particular, the coatings and charge of the particle surface, the matrix surface

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chemistries, the ionic strength or salinity of the water, and the interactions with other substances,

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such as natural organic matter (NOM).28 Therefore, quantitatively understanding the aggregation

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and deposition/adsorption behavior of (surface)stabilized iron oxide nanoparticles (IONPs) under

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different water chemistries is crucial for use in any potential in-situ, subsurface technologies.

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The development of low defect, single domain nanoscale IONPs has drawn considerable

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attention from a number of research communities over the past two decades.5, 7, 29-31 In contrast

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to aqueous preparation routes, high temperature organic solution phase methods, in particular,

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allow for the preparation and control of highly uniformed nanoparticles due to the successful

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separation of nucleation and the growth phases during synthesis.5 For this work, monodisperse

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IONPs with controlled sizes were synthesized by decomposition of iron carboxylate salts in

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high-temperature boiling solvent.29,

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organic solvent, a favorable stabilizing surface is required for aqueous suspensions, and thus

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applications. Here, we use a stable, oleic acid bilayer surface coating allowing for the efficient

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transfer33 of the nanoparticles from nonpolar solvent to water, forming stable, nonaggregating,

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monodispersed suspensions.

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available (oleic acid is a major component in a number of natural oils including olive oil and

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magnetite is a widely found natural mineral), such a “green” core-shell structure may be

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As the aforementioned materials are synthesized in

Further, as both materials are widely naturally occurring and

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desirable for actual environmental applications.33

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superparamagnetic properties29 of the iron oxide core does not provide attractive magnetic forces

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between nanoparticles, unlike ferromagnetic particles, unless an external magnetic field is

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applied, thus simplifying aggregation observations and discussion.

Lastly, within this size range, the

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To the best of our knowledge, this is the first study systematically quantifying the aggregation

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kinetics of engineered superparamagnetic IONPs and their deposition behaviors onto different

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model environmental surfaces in the presence of sodium and calcium cations. IONP suspensions

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were developed, synthesized and characterized with size of 8 nm as stable, monodispersed

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aqueous suspensions by way of an oleic acid surface bilayer. Particle-particle and model surface

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interactions were quantitatively investigated and described as a function of ionic strength/type

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with time resolved dynamic light scattering (DLS), zeta (ζ) potential and real-time quartz crystal

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microbalance with dissipation monitoring (QCM-D) measurements (surface deposition and

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release), using two model environmental surfaces (hydrophilic vs. hydrophobic).

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MATERIALS AND METHODS

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Materials: Iron(III) oxide (hydrated, catalyst grade), 1-octadecene (technical grade, 90%),

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oleic acid (technical grade, 90%), sodium chloride (ACS reagent, ≥99.0%), calcium chloride

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dihydrate (ACS reagent, ≥99%), sodium hydroxide (ACS reagent, ≥97.0%) , sodium bicarbonate

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(ACS reagent, 99.7-100.3%) and nitric acid (trace metal grade) were all purchased from Sigma-

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Aldrich. All materials were used without any further purification.

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Preparation of Oleic Acid Bilayer Coated Iron Oxide Nanoparticles (OA-IONPs):

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Detailed synthesis of IONPs and phase transfer method for OA-IONPs are given in the

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Supporting Information (SI). The concentration of the water stable OA-IONPs stock suspension

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was 50 mg/L as determined by inductively coupled plasma mass spectrometry (ICP-MS, Agilent

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7500ce).

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Solution Chemistry: Various concentrations of NaCl and CaCl2 electrolyte stock solutions

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were prepared and filtrated (pore size of 0.2 um, Millipore) before use. All DLS and QCM-D

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measurements were conducted at pH 7.2 ± 0.2 buffered by 0.15 mM NaHCO3 and at room

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temperature (22 °C).

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Dynamic Light Scattering: The DLS measurements were performed on a Zetasizer (Nano

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ZS, Malvern). The OA-IONPs stock solution was diluted 50 times to 1 mg/L for the DLS

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experiments and pH was adjusted to 7.2. For each measurement, a predetermined volume of

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diluted nanoparticle suspension was added into a vial. After that, a certain amount of electrolyte

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stock solution was injected into the vial to make the total volume of sample to be 1 mL. After a

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short time of vortex (1.5 s), samples were quickly put into the DLS chamber and measured

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immediately. The scattered light intensity was detected by a photodetector at a scattering angle

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of 173°. Data points were measured every 15 s and recorded continuously. DLS samples were

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left to aggregate between 20 to 60 min, depending on the aggregation rate of each sample. The

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attachment efficiency (α) of the OA-IONP aggregates in the presence of various electrolyte

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concentrations was calculated by the following equation34

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1

α= W = k

k fast

(1)

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where k is the initial aggregation rate constant at different salt concentrations and kfast is the

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aggregation rate constant under diffusion-limited (fast) aggregation conditions.

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Quartz Crystal Microbalance with Dissipation: QCM-D measurements were performed

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with a Q-Sense E4 (Q-sense AB, Sweden) unit by simultaneously monitoring the changes in

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frequency (∆f) and energy dissipation (∆D) of a 5 MHz silica (SiO2) coated QCM-D crystal

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(QSX-303, Q-sense) and a 5 MHz polystyrene (PS) coated QCM-D crystal (QSX-305, Q-sense).

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Protocols used to clean the sensors and detailed deposition experiment conditions are described

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in the Supporting Information (SI). All deposition measurements were allowed to proceed for a

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period between 10 to 30 min to determine the nanoparticle deposition rates. As deposition of

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OA-IONPs occurred onto the silica or polystyrene sensor surfaces, the increase in the mass of the

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crystal induced a continuous shift in the frequency (f), as described by the Sauerbrey

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relationship.35

∆ = −  ∆

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(2)

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where n is the overtone number (1, 3, 5, 7, 9, etc…) and C is the crystal constant (17.7 ng/(Hz

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cm2)). The deposition process on the crystal surface will also enhance the crystal’s ability to

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dissipate energy, as shown in the increase in the energy dissipation (D) via the following

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equation: E

dissipated D= 2πE

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stored

(3)

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where Edissipated is the energy loss in one oscillation cycle and Estored is the total energy stored in

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the oscillator. Since deposited mass is linear to the frequency shift, the nanoparticle deposition

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rate can be calculated from the initial slope of frequency change.

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normalized frequency at the third overtone in a given period (t) was used to quantify the

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deposition rate (rd):34

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d =

d∆ d

The initial change of

(4)

In order to obtain the deposition attachment efficiency (αD) as shown in equation 5,

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favorable deposition conditions were conducted by coating the silica sensor with a positively

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charged poly-L-lysine (PLL) layer as described elsewhere:36

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 = "

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∆ ⁄  ∆ ⁄  #fav

(5)

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RESULTS AND DISCUSSION

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IONPs Stabilization and Characterization

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IONPs of 8 nm were synthesized and used specifically for this study as shown in TEM

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micrograph in Figure 1a. These nanoparticles are highly uniform in size, with size distribution

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variability well under 10 %; the size distribution histograms are shown in Figure S1a. The HR-

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TEM image (SI Figure S1b) of 8 nm IONPs shows that they are highly crystallized and the

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lattice fringe was indexed to (440) plane of the inverse spinel iron oxide structure.29, 37 Once

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synthesized, all nanoparticles used for this work were capped with an oleic acid layer with

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hydrophobic tail pointing outside, rendering them stable in the non-polar solvent (in this case,

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hexanes). A water stabilizing, surface bilayer was achieved by mixing a small amount of

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additional oleic acid with water and the iron oxide suspension in hexane (creating a liquid-liquid

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system) and then using a sonication probe to facilitate phase transfer.38-40 Corresponding TEM

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micrographs (Figure 1b) along with DLS measurements discussed below, indicate aqueous

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transferred IONPs remain monodisperse with no core size change. The stable, homogenous

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bilayer, as described by others, is formed when the hydrophobic oleic acid tail of the second

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layer aligns with the original hydrophobic tail of the first layer (via hydrophobic and dispersive

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Van der Waals forces),41 and the hydrophilic head group (carboxylic acid functionality) of the

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second layer aligns at the aqueous interface, rendering the nanoparticles water stable.33 The

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number-weighted hydrodynamic diameter of the OA-IONPs was measured to be 15.6 ± 1.3 nm

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for 8 nm IONPs originally dispersed in hexane (SI Figure S2). The DLS value for 8 nm IONPs

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is consistent with the value reported before (14.2 ± 2.6 nm) which takes into account the

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thickness of the bilayer.33 For all aqueous suspensions, no significant change in hydrodynamic

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diameter was observed after 3 months and the OA-IONPs did not precipitate over 6 months.

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Figure 2 shows ζ-potential measurements of 8 nm OA-IONPs under various NaCl and CaCl2

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electrolyte concentrations. Due to the dissociation of carboxylate groups at pH 7.2, OA-IONPs

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exhibit negatively charged surfaces (OA pKa = 4.95).42 ζ-potentials of OA-IONPs were negative

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for the entire range of NaCl and CaCl2 concentrations examined in this study.

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conditions, as expected, the nanoparticle ζ-potentials become less negative with increasing ionic

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strength due to the basic charge screening effect.43 ζ-potential values of OA-IONPs became less

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negative from -53.4 mV to -46.5 mV as NaCl concentration increased from 10 to 300 mM. As

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low as 0.05 mM of CaCl2 significantly increased the ζ-potential values of OA-IONPs to -30.7

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mV, indicating the enhanced effect of charge neutralization from divalent cations, as observed in

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other studies.34, 43, 44

Under all

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Aggregation Kinetics

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Extensive studies, focused mostly on carbon based material and metal/metal oxides, have been

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conducted to evaluate the aqueous aggregation behavior(s) of a number of engineered

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nanomaterials.27 By monitoring effective particle size change via dynamic light scattering (DLS),

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aggregation kinetics (as a function of one variable) can be determined. For most studies, such

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aggregation behaviors of engineered materials can be described by Derjaguin-Landau-Verwey-

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Overbeek (DLVO) theory27 and exhibit reaction-limited (slow) and diffusion-limited (fast)

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regimes.45 Further, previous reports primarily focus on the effects of Na+ and Ca2+, as sodium

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and calcium are the most abundant cations in most natural aquifers and even deep saline water

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resevoirs.46

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Here, the aggregation of OA-IONPs was also studied in the presence of NaCl and CaCl2 at pH

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7.2. The aggregation rate of OA-IONPs increased with increasing NaCl concentrations below

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700 mM (SI Figure S3a). This is consistent with zeta potential measurements as an increase in

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NaCl concentration, nanoparticle zeta potential became less negative (Figure 2). However, at

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higher NaCl concentrations (800 and 1000 mM), the increase in electrolyte concentration has a

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negligible effect on the aggregation rate. Similarly, the aggregation kinetics of OA-IONPs in the

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presence of CaCl2 follows the same trend (SI Figure S3b), but at lower concentrations as

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expected with divalent Ca2+.34, 44, 47 Figure 3 shows the aggregation attachment efficiencies of

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OA-IONPs as a function of both electrolyte concentrations. For these systems, aggregation

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kinetics can also be classically divided into two regimes: reaction-limited (slow) and diffusion-

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limited (fast) aggregation.

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concentration screens the surface charge, thus effectively reducing the energy barriers to

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aggregation (SI and SI Figure S4).27,

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However, when the electrolyte concentrations increase to the critical coagulation concentration,

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the energy barrier is completely eliminated, leading to diffusion-controlled aggregation. Figure

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S5 shows good agreement between prediction of DLVO theory (calculated) and experimental

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data. The critical coagulation concentrations (CCC) for OA-IONPs are 710 mM for NaCl and

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10.6 mM for CaCl2. Tombácz et al. reported a CCC value of 500 mM NaCl for poly(acrylic acid)

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– PAA coated magnetite nanoparticles with primary size under 10 nm at pH 6.5.48 Considering

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the different preparation methods for IONPs and surface modifications, our CCC value for OA-

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IONPs is comparable. The ratio of CCC values calculated (10.6/710) is proportional to z-6.07,

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where z is the valence of the calcium counterion (i.e. z=2). This is in good agreement with the

In the reaction-limited regime, an increase in the electrolyte

34

As a result, the aggregation sizes increase rapidly.

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empirical Schulze-Hardy rule that the CCC ratio for CaCl2 and NaCl should be z-6 for particles

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with large ζ-potentials.49

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Deposition Kinetics

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Quartz crystal microbalance with dissipation (QCM-D) enables the real-time, high sensitivity

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surface (interaction) analysis (here as particle deposition and release) for fluid suspended

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particles and even macromolecules.50, 51 Recently, QCM-D has proven to be useful and powerful

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in evaluating solution based interfacial behaviors of engineered nanomaterials.27,

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Representative studies of note include: Chen et al. who examined the deposition of fullerene

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nanoparticles onto silica surfaces and found a decreased deposition rate at higher electrolyte

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concentrations;34 Fatisson et al.52 employed this technique to compare the deposition behavior of

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bare and CMC-modified nanoscale zerovalent iron (nZVI) particles onto silica surfaces over a

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wide range of solution chemistries; Saleh et al. found the lowest deposition rates from the

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triblock copolymer coated nanoscale zerovalent iron (nZVI) compared to bare and other

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surfactant-modified nZVI from QCM-D experiment.53 Further, QCM-D based analyses can be

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tailored as quartz crystal (sensor) surfaces can be modified via a number of methods to mimic

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particle or environmental surfaces36 for enhancing the technique’s applicability. As done in this

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work, interfacial surface interactions can be quantitatively investigated with QCM-D using both

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(relatively) hydrophilic (as silica) and (relatively) hydrophobic (as polystyrene)54-57 sensor

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surfaces.

36, 52

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A representative normalized frequency shift at the third overtone ( ∆"%# ) for OA-IONPs

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deposition onto a polystyrene surface is shown in Figure S6. The deposition kinetics for OA-

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IONPs were studied as a function of nanoparticle concentration ranging from 2.5 mg/L to 40

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mg/L (measured as Fe). In order to have a sufficient frequency shift for all deposition studies,

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we chose 7.5 mg/L as the concentration for all QCM-D measurements, above this concentration

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(40 mg/L maximum) no change in deposition kinetics was observed. Figure S7 presents a

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typical deposition study of 8 nm OA-IONPs in the presence of 0, 300, 500, and 800 mM NaCl

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onto a silica sensor surface. To begin, there was no deposition of OA-IONPs onto silica sensor

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surface in the absence of salt.

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electrostatic interactions between OA-IONPs and the silica surface.

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silica58 are both negatively charged pH 7.2, the strong repulsive force simply inhibits deposition.

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When OA-IONPs do interact with the sensor surface, the decrease in the frequency shift

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indicates the continuous deposition of nanoparticles and as nonlinear deposition behavior34 is

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observed at high ionic strength (e.g., 800 mM NaCl on silica), where the initial slope is used to

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calculate the unsaturated (surface) deposition rate. The deposition behaviors of 8 nm OA-IONPs

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onto silica and polystyrene sensor surfaces were examined over a wide range of NaCl and CaCl2

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concentrations, as shown in Figure 4. As electrolyte concentrations increased, deposition rates

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correspondingly increased as the electric double layers were compressed by the charge screening

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from the additional salt. Further increase in electrolyte concentrations close to or higher than the

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CCC values, resulted in diffusion limited transport, and the deposition rate then decreased as

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expected and observed by others.34 From Figure 4a, nanoparticles reach a maximum deposition

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rate on silica at around 500 mM NaCl, while on the more hydrophobic polystyrene surface, the

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fastest deposition rate was observed for NaCl concentrations between 200-400 mM.

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separate peaks in the deposition rates of silica and polystyrene surfaces indicate the higher

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affinity of (this particular) OA-IONPs deposition onto polystyrene, a relatively more

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hydrophobic surface. In addition, the maximum deposition rate on polystyrene is around 6.5

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Hz/min, which is significantly higher than the deposition rate on silica surface (2.5 Hz/min).

This observation can be explained based on the repulsive Since OA-IONPs and

The

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From Figure 4b, nanoparticles reach a maximum deposition rate on silica around 5 to 7.5 mM

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CaCl2, while on the polystyrene surface, the fastest deposition concentration for CaCl2 is

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between 2-3 mM. The concentrations at which the nanoparticles reach highest deposition rate in

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the presence of NaCl are significantly higher than that in the presence of CaCl2. In addition to

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the similar charge screening effect as Na+, Ca2+ can also form complexes with the carboxyl

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groups and thus further neutralize their surface charge.34 Furthermore, carboxyl groups do not

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form inner sphere complexes with Na+ (i.e. Na+ can only screen the charges of nanoparticles).59

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For these reasons, Ca2+ ions are significantly more effective in reducing the energy barrier to

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OA-IONPs deposition than Na+, which is in line with observations made by others.34, 43, 53, 60

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Favorable deposition onto PLL coated silica sensor surfaces was also conducted under the

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same conditions as for the unfavorable conditions.27, 34 Insets from Figure 4 show the deposition

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rates (frequency shift rates) of OA-IONPs in the presence of NaCl and CaCl2 onto PLL coated

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sensor surfaces at pH 7.2. Generally, on PLL coated sensor surfaces, deposition rates decreased

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with increasing ionic strength in both NaCl and CaCl2 solutions.

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explained due to the significant formation of large aggregates36,

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concentrations as shown for previous DLS measurements (SI Figure S3). By normalizing the

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particle deposition rates at unfavorable conditions to the corresponding particle deposition rates

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at favorable conditions, deposition attachment efficiencies (αD) of OA-IONPs are shown in

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Figure 5. For deposition onto silica sensor surfaces, αD increased with the increasing IS until the

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energy barrier is completely eliminated, resulting in αD of 1 (SI Figure S8). The critical

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deposition concentration36 (CDC) was determined to be 485 mM for NaCl and 5.1 mM for CaCl2.

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While the deposition kinetics on silica surfaces clearly shows typical unfavorable and favorable

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regimes, deposition kinetics on polystyrene surfaces do not follow classical deposition behaviors

The observation can be

43, 58

at elevated electrolyte

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of engineered particles,27 suggesting that hydrophobic interactions mainly influence the

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attachment of engineered OA-IONPs onto polystyrene surfaces.61 Xiao and Wiesner found that

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aqu-nC60, a moderately hydrophobic nanoparticle, has the highest retention on the most

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hydrophobic BSA-coated glass beads, indicating the hydrophobic interaction contributes to the

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particle attachment.62 A recent study by Song et al.61 suggested hydrophobic interactions are

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responsible for the increased deposition onto hydrophobic surfaces with increasing

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hydrophobicity of Ag nanoparticles. As oleic acid bilayer coating is actually amphiphilic,33 we

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propose that the increased deposition rate onto polystyrene is due to the additional hydrophobic

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interactions55 between the hydrophobic portion of the coating with the polystyrene sensor surface

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(which also has less surface charge than silica).56 However, the exact mechanisms behind the

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hydrophobic interactions (nanoparticle-surface) are still not fully understood.63-65 The relative

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higher deposition attachment efficiencies of engineered OA-IONPs onto the polystyrene surface

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indicate that the transport and fate of these nanoparticles will be greatly influenced by the

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hydrophobic surfaces in the environment (e.g. oil, NAPL or natural organic matter). In another

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word, if transportation of these engineered IONPs in the subsurface could reach to a target

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volume, favorable in-situ partitioning at oil / NAPL is likely.

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Deposited Layer Stiffness and Stability

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Along with measuring frequency changes, thus mass deposition changes, QCM-D can also

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measure the change in dissipated energy during and after particle deposition events.60 The slope

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of D to f (&∆'"%# ⁄∆"%# &) can be used as an estimation of the induced energy dissipation per

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coupled mass change – which is a measure of particle size and particle-surface contact stiffness

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for films of discrete nanoparticles.55, 66-68 Here, the slope of D to f exhibited a linear relationship

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(R2 ≥ 0.99, SI Figure S9) for most cases except at very low ionic strength due to negligible

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Therefore, &∆'"%# ⁄∆"%# & was calculated for all the

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deposition mass on the sensor surface.

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deposition experiments except for deposition at very low electrolyte concentrations. The trends

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of &∆'"%# ⁄∆"%# & as a function of NaCl and CaCl2 are presented in Figure 6. For nanoparticle

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deposition onto the silica surface, &∆'"%# ⁄∆"%# & increased with increasing electrolyte

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concentration for both NaCl and CaCl2. The interactions of aggregated nanoparticles with the

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silica surface become increasingly dissipative and therefore, &∆'"%# ⁄∆"%# & values increase – in

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other words, the layer becomes more loosely attached to silica with increasing ionic strength due

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to formation of large aggregates.69

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coated surfaces are lower than the values on silica surfaces. Interestingly, the &∆'"%# ⁄∆"%# & of

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nanoparticle deposition on the polystyrene surface is much lower than for a silica surface in the

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presence of NaCl and CaCl2, indicating the nanoparticles were more rigidly attached onto the

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polystyrene surface as compared to the silica surface. This phenomenon is hypothesized to be in

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part, due to stronger hydrophobic interactions,55,

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attachment of aggregated nanoparticles onto the polystyrene surface.

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electrolyte concentrations and types, the &∆'"%# ⁄∆"%# & value on the polystyrene surface remains

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constant, which suggests the stiffness of the nanoparticles’ attachment is independent to the

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addition of salt and surface chemistry. These observations are in good agreement with Chang et

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al.’s study which highlights the role of sensor surface chemistry with regard to nanoparticles

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deposition.55

Under non-repulsive conditions, &∆'"%# ⁄∆"%# & on PLL

61

as discussed above, leading to the rigid Moreover, under all

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To further evaluate the properties of the sorbed layer, experiments were designed to measure

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the effective particle release after favorable deposition60 had occurred. OA-IONPs were first

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deposited onto the silica surface at favorable deposition rate conditions (500 mM NaCl and 7.5

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mM CaCl2, respectively) and then the (flowing) aqueous solution chemistry over the deposited

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layer was changed (termed the rinse solution) to investigate the stability of the sorbed layer and

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release of nanoparticles back into solution. For silica surfaces (Figure 7a), the rinse solutions

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used here include the corresponding buffer, 1 mM NaCl, water buffered at pH 7.2 and water

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buffered at pH 12. A partial increase of frequency is observed in Figure 7a where the rinse

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solution is changed from 500 mM NaCl (step D) to 1 mM NaCl (step E), indicating release of

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sorbed particles when the solution chemistry changed. However, with the initial 7.5 mM CaCl2

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based suspension, no obvious frequency change is observed (less than 2 % of mass change

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calculated with Sauerbrey model, Figure 7b and SI Table S1), thus indicating a stable deposition

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layer regardless of the changes in water chemistry. As discussed, previous studies have shown

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that Ca2+ can bind to two adjacent carboxyl groups, acting as a bridge, which leads to a more

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stable deposited layer.43, 70, 71 The negative frequency shift in step G was due to the increase in

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viscosity/density in water solution buffered at high pH.34 These results indicate that the sorbed

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layer properties can also be functions of both ionic type71 and surface, and that the initial

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conditions are critical, as we observed the majority of sorbed layers, for all cases, remain (mass

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retained) even after the rinse solution changed back to MilliQ water. Such observations are

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important when considering particle transport over long distances or times as heterogeneities

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with regard to local ionic strength/type and surfaces may act as effective surface (particle) sinks.

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On the other hand, if a stable, rigid (deposition) layer is desirable, divalent or even trivalent

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cations may be useful in application.

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In summary, this work fundamentally describes the role of two typical cations, Na+ and Ca2+,

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on the aggregation, deposition and corresponding release of engineered iron oxide nanoparticles

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(IONPs) with two model surface types (hydrophilic vs. hydrophobic).

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quantitatively describe and discern the effects of different cations and ionic strength, which

Measurements

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strongly affect the stability of nanoparticles and thus their function with regard to particle

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deposition and release onto/from different, model environmental surfaces. Data sets indicate

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these OA-IONPs will be relatively stable in groundwater conditions as the Na+ is typically 1-10

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mM and Ca2+ is typically 0.1-2 mM.53 However, based on this and other studies, it is still

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difficult to control the stability and deposition of engineered IONPs under extreme conditions,

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particularly at high salinity (IS > 1 M) as found, for example in brine aquifers or some petroleum

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reservoirs.46 Additionally, sensor surface (coatings) also proved to be critical factors governing

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the deposition rates of these nanoparticles onto environmental surfaces.

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observed a greater affinity, in all cases, for these nanoparticles to associate with the more

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hydrophobic surface and that oleic acid coatings are quite sensitive to the presence of calcium.

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In particular, we

To conclude, aqueous application (e.g. sensing, remediation, etc.) of highly controlled,

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magnetic engineered nanoparticles remains relatively nascent.

This work provides new

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fundamental knowledge and understanding for such applications and beyond, while underscoring

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complexities associated with nanoparticle behavior in multiphase systems (here as water-solid

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interfaces). The authors certainly recognize that natural environments will be more complicated

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than systems presented, based on the presence of NOM, redox reactions (resulting in particle

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aging), (bio) molecules, among others, which all add to the uncertainty of extrapolation with

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regard to real world understanding and accurate prediction of aggregation and deposition

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processes.27

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specifically discerning the role of environmental aging and the presence of NOM for similar

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IONPs aggregation and deposition behaviors.

Accordingly, ongoing research is being conducted to investigate such factors,

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377 378

Figure 1. TEM micrographs of the as-prepared 8 nm IONPs in (a) hexane and (b) water. All

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scale bars are 50 nm.

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380 381

Figure 2. Zeta potentials of OA-IONPs over a range of NaCl and CaCl2 concentrations under pH

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7.2. Each data point shows the mean of 30 measurements of triplicate samples, where the error

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bars represent standard deviations.

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Figure 3. Attachment efficiency (α) of OA-IONPs as functions of (a) NaCl and (b) CaCl2

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concentrations at pH 7.2.

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measurements is 710 mM NaCl and 10.6 mM CaCl2 for OA-IONPs. The lines are extrapolated

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from the reaction-limited and diffusion-limited regimes, and the intersections show the

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respective CCC values.

The critical coagulation concentration (CCC) based on the

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390 391

Figure 4. Deposition rates (frequency shift rates) of OA-IONPs in the presence of (a) NaCl and

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(b) CaCl2 onto silica and polystyrene sensor surfaces. Insets: deposition rates under favorable

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conditions. Each data point shows the average of duplicate or triplicate measurements, where the

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error bars represent standard deviations.

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Figure 5. Deposition attachment efficiency (αD) of OA-IONPs in the presence of (a) NaCl and (b)

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CaCl2 onto silica and polystyrene sensor surfaces. The lines are extrapolated from the

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unfavorable and favorable deposition regimes, and the intersections show the respective critical

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deposition concentration (CDC) values.

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400 401

Figure 6. &∆'"%# ⁄∆"%# & of OA-IONPs deposition in the presence of NaCl and CaCl2 onto PLL,

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silica and polystyrene surfaces.

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403 404

Figure 7. Stability of deposited OA-IONPs layer over different rinse solutions when the layer

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was formed in the presence of (a) 500 mM NaCl and (b) 7.5 mM CaCl2. Baseline was first

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established in MilliQ water (A) and corresponding electrolytes (B), before the nanoparticles are

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deposited onto the silica surface (C). The system is then rinsed in the respective electrolytes (D),

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1 mM NaCl at pH 7.2 (E), MilliQ water at pH 7.2 (F), and finally, MilliQ water with pH adjusted

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to 12 (G).

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ASSOCIATED CONTENT

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Supporting Information. Detailed synthesis and phase transfer of iron oxide nanoparticles,

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QCM-D sensor cleaning protocols, QCM-D deposition experiment, DLVO calculations, nine

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figures (nanoparticle size distribution, DLS size of nanoparticles, aggregation profiles, DLVO

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interaction energy profiles, DLVO predictions, QCM-D deposition experiments, and

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representative D/f ratio) and one table are available free of charge via the Internet at

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http://pubs.acs.org.

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AUTHOR INFORMATION

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Corresponding Author

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*To whom correspondence should be addressed:

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John D. Fortner: Tel: +1-314-935-9293; Fax: +1-314-935-5464; Email: [email protected]

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Funding Sources

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The authors would like to thank the American Chemical Society’s Petroleum Research Fund

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(#52640-DNI10) and the National Science Foundation (CBET, #1236653) for supporting this

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work.

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ACKNOWLEDGMENT

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This work was supported by American Chemical Society’s Petroleum Research Fund and the

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National Science Foundation. TEM, DLS facilities were provided by the Nano Research Facility

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(NRF) at Washington University in St. Louis, a member of the National Nanotechnology

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Infrastructure Network (NNIN), which is supported by the National Science Foundation under

430

Grant No. ECS-0335765.). We also thank Mr. Carl H. Hinton for his contributions to this work.

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