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Environ. Sci. Technol. 2002, 36, 184-189
Effect of Molecular Scale
Roughness of Glass Beads on
Colloidal and Bacterial Deposition
KARL SHELLENBERGER AND
BRUCE E. LOGAN*
Department of Civil and Environmental Engineering,
The Pennsylvania State University,
University Park, Pennsylvania 16802
Molecular-scale surface roughness and charge heterogeneity have been hypothesized as factors that can affect
the deposition rates of colloids during their transport in
porous media. To test their relative importance, a single
batch of cleaned glass beads was divided in half and
chemically treated with acid or base to alter surface
roughness. Analysis of the topography of 20 glass beads
with an atomic force microscope (AFM) indicated that the
chromic acid-treated (rough) beads had a root-meansquare roughness of 38.1 ( 3.9 nm, while the sodium
hydroxide-treated (smooth) beads had root-mean-square
surface roughness of 15.0 ( 1.9 nm. AFM force volume imaging
of glass bead surfaces did not reveal surface charge
heterogeneity. Filtration experiments with inorganic colloids
(latex microspheres, 1 µm diameter) consistently demonstrated that there was a greater retention of latex
microspheres on rough than smooth glass beads suspended
in either low (10-5 M) or higher (10-1 M) ionic strength
(IS) solutions. Collision efficiencies for rough beads were 3050% larger than for smooth beads. Collision efficiencies
of bacteria using rough glass beads were also equal to or
greater than those measured for smooth beads. In
experiments with the perchlorate-reducing bacterial
isolate KJ, collision efficiencies were significantly greater
on rough rather than smooth beads for two different
ionic strength solutions (IS ) 0.05 or 1 M). In another
case (IS ) 0.1 M) for KJ, and in filtration experiments with
E. coli, collision efficiencies were not significantly different
between the rough and smooth beads. We hypothesize
that the consistently greater deposition rates of microspheres,
but not bacteria, on rough rather than smooth beads are
due in part to the presence of polymers on the surfaces of
bacteria.
Introduction
An understanding of the chemical and physical factors
influencing bacterial adhesion can lead to greater control of
the fate and transport of bacteria in subsurface environments.
Reducing bacterial adhesion can increase the success of
bioremediation of contaminated soils and aquifers. To widely
disperse pollutant-degrading bacteria via bioaugmentation,
the ionic strength of the water can be lowered (1-3), or
nonionic surfactants can be added to the cell suspension (4,
5), or low-adhesion isolates can be obtained from monoclonal
* Corresponding author phone: (814)863-7908; fax: (814)863-7304;
e-mail: [email protected].
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populations (6-8). Alternatively, increasing the adhesion of
bacteria can be used to limit the migration of pathogenic
bacteria in groundwater aquifers.
The chemical properties and morphology of a surface are
important factors for understanding bacterial adhesion rates.
Metal oxides and clays can increase deposition rates of
negatively charged particles such as bacteria, although natural
organic matter can partially ameliorate these effects (9-11).
Even on cleaned and highly spherical glass beads, however,
it has been speculated that charge heterogeneities produce
localized, highly favorable sites for attachment (12-15). There
is experimental evidence of slowly increasing breakthrough
during injection of colloids into a packed medium that
support the hypothesis of favorable sites (16), and computer
models designed to account for surface heterogeneity support
this mechanism (14). Cleaning glass bead and quartz particles
can alter deposition rates (5, 16) providing indirect evidence
of different types of deposition sites. However, favorable
deposition sites for bacteria have never been directly
measured on cleaned glass beads.
While strong acids can be used to clean glass and quartz
surfaces they also can etch the surface and increase surface
roughness. The importance of molecular-scale roughness
has never been systematically investigated in laboratory
filtration experiments, although it is generally accepted that
particle irregularity is an important factor in colloid transport
(12, 17, 18). For example, under identical colloid and solution
chemistry conditions greater collision efficiencies of colloids
are produced with irregularly shaped quartz particles than
with regularly shaped spherical glass beads (5), and relatively
rough composite polyamide reverse osmosis membranes
(protrusions of several hundred nm) foul faster than smoother
cellulose acetate membranes (protrusions of only a few nm)
(17, 19). Models of surface roughness have shown that DLVO
interaction energy profiles for rough surfaces (protrusions
on the order of 1-5 nm) deviate significantly from those
derived assuming smooth surfaces (18).
To directly measure whether surface roughness and charge
heterogeneity could affect colloid transport in porous media,
we measured the overall retention of three different particles
(two bacteria and latex microspheres) in minicolumns
experiments using rough and smooth glass beads. An atomic
force microscope (AFM) was used to probe surface topography (roughness) and charge distribution of glass bead
surfaces at molecular scales. The dimensions of the end of
some AFM tips (as low as 2-10 nm (20)) make it possible to
scan extremely small surface protrusions and adsorbed
materials such as humic acids on surfaces (21-23). Measurements of the forces between the tip and the surface obey
DLVO model predictions of colloid-surface interactions with
respect to pH and ionic strength if the pyramid-shaped tip
is defined as a spherical colloid in the range of 100-400 nm
(24). Therefore, we used the AFM to probe the surface of
glass beads to determine if we could measure charge
heterogeneities across the surface of the glass beads.
Methods
Glass Beads. A single batch of soda-lime glass beads 500750 µm in diameter (Polysciences, Inc., Warminster, PA) was
cleaned with 1 N H2SO4 (25), split into two batches, and
further treated to alter surface roughness. To increase
roughness, glass beads were successively soaked for 24 h
and rinsed with deionized water (Milli-Q, Millipore Corp.,
Bedford, MA) in the following: 36.5-38% HCl, 10% H2CrO4,
36.5-38% HCl, and dried (16). To make beads smoother they
were soaked in 12.5 M NaOH for 30 min and then rinsed with
10.1021/es015515k CCC: $22.00
 2002 American Chemical Society
Published on Web 12/13/2001
ultrapure water. Electrophoretic mobility measurements of
the beads were not made because the beads would need to
be crushed to reduce particle sizes, altering the exposed
surface area.
Analysis of Surface Roughness. A Digital Instruments
(DI; Santa Barbera, CA) atomic force microscope mounted
on an inverted Olympus IX70 optical microscope (Bioscope;
Nanoscope III software, versions 4.23 and 4.32) was used to
measure surface roughness and probe surface charge distribution. Glass beads were bonded to glass microscope slides
with epoxy (Devcon 2-Ton Crystal Clear Epoxy) and surface
roughness measured with contact-mode imaging in air using
standard silicon nitride tips (type DNP; Digital Instruments)
with a radius of curvature of 20 to 60 nm (20).
Tip deflection data was converted to root-mean-square
height, RMS, using the DI software, calculated as
RMS )
[(zi - zavg)2]1/2
N
(1)
where zi and zavg are the individual height values and the
average (datum) height, respectively, and N is the number
of samples. Because the surface of a glass bead is curved,
height changes produced by this curvature were eliminated
before calculating the RMS. To remove the surface curvature,
each individual AFM trace over a surface was adjusted by
fitting the arc of the data based on a circle of radius R and
then subtracting the height due to the arc of the circle as
z ) z0 + [R2 - (x - x0)2]
(2)
where x and z are the x- and z-coordinates of a point on the
arc of a circle, and x0 and z0 are the coordinates of the center
of the circle. Adjusting the height data produced a flat trace
of surface deflection data that was then quantified in terms
of the RMS heights using eq 1.
Surface Charge Heterogeneity. The distribution of charge
on the surface of a glass bead in Milli-Q water was examined
by measuring the interaction force between the negatively
charged AFM tip and the glass surface using force volume
(FV) imaging (DI software version 4.23). To create a FV image,
a section of the surface was imaged in contact mode and
divided into an F×F matrix, and a force curve was obtained
in the center of each grid box. A force curve is a plot of the
location of the tip, while the tip is lowered to the surface as
a function of the distance the cantilever is lowered. Attraction
or repulsion between the tip and the surface is demonstrated
by the tip being pulled down to, or pushed away from, the
surface, resulting in a deviation from a linear relationship
between the tip position with the cantilever displacement.
Once the tip hits the surface, the cantilever continues to be
lowered for a short period producing the “constant compliance” region where the tip does not move but the laser is
deflected due to the bending of the cantilever. The tip is then
retracted, and the cantilever is moved to the next point in
the sampling matrix. The location of the surface in a force
plot is obtained as the intersection between two straight lines
generated from the constant compliance region and the
approach region (zero interaction force) in a force plot (26).
Tip deflection data were converted to forces (nN) using
Hooke’s Law, or F ) -kx, where k the spring constant (N/m),
and x is the deflection (nm). The spring constant was
calculated for each cantilever using DI software (Nanoscope
III v. 4.3.2) based on the Cleveland method (27). All force
curves were measured in deionized water (Milli-Q, New
Bedford, MA). The origin was manually reset for some force
curve data (as indicated) by exporting data to a specialized
graphics program and identifying the intersection of the
constant-compliance and zero-force lines (26, 28).
When all force curves are combined, a FV image is
produced that depicts the location (deflection) of the tip at
a given height from the surface (29). When the surface is
smooth, these heights can be used to measure the relative
attraction or repulsion between the tip and the surface based
on the tip location relative to the surface. Using the FV image,
we hypothesized that it would be possible to find areas of
a surface that held greater attraction or repulsion of the
negatively charged AFM tip than other areas, providing a
map of more or less favorable deposition sites for negatively
charged colloids and bacteria.
Bacteria and Microspheres. Two strains of bacteria were
used: Escherichia coli HCB137 (30) and Dechlorosoma sp.
KJ (31, 32). HCB137 is a nonmotile mutant of a well
characterized chemotactic strain that has been used to
understand the motion of bacteria near surfaces (30). HCB137
cells are 3 µm × 1 µm (equivalent spherical diameter of 1.8
µm). Cell suspensions were grown using 30 g/L of tryptic soy
broth (TSB, Sigma Chemical, Co., St. Louis, MO) and
harvested during the mid- to late-exponential growth phase.
KJ is a newly isolated Gram negative bacterium that respires
using perchlorate (31) and has been examined for bioremediation of perchlorate-contaminated waters (32). KJ cells
are 2 µm × 1 µm (equivalent diameter of 1.5 µm). Cell
suspensions were grown aerobically on acetate (1 g/L) in a
mineral salts medium and harvested during the late exponential growth phase (33).
Bacteria retained in column experiments described below
were counted using a radiolabeling technique (4, 34, 35).
3H-leucine ((1 miCu/mL); 40 µL/100 mL; ICN Biomedicals)
was added to a washed cell suspension of E. coli in 0.1 M KCl
and incubated at room temperature for 6 h. For KJ suspensions, radiolabeled leucine was added directly to the growth
medium, and the cells were allowed to take up the label
during growth.
Fluorescent carboxylated latex microspheres 1.0 µm in
diameter (Polysciences) were washed three times by centrifugation using Milli-Q water. To correlate radiolabel
measurements to actual cell numbers, bacteria were stained
with acridine orange, and both bacteria and microspheres
were counted on prestained black filters (polycarbonate, 0.4
µm pore diameter; Osmonics Corp.) with a microscope (BH2; Olympus Corp.) equipped for fluorescence under blue light
at 1000×.
Column Studies. Minicolumn experiments with three
different particles (radiolabeled bacteria or fluorescent
microspheres) were conducted as described previously (34).
Briefly, columns made from the barrels of 3 cm3 syringes (0.8
cm inner diameter) were packed with 1.5 g of glass beads
supported by two GF/C filters (1.2 µm nominal pore size;
Whatman) and attached to a vacuum box. Each filtration
experiment (triplicate columns) consisted of the following:
10 mL of rinse solution, 5 mL of sample containing either
radiolabeled bacteria or latex microspheres, and 10 mL of
rinse solution. The columns were then vacuumed until they
were dry. Filtration experiments were conducted with influent
concentrations of either 107 cells/mL or 108 microspheres/
mL. Particles were suspended in deionized water having an
ionic strength of ∼10-5 M (Milli-Q water) or solutions set at
different ionic strengths (0.05 or 0.1 M) using CaCl2.
The number of retained particles were counted by
extruding the column packing with a syringe plunger and
cutting the top 1 cm of the column into three sections.
Microspheres were removed from the glass beads by sonication (Bransonic 1210 Ultrasonic Cleaner) for 3 min in a
surfactant solution (Tween 20, 0.1%) that was then filtered
through black filters for microscopic counting. Direct examination of the glass beads after sonication revealed a small,
but insignificant, number of microspheres remained on the
beads. Cell suspensions (2 mL) or column packing from a
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FIGURE 2. Traces used to determine average roughness values for
the rough and smooth beads.
FIGURE 1. AFM images of glass bead surfaces: (A) smooth bead
and (B) rough bead.
filtration experiment were combined with 10 mL of scintillation cocktail (CytoScint, ICN Biomedicals) and analyzed
by liquid scintillation counting (RackBeta 1217, LKB-Wallac).
The retention of unassimilated radiolabel in the column was
accounted for by conducting parallel filtration experiments
using filtrate from cell suspensions as previously described
(5, 34, 35).
Filtration theory was used to model particle retention in
the packed minicolumns (36). The particle collision efficiency,
R, is defined as the fraction of collisions between a particle
and a collector (glass bead) that are successful. By measuring
the fraction of particles that are retained in the column, FR,
the collision efficiency can be calculated (36, 37) as
R)
-2dc ln(1 - FR)
3(1 - θ)ηL
(3)
where dc ) 500 µm is the diameter of the glass beads, θ )
0.4 the porosity of the medium, η, the collector efficiency,
is calculated using the Rajagopalan and Tien model (36),
and L is the length of the column (or slice).
Results
Glass Beads Roughness. Glass bead surfaces treated with
sodium hydroxide were smoother than those soaked in
chromic acid as shown in Figure 1 for 30 µm × 30 µm sections
of the bead analyzed with contact mode AFM. Duplicate
scans of 20 beads (10 rough, 10 smooth) were transformed
to remove surface curvature and analyzed for roughness as
shown in Figure 2. Based on data from 20 scan lines for each
batch of beads, the RMS heights of the sodium hydroxidetreated beads (smooth beads) was 15.0 ( 1.9 nm and the
chromic acid-treated beads (rough beads) was 38.1 ( 3.9
nm.
Filtration Experiments with Microspheres. There was a
greater retention of microspheres on rough than smooth
beads suspended in either low (10-5 M) or higher (10-1 M)
ionic strength solutions. Collision efficiencies measured in
three sections of the column for rough beads under low ionic
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FIGURE 3. Collision efficiencies for latex microspheres measured
in minicolumn experiments using rough or smooth beads as a
function of solution ionic strength (IS) under clean bed conditions:
(A) C0 ) 108 mL-1, IS ) 10-5 M and (B) C0 ) 107 mL-1, IS ) 10-1
M. (Error bars based on (SD of columns run in triplicate.)
strength conditions were on average 30-40% larger at low
ionic strength and approximately 50% larger at the higher
ionic strength than those on smooth beads (Figure 3). The
higher retention of microspheres on the rough rather than
the smooth beads at 10-5 M was verified in separate
experiments by placing glass beads from the column on a
microscope slide and counting microspheres on the upper
half of the glass bead using fluorescence microscopy (28).
Greater retention on rough than smooth beads only
occurred if the microspheres did not occupy a large fraction
of the surface area or under “clean bed” conditions (38). As
shown in Figure 4, there was no difference between the
retention of microspheres on rough and smooth glass beads
in filtration experiments under conditions (108 mL-1; IS )
0.1 M) that resulted in a high surface loading (4.3-5.6%
surface area, assuming perfect spheres). Others have shown
that surface coverages of only 4-5% (microspheres) and
8-9% (bacteria) are sufficient to completely cover or “block”
surfaces (39, 40).
Collision efficiencies larger than unity were observed in
some of these experiments, but others have also found R >
1 (25, 36, 41, 42) indicating that the Rajagopolan and Tien
Model filtration equation underpredicted the frequency of
collisions.
Filtration Experiments with Bacteria. In all filtration
experiments with bacteria, the overall average retention of
bacteria was higher on rough rather than smooth glass beads
(Figure 5). However, these differences were not always
FIGURE 4. Collision efficiencies of latex microspheres measured
in minicolumn experiments using rough or smooth beads producing
a high surface loading of 4.3 to 5.6% coverage in the top slice of
a column. (C0 ) 108 mL-1, IS ) 0.1 M. Error bars based on (SD of
columns run in triplicate.)
FIGURE 6. Force volume image (approach curves) of 50 × 50 µm2
surface of a smooth glass bead.
FIGURE 7. Comparison of individual force curves taken from areas
of greatest apparent differences, defined as “light” and “dark”
regions in Figure 6.
FIGURE 5. Collision efficiencies for bacteria measured in minicolumn experiments using rough or smooth beads at different ionic
strengths: (A) KJ and (B) E. coli. (Error bars based on (SD of
columns run in triplicate; symbols without error bars are single
measurements.)
significant in minicolumn tests due to low values of R and
variability between replicate columns. At ionic strengths of
0.05 and 1 M, the collision efficiency for KJ suspensions was
40 and 54% larger on the rough beads than those on the
smooth beads (Figure 5A). At an ionic strength of 0.1 M, R
was 23% larger on average, but the error bars ((SD between
triplicate columns) overlapped. Overall, there appeared to
be no trend in R with ionic strength.
In filtration experiments with E. coli, a trend of increasing
retention with surface roughness was again observed, but
results were not significant (Figure 5B). A combination of
relatively little uptake of the radiolabel and low collision
efficiencies (0.02 e R e 0.05) resulted in large variations in
R. At solution ionic strengths of 0.05 and 0.1 M bacterial
deposition was larger on average for the rough beads than
for the smooth beads, but the error bars overlap indicating
the results were not significant. At the lowest ionic strength
(IS ) 10-5 M) deposition on the rough beads was too low to
be measured. Repeated experiments with these bacteria at
all three ionic strengths produced similar results of higher
average deposition on the rough than smooth beads and low
deposition rates in the 10-5 ionic strength experiment. We
were unable to reduce the error in deposition measurements
for E. coli prior to the exhaustion of our supply of the two
batches of glass beads.
Probing Surfaces using Force Volume Imaging. Force
volume imaging of glass bead surfaces initially appeared to
suggest the presence of surface heterogeneities, but a
thorough examination of force curves did not support the
presence of charge heterogeneities on these surfaces. A typical
FV image of a 50 µm × 50 µm area of a smooth glass bead
is shown in Figure 6. This surface is separated into a 64 ×
64 grid of force curves for a total of 4096 individual force
curves, with each force curve composed of 64 points (the
maximum number possible with this AFM software for this
number of force curves). Assuming a tip radius of 20-60 nm
for this tip (20), this means that 0.21% to 1.85% of the surface
in each grid box was sampled for each force curve. The gray
scale of each grid point indicates the magnitude of the
interaction force between the AFM tip and the surface during
the approach of the tip to the surface. Thus, a light color
should indicate a small repulsive force and a dark color should
indicate a large repulsive force.
While the light/dark variations shown at different grid
points in Figure 6 apparently support the presence of large
differences in tip-surface forces and therefore surface charge
heterogeneity, offline analysis of the FV data does not.
Individual force curves from three random “light” and “dark”
grid points are shown in Figure 7. The location of the surface
of the bead can be identified as the intersection of two lines
formed from the force measurements taken at far distances
from the surface (right side of figure) and after the tip has
contacted the surface (far left of figure). After superimposing
the six curves as shown in Figure 7, it can be seen that at the
resolution of these scans there was no difference in the forces
measured between the tip and the glass bead surface. This
indicates that the apparent differences in force by the FV
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image shown in Figure 6 is really due to a comparison of the
force curves at different points relative to the surface and
not differences in interaction forces. Therefore, we were
unable to detect any differences in charge distribution using
the FV imaging technique.
Discussion
Collision efficiencies measured for latex microspheres in
filtration experiments were consistently higher for glass beads
with an average roughness of 38.1 ( 3.9 nm than for those
with an average roughness of 15.0 ( 1.9 nm. The roughness
of the glass beads also contributed in some cases to increased
deposition of bacteria. Collision efficiencies were significantly
larger for strain KJ on rough rather than smooth beads at
ionic strengths of 0.05 and 1 M; in three other experiments,
there was no significant difference between rough and
smooth beads. These results for microspheres and bacteria
demonstrate that molecular-scale surface roughness can
affect colloid deposition, but that this effect is colloiddependent.
Microspheres do not have long polymers on their surfaces
and thus interact with the glass beads in a different manner
than bacteria. The size of protrusions from glass beads makes
them relevant to sizes of polymers on the surface of bacteria
and the thickness of the electrostatic repulsive layer. Protrusions from the rough glass beads averaged 38.1 nm but ranged
up to 200 nm. These heights can be compared to the repulsive
layer thickness characterized by the inverse of the DebyeHuckel parameter (43). At an ionic strength of 10-5 M at 20
°C, the repulsive layer thickness is 43 nm, but it decreases
to 1.4 nm for a 0.1 M solution. In order for approaching
colloids not to be repelled by the protrusions themselves, we
hypothesize that these protrusions on negatively charged
glass bead surfaces carry insufficient overall charge to deflect
approaching negatively charged microspheres. These nanoscale glass bead protrusions probably penetrate the repulsive
layer around the micron-sized colloids and initiate contact.
Thus, we observed (Figure 3) consistently greater overall
deposition of microspheres on glass surfaces with larger
protrusions (rough beads) than on surfaces with smaller
protrusions (smooth beads). However, when the colloidal
particle was a bacterium, which has polymers on its surface,
there was a less clear relationship between deposition and
surface roughness.
It is well accepted that the overall properties of the colloids,
such as electrophoretic mobility and surface hydrophobicity,
are important determinants of the probability of colloid
adhesion to a glass surface (44). However, these two properties
alone are insufficient to predict R, indicating other factors
are necessary to explain bacterial adhesion (45). The interaction of the glass bead protrusions with a bacterium is more
difficult to understand than with latex microspheres due to
the polymers on the surface of the bacterium. E. coli have
well characterized surface lipopolysaccharide (LPS) polymers
that extend 3.8 to 42.5 nm into solution (46) and therefore
are similar in length to the glass bead surface protrusions.
AFM measurements suggest that EPS (extracellular polysaccharides) on other bacteria (Pseudomonas putida KT2442,
Burkholderia cepacia G4) can span much larger distances of
230-1040 nm (47). AFM measurements also show that these
polymers can repel or attract the negatively charged pyramidshaped AFM tip when the tip approaches the bacterial surface
(35, 48, 49). This suggests that polymers could increase or
decrease the probability of attachment during an initial
collision with a nanosized glass bead protrusion. However,
if a collision occurs, there can be a strong adhesion force
holding the bacterium at the surface. When an AFM tip
contacts a bacterial surface there is a large attractive force
that holds the tip at the bacterial surface. Although the AFM
tip is not identical to glass bead protrusions in size and
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chemical composition, both are negatively charged pyramidshaped surfaces. AFM experiments have shown that once
the AFM tip contacts a bacterial surface the force holding
the tip on the cell is greater than attractive or repulsive forces
measured during the tip approach. Thus, the presence of
these polymers may alter the outcome of a bacterium
interaction with a rough surface compared to those occurring
with a relatively smooth latex microsphere.
Charge heterogeneities did not appear to be a factor in
bacterial or microsphere attachment to cleaned glass surfaces
since localized areas exhibiting differences in attractive or
repulsive forces could not be measured using the AFM.
Whereas surface charge heterogeneity cannot be eliminated
as a factor in bacterial deposition rates to surfaces, if such
heterogeneities exist, they must be present at scales smaller
than those of the AFM tip dimensions.
Given the scale of surface protrusions relative to the
minimum detectable dimension for surface heterogeneities,
we conclude that surface roughness is the critical factor in
determining favorable, versus less favorable, sites of attachment on cleaned glass surfaces. The importance of surface
roughness is also likely manifest at larger dimensions as
irregular particles are known to produce greater bacterial
deposition than on more spherical particles (5). Including
molecular scale roughness and particle surface geometrical
effects in filtration models should lead to a more accurate
prediction of particle transport and deposition rates in porous
media.
Acknowledgments
This publication was supported by grant CHE-0089156 from
the National Science Foundation (NSF) and by ES-04940 from
the National Institute of Environmental Health Science,
NIEHS. Additional funding for the AFM was provided in part
by NSF/IGERT DGE-9972759. The contents of this paper are
solely the responsibility of the authors and do not necessarily
represent official views of a funding agency. We thank S.
Pardi for assisting with microsphere counts, T. Camesano
for assistance with AFM measurements, and M. Elimelech
and T. Camesano for comments on an earlier manuscript.
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Received for review May 4, 2001. Revised manuscript received September 18, 2001. Accepted October 17, 2001.
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