The document outlines a new method to determine the concentration of iron oxide nanoparticles on the surface of oil droplets in a Pickering emulsion using fluorescence confocal microscopy. Intensities observed from fluorescently tagged nanoparticles in water samples are used to map intensities to known concentrations, which can then determine surface concentrations on oil droplets. Preliminary results analyzing intensities of oil droplet surfaces and oil-water interfaces across emulsions of varying nanoparticle concentrations in water are presented, though variations and potential sources of error are noted that require further exploration.

1. Pickering Emulsion: Nanoparticle Surface Concentrations
Erin Blauvelt,∗
O.N.e O’Neill, and Daniel H. Ou-Yang
Lehigh Department of Physics
(Dated: July 31, 2015)
We are developing an outline for a new method of determining the concentration of nanoparticles
(Fe3O4) on the surface of an oil droplet (hexyl-decanol) in a water and oil Pickering emulsion. We
use fluorescently tagged nanoparticles in our experiments. By observing our nanoparticles suspended
in water using fluorescence confocal microscopy, we are able to determine a relation between the
observed nanoparticle intensity and the nanoparticle concentration. We obtain intensities across
the full vertical sweep of a sample on a microscope slide and observe a gradient distribution. Using
a method of sampling the observed gradient, we can make estimates in determining the intensity
for a known concentration of nanoparticles in water. If we can obtain reliable intensities for droplet
images, through this intensity to concentration mapping, we can determine the surface concentration
of nanoparticles on droplets in our emulsion. We provide a table of observed oil droplet surface
intensities and oil water interface intensities, discuss the results, and offer ways to move forward
with the project.
1. PICKERING EMULSIONS
Emulsions are the stable mixture of two liquids which
are not generally able to mix with one another, such as
oil and water. Classically surfactants are used to stablize
emulsions of immiscible liquids. However solid particles
can be used, this is called a Pickering emulsion. Fig. 1
below shows the basic structure of emulsifiers around an
oil droplet in both a classical and Pickering emulsion. See
the review by Chevalier and Bolzinger Emulsions stabi-
lized with solid nanoparticles: Pickering emulsions Col-
loids and Surfaces A: Physicochem. Eng. Aspects 439
(2013) 2334, from which Fig. 1 was obtained, for a nice
introduction to the basics of Pickering emulsions.
FIG. 1: Oil droplets in water for a classical emulsion and for
a Pickering emulsion (Chevalier and Bolzinger 2013).
Classical emulsions using surfactants have shown some
undesirable characteristics in their use in cosmetics and
pharmaceuticals. In most applications Pickering parti-
cles can be substituted for surfactants in classical emul-
sions. Pickering emulsions using solid particles as an
emulsifier may provide a way to avoid some undesir-
able effects (such as irritation and chemical waste) that
can come along with using surfactants. (Chevalier and
Bolzinger 2013).
Another point of interest is the potential to easily re-
∗Electronic address: ekb215@lehigh.edu
cover an emulsifier, Pickering particles may be a can-
didate for this. Particles with magnetic properties can
be extracted from an emulsion using magnets. The iron
oxide nanoparticles used in our experiment have mag-
netic properties, allowing for a method for extracting and
reusing this emulsifier to be developed.
In our experiments we seek to determine the surface
concentrations of nanoparticles on oil droplets in our
emulsion. Understanding the surface concentration of
nanoparticles on the surface of oil droplets in our emul-
sion will help us to better understand the interaction of
nanoparticles at the interface between oil and water. This
determination will help to form a better picture of the
basic structure of our emulsion. We use fluorescence mi-
croscopy to examine the concentration of the nanopar-
ticles in water and on the surface of oil droplets in an
emulsion. This method of observation has many aspects
to explore for use in the study of Pickering emulsions.
2. MATERIALS AND EXPERIMENTAL SETUP
2.1. The Emulsion
FIG. 2: A sample of iron oxide nanoparticles in water and oil
shown as a stable Pickering emulsion.
In our experimentation we are studying a Pickering
emulsion. This emulsion uses ∼ 155 nm diameter iron
oxide (Fe3O4) nanoparticles from Professor Li as the
emulsifier in oil (hexyl-decanol 97% purity (Aldrich) un-
altered) and water. By combining a nanoparticle and

2. 2
water solution with oil in a container and then shaking
the mixture by hand and with the vortex mixer we get
our Pickering emulsion. One sample of the emulsion is
shown in Fig. 2. The first image shows the kind of 1.5 µL
certifuge vial used to store and agitate the mixture. The
second image gets closer to show the oil (clear and at the
top of the mixture), the emulsion in the middle, and the
reddish nanoparticle water solution at the bottom. The
third image gets a little closer to focus on the droplet like
structure of the emulsion.
2.2. The Microscope
We used an Olympus FV1000 Confocal Micro-
scope to observe the fluorescently tagged iron oxide
nanoparticles in water and on the surface of an oil drop
in an emulsion of water and oil.
It was essential to keep the following settings constant
for all images in which we wish to compare observed in-
tensities. Any adjustment in these settings will either
increase or decrease the intensities observed thus affect-
ing the apparant concentration.
1. Microscope Settings Used:
HighVoltage=670, Gain=1,Offset=0
Laser Intensity=75%
100x lens, N.A. = 1.3
Image size = 320 x 320 pixels, 4 µs per pixel
AlexaFluor 488
3. DATA AND ANALYSIS
3.1. Determining the Nanoparticle Concentration
for Observed Intensities
FIG. 3: An entire intensity sweep across the vertical axis of
the slide, including just above and below the slide.
FIG. 4: Data between the peaks of the intensity observed at
the top and bottom of the slide were used for the fit (green
line).
Determining the concentration of nanoparticles from a
given intensity would seem like a straight forward mea-
surement. One simple way to measure this might be to
place a sample of known concentration under the micro-
scope and observe the intensity given off. However, when
our sample is placed on a microscope slide and under a
slide cover, the resulting intensity is very high at the bot-
tom of the slide. From there, it tapers off exponentially
at first followed by a linear decrease between the bottom
of the slide and the slide cover and then exponentially
grows again near the surface of the slide cover as shown
in Fig. 3.
We used python’s lmfit library to generate a fit to the
curve between the peaks. This fit is shown in Fig. 4.
The fit yielded the following equation that describes the
exponential decay, linear fall off, and exponential growth
of the samples distribution between the slide and the slide
cover:
1
A
C1e
−t
τ
+ C2 + C3t
+ C4e
t
τ2
−C5
.
(1)
Where C1 = 239.971010, τ = 8.41189475, C2 =
329.409672, C3 = -0.11541388, C4 = 1644.68890, C5 = -
38.0137081, and τ2 = 11.6611122 (the associated fit error
still needs to be evaluated here).
To address the parameter A we need to discuss the
benefits of normalizing this function. If we assume that
intensity observed in a sample of a given volume scales
directly with the number of nanoparticles present in the
given volume, we can relate the area under the curve de-
scribed by Equation (1) to the number of nanoparticles

3. 3
present in the total volume of the sample observed or any
subunit of the volume within the gradient. To accomplish
this first, we integrate over the total function from slice
0 to 409 of Fig. 4 and set that equal to one (to represent
100 % of the nanoparticles in the total volume), which
gives us A = 128107.933222337. As the volume scales
directly with the number of nanoparticles in a mixture
where the nanoparticles are evenly spread, we can make
the argument that in a sample that has the nanoparti-
cles evenly distributed through the water we expect to
see the same ratio for one part of volume compared to
the whole volume as the subset of nanoparticle present
in that partial volume compared to the total number of
nanoparticles in the total volume. So for example - using
the aforementioned argument - for a 1.5 µm x 10 µm x 10
µm volume sampled from a total volume of 20.45 µm x
10 µm x 10 µm in which the nanoparticles are evenly dis-
tributed, we expect to see 7.3 % of the total nanoparticles
to be present in that 1.5 µm x 10 µm x 10 µm sample
of the evenly distributed nanoparticle solution. In the
gradient distribution of particles under the slide there is
only one place in which a sample volume of 1.5 µm x 10
µm x 10 µm will contain 7.3 % of the total nanoparticles.
That place is found where the area under the curve over
our fitted function over 1.5 µm (which corresponds to 30
slices) is equal to .073. This is found for slices 125-155
and the value of integrating over slice 125-155 over our
function is .073. Therefore, we take the intensity found
in this range of slices to be the intensity that corresponds
to the concentration of the sample, which for us was 50%
diluted from stock and from this general idea now any
intensity can be mapped to a concentration through the
curve of the gradient distribution (given that the settings
on the microscope listed in the experimental setup sec-
tion remain constant).
We found that most of the middle region is roughly the
same concentration of the original sample. So long as one
stays away from the peaks, a ballpark concentration value
for the intensity can be obtained. However, even in the
linear fall off section the concentration over 10 slides from
50-60 contains 2.52% of the total nanoparticles and the
same sample volume over 350-360 contains 2.26% of the
total nanoparticles. This is gives about a 10% difference
in the number of nanoparticles in the sample volume and
therefore about a 10% difference in the intensity observed
- not trivial!
3.2. Oil Droplet Surface Concentrations
We present summary Table I with a sampling of ob-
served surface concentrations on droplets in emulsions of
varying nanoparticle concentrations in water. The re-
sults appear to fluctuate for unknown reasons. To ob-
tain reliable and reproducible intensities for use with our
concentration to intensity mapping obtained earlier, we
need to understand some of the reasons we see fluctua-
tions across images in the same sample or how a sample
TABLE I: Oil drop surface concentrations observed over a
range of nanoparticle concentrations in water.
Solution Radius Intensity Ratio: Surface/Bulk
25 %a
∼ 70 µm ∼ 500/340 = 1.5
40 %a
∼ 15 µm ∼ 1050/250 = 4.2
50 %a
∼ 32 µm ∼ 350/240 = 1.5
50 %a
∼ 35 µm ∼ 700/275 = 2.5
60 %a
∼ 38 µm ∼ 1000/300 = 3.3
60 %a
∼ 72 µm ∼ 1250/800 = 1.6
70 %a
∼ 38 µm ∼ 425/275 = 1.5
80 %b
∼ 50 µm ∼ 700/350 = 2.0
aOil in Water Droplet
bWater in Oil Droplet
of lower concentration can give higher intensity values
in the bulk. The bulk is the water surrounding the oil
droplet, intensities are obtained for the bulk after the
sharp drop of the peaks corresponding to the surface of
the droplets as shown in Section 5.1.
3.3. Concentrations at the Oil and Water Interface
The concentrations seen in Table II at the interface
across various emulsions with different nanoparticle con-
centrations exhibit a peak although the error associated
with these observations needs to be addressed. This pos-
sible trend suggests that the nanoparticle concentration
may be highest at the interface when using 40-60% stock
nanoparticle concentrations in our emulsions. This might
be related to the stability of an emulsion as we observe
that our most stable emulsions are also in that range.
However, our error is unknown here, this is a small sam-
pling, and we need more data before this can really be
analyzed.
TABLE II: Oil and water interface concentrations observed
over a range of nanoparticle concentrations in water.
Solution Intensity Ratio: Interface/Bulk
10 % ∼ 625/240 = 2.6
20 % ∼ 1575/225 = 7
30 % ∼ 875/250 = 3.5
40 % ∼ 1550/300 = 5.2
50 % ∼ 2100/400 = 5.4
60 % ∼ 2100/400 = 5.4
70 % ∼ 1050/425 = 2.5
80 % ∼ 1100/350 = 3.1
90 % ∼ 1150/325 = 3.5
100 % ∼ 1000/300 = 3.3

4. 4
3.4. Vertical Axis Drift
There is also an issue with maintaining our vertical
position while observing the sample on the slide at the
microscope. The vertical zero point (the brightest point
in the vertical sweep of the silde) seems to drift as we take
time averaged depth scans and moving in the horizontal
plane across the slide most noticeably. This may be due
to the oil on the objective touching the bottom of the
slide while observing. We should repeat our experiments
with the 60x objective lens as the working distance is
larger and we will be able to avoid having the oil between
the lens and the slide touch.
4. CONCLUSIONS
The gradient distribution of particles within the slide
seems promising as a method of determining an intensity
to concentration relationship for our observations. To ob-
tain intensities of surface concentrations that can be used
with this mapping is a little more difficult. The images
have variations that are not well understood to us at this
time. Potential sources of systematic error that come
along with taking images with the microscope (profile
drop off) as well as issues with fluctuations in the bulk
and at the surfaces of the droplet need to be explored
further. Sometimes when moving through a sample the
overall intensity of the bulk varies quite drastically and
we are not sure why. There are many small projects that
can be investigated within this broad sweep of explor-
ing the surface concentration of oil droplets (or water in
oil droplet) in our Pickering emulsion. The method for
mapping intensity to concentration could be improved by
addressing the peaks more closely - the thickness of the
peaks needs to be accounted for and the model adjusted
accordingly. Oil droplets across on sample should be an-
alyzed looking at different factors such as position in the
slide and radius of the bubble as compared to intensity.
The interface concentration experiment should be done
multiple times to establish a trend and see if the 40-60%
really is the highest interface concentration to bulk ratio
or if the error in our observations is really just that high.

5. 5
5. RAW IMAGES AND INTENSITY PROFILES
5.1. Emulsion Droplets Intensities

6. 6
6. INTERFACE INTENSITIES

7. 7

8. 8