Qian Chen1, Hoduk Cho2, Karthish Manthiram3, Mark Yoshida4, Xingchen Ye5, A Paul Alivisatos6. 1. Miller Institute for Basic Research in Science, Department of Chemistry, Kavli Energy NanoScience Institute, and Department of Chemical Engineering, University of California, Berkeley, California 94720, United States; Miller Institute for Basic Research in Science, Department of Chemistry, Kavli Energy NanoScience Institute, and Department of Chemical Engineering, University of California, Berkeley, California 94720, United States; Materials Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, United States. 2. Miller Institute for Basic Research in Science, Department of Chemistry, Kavli Energy NanoScience Institute, and Department of Chemical Engineering, University of California, Berkeley, California 94720, United States; Materials Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, United States; King Abdulaziz City for Science and Technology, Kingdom of Saudi Arabia. 3. Materials Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, United States; Miller Institute for Basic Research in Science, Department of Chemistry, Kavli Energy NanoScience Institute, and Department of Chemical Engineering, University of California, Berkeley, California 94720, United States. 4. Miller Institute for Basic Research in Science, Department of Chemistry, Kavli Energy NanoScience Institute, and Department of Chemical Engineering, University of California , Berkeley, California 94720, United States. 5. Miller Institute for Basic Research in Science, Department of Chemistry, Kavli Energy NanoScience Institute, and Department of Chemical Engineering, University of California, Berkeley, California 94720, United States; Materials Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, United States. 6. Miller Institute for Basic Research in Science, Department of Chemistry, Kavli Energy NanoScience Institute, and Department of Chemical Engineering, University of California, Berkeley, California 94720, United States; Miller Institute for Basic Research in Science, Department of Chemistry, Kavli Energy NanoScience Institute, and Department of Chemical Engineering, University of California, Berkeley, California 94720, United States; Materials Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, United States; King Abdulaziz City for Science and Technology, Kingdom of Saudi Arabia.
Abstract
We demonstrate a generalizable strategy to use the relative trajectories of pairs and groups of nanocrystals, and potentially other nanoscale objects, moving in solution which can now be obtained by in situ liquid phase transmission electron microscopy (TEM) to determine the interaction potentials between nanocrystals. Such nanoscale interactions are crucial for collective behaviors and applications of synthetic nanocrystals and natural biomolecules, but have been very challenging to measure in situ at nanometer or sub-nanometer resolution. Here we use liquid phase TEM to extract the mathematical form of interaction potential between nanocrystals from their sampled trajectories. We show the power of this approach to reveal unanticipated features of nanocrystal-nanocrystal interactions by examining the anisotropic interaction potential between charged rod-shaped Au nanocrystals (Au nanorods); these Au nanorods assemble, in a tip-to-tip fashion in the liquid phase, in contrast to the well-known side-by-side arrangements commonly observed for drying-mediated assembly. These observations can be explained by a long-range and highly anisotropic electrostatic repulsion that leads to the tip-selective attachment. As a result, Au nanorods stay unassembled at a lower ionic strength, as the electrostatic repulsion is even longer-ranged. Our study not only provides a mechanistic understanding of the process by which metallic nanocrystals assemble but also demonstrates a method that can potentially quantify and elucidate a broad range of nanoscale interactions relevant to nanotechnology and biophysics.
We demonstrate a generalizable strategy to use the relative trajectories of pairs and groups of nanocrystals, and potentially other nanoscale objects, moving in solution which can now be obtained by in situ liquid phase transmission electron microscopy (TEM) to determine the interaction potentials between nanocrystals. Such nanoscale interactions are crucial for collective behaviors and applications of synthetic nanocrystals and natural biomolecules, but have been very challenging to measure in situ at nanometer or sub-nanometer resolution. Here we use liquid phase TEM to extract the mathematical form of interaction potential between nanocrystals from their sampled trajectories. We show the power of this approach to reveal unanticipated features of nanocrystal-nanocrystal interactions by examining the anisotropic interaction potential between charged rod-shaped Au nanocrystals (Au nanorods); these Au nanorods assemble, in a tip-to-tip fashion in the liquid phase, in contrast to the well-known side-by-side arrangements commonly observed for drying-mediated assembly. These observations can be explained by a long-range and highly anisotropic electrostatic repulsion that leads to the tip-selective attachment. As a result, Au nanorods stay unassembled at a lower ionic strength, as the electrostatic repulsion is even longer-ranged. Our study not only provides a mechanistic understanding of the process by which metallic nanocrystals assemble but also demonstrates a method that can potentially quantify and elucidate a broad range of nanoscale interactions relevant to nanotechnology and biophysics.
How nanoscale objects
interact and communicate in the solution
phase is a critical underlying issue for both biological[1−4] and artificial systems.[5−8] Inside a living cell, small biomolecules often self-assemble
into supercomplexes with essential functions, such as channel formation[2,3] and protein cooperativity,[1,4] through various forms
of noncovalent interactions. Similarly, colloidal nanocrystals have
been spatially arranged into larger assemblies, in order to take advantage
of collective effects in optics,[9−14] electronics,[15−17] catalysis,[18,19] etc. For both classes
of systems, computational efforts[20−26] have taken the lead to model and understand the interactions essential
to solution phase assembly processes at nanometer or sub-nanometer
resolution. One commonly adopted strategy to measure the interaction
potential between larger, micrometer-sized colloidal particles is
to directly image the colloidal dynamics in solution using optical
microscopy.[27−29] This strategy, however, has not been extended to
the study of nanoscale interactions due to the nanometer resolution
required for direct imaging. For nanoscale objects, the relevant interactions
are usually effective within the range of nanometers to hundreds of
nanometers. For any technique of this type to be broadly useful, it
should be able to correlate interaction potentials with the shape
or surface chemistry of nanoscale building blocks. Until recently,
conventional electron microscopy techniques that offer nanometer scale
resolution required high vacuum and thus were considered to be incompatible
with solution phase dynamics. The multiple recent demonstrations of in situ observations of a wide range of nanoscale dynamic
processes using liquid phase TEM[30−39] open up the possibility of determining full anisotropic pairwise
and higher order interparticle potentials for nanoscale objects at
high resolution by trajectory tracking. Here we demonstrate this for
the case of Au nanorods.Au nanorods are an important system
for which the determination
of the anisotropic interaction potentials will be of great use.[40,41] Individual Au nanorods can concentrate incident electromagnetic
fields due to their strong and tunable uniaxial plasmon resonances,
making them a useful probe for biological imaging with dark field
microscopy and a strong candidate for photothermal cancer therapies.[42,43] When placed in close proximity to each other, Au nanorod plasmon
resonances couple to each other strongly, producing a broader class
of plasmonic molecules with spectra that can be designed with precision,
leading even to three-dimensional plasmon rulers, electromagnetically
induced transparency, and many other collective phenomena.[9,44,45] The ability to understand and
control the assembly of these nanocrystals hinges on knowing the anisotropic
interaction potential, and this potential in turn depends very strongly
on the condition of the liquid environment. The ability to visualize
elementary assembly processes under different conditions of the solution
such assalt concentration will be of immediate use in the creation
and testing of models and theories for nanocrystal assembly.Here we show that it is possible to use liquid phase TEM to visualize
and track each pairwise interaction between nanocrystals within a
field of view over time, and to use this information to extract the
anisotropic interaction potential as a function of critical parameters
like the ionic strength. While the focus of previous liquid phase
TEM work has been either on resolving the finest possible structural
details of nanoscale objects[31−34] or on a phenomenological observation of their dynamics,[35−39] we utilize the massive but often missed nanocrystal position data
to obtain an unprecedentedly quantitative understanding of the factors
governing nanocrystal assembly. Such governing factors were hidden
beneath the apparent solution parameters such as ionic species, pH,
and choice of ligands, which led to sometimes controversial claims
in nanocrystal assembly. For example, an ionic-strength interaction
potential that we observe here can be used to account for two earlier
and seemingly contradictory in situ studies[38,39] of Au nanosphere assembly in which distinctly different assembly
patterns had been observed.
Results and Discussion
We used Au
nanorods synthesized from seed-mediated growth,[46] without further postsynthetic surface modifications
(see Supporting Information, Materials and
Methods section). These rods are our model system to study the more
generic shape effect on interaction profiles, which can be readily
applicable to other anisotropically shaped colloidal nanocrystals
and nanoscale objects. Au nanorods can be synthesized with high shape
purity and size uniformity, which facilitates obtaining a statistically
significant data set. Their high electron density enables the acquisition
of high contrast TEM images for our image analysis.An aqueous
solution of well-dispersed Au nanorods was flowed into
a liquid chamber with Si3N4 windows for in situ TEM imaging of their collective motions in solution
(see Figure S1 in the Supporting Information). Au nanorods move in a quasi-two-dimensional plane close to the
Si3N4 window, to which they are slightly attracted,
where our focal plane is. This nanorod–window attraction is
weak since we still observe the dynamic adsorption and desorption
of nanorods coming to and leaving the focal plane. When the concentration
of Au nanorods is too low for them to interact with each other, they
move randomly within the field of view following the features of Brownian
motion (see Figure S2 in the Supporting Information), which means we can ignore the contribution of nanorod–window
interaction to the energetics of their collective motions. But when
Au nanorods are concentrated enough to cross talk, individual Au nanorods
start to self-assemble, under electron beam illumination (as shown
in Movies S1 and S2 in the Supporting Information and Figure 1). Note that the Au nanorod solution
is confirmed to be colloidally stable ex situ, and
the in situ self-assembly region is highly localized.
When the electron beam is shifted to a new region, we see individual
and well-separated nanorods at the beginning, and then they are triggered
to assemble after seconds of illumination under the electron beam.
This electron beam induced self-assembly is robust, occurring within
a flux range of 17.3 to 67.1 electrons/(Å2·s)
under 200 kV accelerating voltage: our full observation window of
electron flux. Our later quantification of the governing interactions
will elucidate what to us at least was an unanticipated mechanism
of how the electron beam initiates self-assembly. This understanding
allows us to reproduce the ex situ condition of unassembled
Au nanorods by counteracting the relevant electron beam effect during
the in situ observation.
Figure 1
In situ liquid phase TEM imaging of tip-to-tip
assembly of Au nanorods. (A) The liquid flow TEM setup, with Si3N4 windowed microchips. Well-dispersed Au nanorods
self-assemble under the illumination of electron beam. (B) Representative
TEM image (left) and schematics (right) showing the final assembled
structures. (C) A time series of TEM images showing how nanorods approach
and attach to each other. Red arrows highlight the trajectories of
nanorods before they attach to the cluster of growing rod assemblies.
Scale bar is 100 nm.
In situ liquid phase TEM imaging of tip-to-tip
assembly of Au nanorods. (A) The liquid flow TEM setup, with Si3N4 windowed microchips. Well-dispersed Au nanorods
self-assemble under the illumination of electron beam. (B) Representative
TEM image (left) and schematics (right) showing the final assembled
structures. (C) A time series of TEM images showing how nanorods approach
and attach to each other. Red arrows highlight the trajectories of
nanorods before they attach to the cluster of growing rod assemblies.
Scale bar is 100 nm.We saw an interesting long-range effect when we looked closely
into the detailed steps of self-assembly. As shown in Movie S1 in
the Supporting Information, a pair of approaching
nanorods first become aligned in their relative orientations from
a distance before they physically touch, suggesting the presence of
long-range interactions that favor certain orientations. This reorientation
process is distinct from the conventional diffusion/reaction limited
aggregation mechanisms[39,47] which involve solely short-range
interactions. After Au nanorods reorient, they attach, at most times
irreversibly, in a tip-to-tip fashion. The TEM images in Figure 1C highlight the free nanorods being added to the
growing cluster of rods, stepwise with their orientations not perfectly
aligned at the beginning but fine-tuned later with the protruding
rods within the cluster to achieve tip-to-tip attachments. Such tip-to-tip
attachments represent 81% of the 610 inter-rod connections (see exemplary
TEM images in Figure S3 in the Supporting Information) we analyzed in the final assembled structures, which was remarkable
since the Au nanorods do not have known tip-specific chemical functionalities.
In fact, the same rods pack densely side by side when they undergo
drying-mediated assembly (see Figure S1A in the Supporting
Information). This is our qualitative observation of the nanorod
assembly in solution.Our first quantitative analysis is to
map out the many different
ways one rod approaches the other, which shows a “depleted”
zone overlaid with the reference rod shape. The underlying statistical
mechanical argument of this analysis is simple: rods follow the more
probabilistic path, i.e., instantaneous relative positions, toward
each other that corresponds to the lowest free energy. In practice,
we first track the end positions for a pair of nanorods in the same
TEM image (see Figure 2A). We arbitrarily choose
one rod as the reference rod and put it vertically at the origin,
and then reposition the other accordingly such that their relative
alignments remain unchanged. This repositioned second rod is simplified
as one blue line as shown in Figures 2A and 2B.
Figure 2
Spatial mapping of pairwise interaction potentials from in situ dynamics of Au nanorods. (A) A TEM image highlighted
with tracked positions of Au nanorods at their tips (red and green
stars), and their centroids (yellow stars). In this pair, the bottom
rod was chosen to be the reference rod, and the top rod was simplified
as a blue line and chosen to be the repositioned rod. (B) rod density
plot, where the blue lines are the observed positions of other rods
relative to the vertical reference rod (yellow rod drawn to scale).
The data was obtained from ∼10000 pairs of rods, but for simplicity,
only 1/8 randomly chosen data was plotted in this figure. (C) The
color-coded counts of total number of rods in the 2D plane of 5 nm
by 5 nm pixels. Color bar shows the counts. (D) g(r) vs r plot. (E) u(r) vs r plot with its exponential
fitting (red line). The inset shows the exponential decay relation
of u(r) by illustrating the resultant
linear relationship of ln(u(r))
vs r.
Spatial mapping of pairwise interaction potentials from in situ dynamics of Au nanorods. (A) A TEM image highlighted
with tracked positions of Au nanorods at their tips (red and green
stars), and their centroids (yellow stars). In this pair, the bottom
rod was chosen to be the reference rod, and the top rod was simplified
as a blue line and chosen to be the repositioned rod. (B) rod density
plot, where the blue lines are the observed positions of other rods
relative to the vertical reference rod (yellow rod drawn to scale).
The data was obtained from ∼10000 pairs of rods, but for simplicity,
only 1/8 randomly chosen data was plotted in this figure. (C) The
color-coded counts of total number of rods in the 2D plane of 5 nm
by 5 nm pixels. Color bar shows the counts. (D) g(r) vs r plot. (E) u(r) vs r plot with its exponential
fitting (red line). The inset shows the exponential decay relation
of u(r) by illustrating the resultant
linear relationship of ln(u(r))
vs r.This automatic pairwise position sampling (see Movie S3 in
the Supporting Information) allows us to accumulate
∼10,000
pairs of nanorod interactions, and to generate a map of all the observed
rod positions and orientations relative to a vertically oriented reference
rod at the origin (Figure 2B). There is a zone
at the origin where other rods are “depleted” or “repelled”
from the reference rod. We determined the shape of this “depleted”
zone by calculating and plotting the total number of rods falling
in each 5 nm by 5 nm pixel around the reference rod (Figure 2C). The zone periphery has a “dipolar field”
shape and touches the tips of the central reference rod, but stays
away from its side; this anisotropic depletion zone is consistent
with the observation that approaching rods become oriented with respect
to each other before they attach tip-to-tip, while they do not attach
side by side.In addition to the qualitative matching of the
shape of the “depleted”
zone to the observed tip-to-tip assembly, we quantitatively determined
the radial distribution function to extract the mathematical form
of the interactions responsible for how rods approach each other.
The radial distribution function, g(r), can relate our experimentally measured rod densities to inter-rod
pairwise interactions. We only use one spatial parameter r, the radial distance of a given pixel to the origin, to describe g(r) since the rod density plots (Figures 2B and 2C) are both radially
symmetric to a good approximation (see Figure S4 in the Supporting Information). But the same relation can also work
if the density plot is radially dependent; one can simply add orientation
as an additional parameter. We plotted g(r) vs r as shown in Figure 2D using the definition g(r) = ρ(r)/ρav, where ρ(r) is the areal density of rods within the circular ring
confined by r and r + δr and ρav is the average areal density
of rods within a circular area of 250 nm in radius. In this particular
experiment, the nanorod concentration is considered to be low enough
to assume that the nanorods only interact in a pairwise manner; g(r) is thus directly related to the pairwise
interaction u(r) via the relationship g(r) = e–, where kB is the Boltzmann constant
and T is the temperature. When the nanorod concentration
is too high, a nanorod situated at r experiences
the interaction not only with the reference rod at the origin but
also with other neighbors. These multibody interactions increases
with particle concentration since there are more neighbors to interact
with. In this case, g(r) is related
to the interparticle potential via a more complicated relation: g(r) = exp[−u(r)/(kT)]y(r), where y(r) = 1 + ∑∞ρy(r), the cavity distribution function. In other words, one can still
extract u(r) from iterative fitting
of g(r) considering higher order
contribution from pairwise interactions as long as such “many-body”
interactions stay as a summation of many pairwise interactions.As shown in Figure 2E, at short distances, u(r) starts from positive values corresponding
to repulsive interactions, which is consistent with the existence
of the central “depleted” zone. Then u(r) slowly decays to zero at larger r, which confirms that our data set is indeed statistically significant
since we expect rods to not interact when they are far away from each
other. Fitting of the u(r) vs r curve shows that u(r) decays exponentially with r, the decay constant
being (16.0 ± 0.7) nm (see Figure 2E).This exponential decay profile, obtained for the first time from in situ observation of nanoscale dynamics, is reminiscent[48] of screened electrostatic repulsion between
cylindrical surfaces coated with small charges, where the decay length
is effectively the Debye length. Indeed, our as synthesized Au nanorods
are stabilized and coated with a bilayer of cetyltrimethylammonium
ions (CTA+), which renders them positively charged. The
electrostatic nature of repulsion can explain why the otherwise well-dispersed
Au nanorods self-assembled only upon electron beam illumination: the
radiolysis of water under the electron beam generates additional reactive
species, including hydrated electrons,[49] which increases the ionic strength in the solution and shortens
the screening length. This decrease in Debye length allows the rods
to come into closer proximity where shorter range interactions can
take over and bring the rods fully into contact. Such an effect is
consistent with previous ex situ studies,[39] where the zeta potential of a charged gold nanosphere
solution is found to decrease upon electron beam irradiation with
a Van de Graaff accelerator, and the authors also attributed such
a decrease of zeta potential to increased ionic strength from radiolysis
of water.This connection prompted us to make a direct comparison
between
our experimental data and theoretical modeling of electrostatic interactions,
and they turn out to be in good agreement with each other. Experimentally,
we plot out the positions and orientations of all the rods after attachment,
including both tip-to-tip attachments and non tip-to-tip attachments
to give an overview of the energetics of rod attachment configurations
(Figure 3A). The density plot of these attached
rods shows a clear preference for rods to align parallel with each
other, as shown in Figure 3B. In the corresponding
theoretical modeling, we coat the rod surface with a large number
of point charges[50,51] and obtain the electrostatic
repulsion of two rods at any given configuration by summing all screened
pairwise interactions between point charges. Note that this way of
modeling electrostatic interaction is highly coarse-grained. We neglected
possible interactions between neighboring point charges, and the molecular
details of how solvant molecules hydrated these point charges. Moreover,
we assume a homogeneous charge density over the rod surface, while
previous studies have shown that due to difference of ligand binding
energy to difference facets, the ligand/charge density at the rod
ends is smaller than on the sides. A more vigorous model that addresses
the above details will give a more description of the electrostatic
potential between two rods. Still our simple modeling here captures
the key feature of shape anisotropy, and helps us understand the qualitative
trend of favored tip-to-tip assembly. This model is based on the 2D
projection of rods since in experiments rods move and assemble in
a 2D plane.
Figure 3
Comparison of experimental data and theoretical modeling of electrostatic
interactions. (A) The rod position plot from ∼300 rod–rod
attachments. The symbol and color scheme are based on what is shown
in Figure 2B. (B) The observed density of rods
in the attached configuration where the reference rod is also sitting
vertically at the center. It is clear that the rods have a preference
to align roughly parallel with each other (see the dark red pixels).
(C) Energy contour plot showing calculated lowest potential for a
pair of nanorods, where one rod stays vertically at the center and
the other samples all the possible rod orientations at each pixel.
The potential at each pixel is color-coded: red for larger values
and blue for smaller values. At the rod side position, the potential
energy is ∼2 times higher than at the rod tip. (D) Calculated
orientation of rods for the lowest energy at each pixel, with blue
color meaning parallel and red color meaning perpendicular as shown
in the schematics on the left.
Comparison of experimental data and theoretical modeling of electrostatic
interactions. (A) The rod position plot from ∼300 rod–rod
attachments. The symbol and color scheme are based on what is shown
in Figure 2B. (B) The observed density of rods
in the attached configuration where the reference rod is also sitting
vertically at the center. It is clear that the rods have a preference
to align roughly parallel with each other (see the dark red pixels).
(C) Energy contour plot showing calculated lowest potential for a
pair of nanorods, where one rod stays vertically at the center and
the other samples all the possible rod orientations at each pixel.
The potential at each pixel is color-coded: red for larger values
and blue for smaller values. At the rod side position, the potential
energy is ∼2 times higher than at the rod tip. (D) Calculated
orientation of rods for the lowest energy at each pixel, with blue
color meaning parallel and red color meaning perpendicular as shown
in the schematics on the left.Figure 3C shows the energy contour
plot
corresponding to rod configurations that minimize the electrostatic
repulsion for a given pixel position. The electrostatic repulsion
around the reference rod is much weaker at the tips than at the sides,
which is consistent with the observed tip selectivity. The contour
shape of calculated equal potentials around the reference rod is ellipsoidal
at a distance (<10 nm) from the rod surface that is smaller than
what we can conveniently resolve. The shape becomes very circular
further from the reference rod surface, just like the depleted zone
periphery experimentally observed as shown in Figure 2C. Figure 3D, on the other hand, maps
out the rod orientations with the lowest energy. Rods are more likely
to align parallel toward each other at the rod tip, consistent with
the experimentally measured Figure 3B, which
further corroborates the electrostatic nature of repulsion.The preceding analysis allows us to propose a mechanism by which
rods assemble tip-to-tip: individual Au nanorods first randomly move,
enveloped by a repulsive “cloud” of a radius that depends
on the ionic strength of the solution. They can only come close to
each other when their repulsive clouds experience the least overlap,
i.e., the smallest repulsion, which occurs specifically when they
approach tip-to-tip. When r is sufficiently small,
short-range attractions, which are mainly contributed from the van
der Waals interactions,[52] take over and
permanently lock the rods into oriented assemblies. We did not see
the features of this short-range attractive component in the interaction
potential we experimentally obtained, most likely because we did not
have enough temporal resolution to accumulate significant statistics
for very small inter-rod distances. In the movies it appears as though
the rods “snap together” at the last instant because
the temporal resolution is low. The fact that we missed the short-range
attractive interaction feature, together with the anisotropy of rod–rod
electrostatic interaction, are the reasons why we chose not to fit
our experimental data with DLVO theory, instead we used theoretical
modeling that accounts for the shape details of nanorods for direct
comparison.As we now understand the interactions governing
assembly, we are
able to counteract the electron beam effect and correlate our in situ experiments with ex situ conditions.
We decreased the ionic strength of the Au nanorod solution through
centrifugation followed by redispersion in hexadecyltrimethylammonium
chloride solution (see Supporting Information, Materials and Methods section) and investigated the nanocrystal
dynamics under the electron beam. This time, Au nanorods stayed apart
and did not assemble under the electron beam, just as one would expect
from a less screened electrostatic repulsion. The plot of experimentally
measured rod positions in Figure 4A shows that
the size of the “depleted” zone increased significantly:
Au nanorods were surrounded by large repulsive clouds, as indicated
by yellow dotted circles in Figure 4B, preventing
them from encountering each other at the close distances needed for
assembly, as shown by their trajectories in Figure 4C, and Movie S4 in the Supporting Information. This observation provides further proof of the dominant role of
electrostatic repulsion. More importantly, the interactions of the
electron beam with the sample and the liquid medium have mostly been
regarded as being undesirably complicated. By understanding the nature
of nanoscale interactions involved, we are able to show how we can
circumvent the electron beam effects to retrieve ex situ conditions under in situ electron beam irradiation.
In other words, using our highly quantitative measurement and interpretation,
our knowledge learned from in situ liquid phase TEM
observations can be transferred to understand ex situ experiments, which, for this specific case, is correlated via adjustment
of the ionic strength.
Figure 4
Suppression of Au nanorod assembly at low ionic strength.
(A) Plot
of different rod configurations (each rod as a purple line) relative
to the central reference rod. The yellow dashed circle indicates the
depleted zone. (B) TEM image of electrostatically stabilized Au nanorods
overlaid with yellow dotted depleted zone. (C) Trajectories of all
eight rods in panel B. Scale bar is 50 nm.
Suppression of Au nanorod assembly at low ionic strength.
(A) Plot
of different rod configurations (each rod as a purple line) relative
to the central reference rod. The yellow dashed circle indicates the
depleted zone. (B) TEM image of electrostatically stabilized Au nanorods
overlaid with yellow dotted depleted zone. (C) Trajectories of all
eight rods in panel B. Scale bar is 50 nm.Our work has demonstrated the use of liquid cell TEM as a
tool
to quantitatively examine the fundamental interactions that govern
how anisotropic colloidal nanocrystals interact with each other in
their native liquid environment without a priori knowledge
of the interactions involved. We have learned that the ionic strength
is a key parameter that will determine whether nanorods assemble end
to end or side by side, and that this arises because at certain ionic
strengths the nanorod repulsion is minimized when the rods are oriented
tip to tip, while at higher ionic strength, nanorods are sufficiently
screened and effectively “uncharged” and only experience
short-range attractions and form into random aggregates (Figure S4
in the Supporting Information). We note that
while the observation of ionic strength dependence and screening length
is consistent with simple models, studies of the assembly process
at high ionic strength are still valuable for testing models of concentrated
electrolytes which are still quite difficult to understand. We see
the real power of the in situ pairwise and higher
order trajectory sampling method being its generalized ability to
correlate spatially the interaction potential profile with the shape/surface
chemistry of other nanoscale systems involving more intricate yet
crucial nanoscale interactions, such as the hydrophobic interactions
among chemically patchy protein molecules.[53]
Authors: Qiao Zhang; Xing-Zhong Shu; J Matthew Lucas; F Dean Toste; Gabor A Somorjai; A Paul Alivisatos Journal: Nano Lett Date: 2013-12-12 Impact factor: 11.189
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Authors: Xingchen Ye; Yuzhi Gao; Jun Chen; Danielle C Reifsnyder; Chen Zheng; Christopher B Murray Journal: Nano Lett Date: 2013-04-08 Impact factor: 11.189
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