Joshua Lequieu1, Andrés Córdoba1, Daniel Hinckley2, Juan J de Pablo3. 1. Institute for Molecular Engineering, University of Chicago , Chicago, Illinois 60637, United States. 2. Department of Chemical and Biological Engineering, University of Wisconsin-Madison , Madison, Wisconsin 53706, United States. 3. Institute for Molecular Engineering, University of Chicago, Chicago, Illinois 60637, United States; Materials Science Division, Argonne National Laboratory, Argonne, Illinois 60439, United States.
Abstract
The self-assembly of DNA-conjugated nanoparticles represents a promising avenue toward the design of engineered hierarchical materials. By using DNA to encode nanoscale interactions, macroscale crystals can be formed with mechanical properties that can, at least in principle, be tuned. Here we present in silico evidence that the mechanical response of these assemblies can indeed be controlled, and that subtle modifications of the linking DNA sequences can change the Young's modulus from 97 kPa to 2.1 MPa. We rely on a detailed molecular model to quantify the energetics of DNA-nanoparticle assembly and demonstrate that the mechanical response is governed by entropic, rather than enthalpic, contributions and that the response of the entire network can be estimated from the elastic properties of an individual nanoparticle. The results here provide a first step toward the mechanical characterization of DNA-nanoparticle assemblies, and suggest the possibility of mechanical metamaterials constructed using DNA.
The self-assembly of DNA-conjugated nanoparticles represents a promising avenue toward the design of engineered hierarchical materials. By using DNA to encode nanoscale interactions, macroscale crystals can be formed with mechanical properties that can, at least in principle, be tuned. Here we present in silico evidence that the mechanical response of these assemblies can indeed be controlled, and that subtle modifications of the linking DNA sequences can change the Young's modulus from 97 kPa to 2.1 MPa. We rely on a detailed molecular model to quantify the energetics of DNA-nanoparticle assembly and demonstrate that the mechanical response is governed by entropic, rather than enthalpic, contributions and that the response of the entire network can be estimated from the elastic properties of an individual nanoparticle. The results here provide a first step toward the mechanical characterization of DNA-nanoparticle assemblies, and suggest the possibility of mechanical metamaterials constructed using DNA.
Nanoparticles functionalized
with short sequences of DNA represent
a highly customizable platform for multiscale materials design. In
such systems, interactions between nanoparticles are mediated by short
strands of DNA, typically with lengths on the order of tens of base
pairs.[1,2] By varying the length and composition of
these linking DNA sequences, the strength, range, and specificity
of interparticle interactions can be precisely tuned. The ability
to customize and specify DNA-mediated interactions promises to facilitate
the design of hierarchical structures whose macroscopic properties
could be tuned by manipulating the corresponding nanoscale building
blocks of which they are composed.DNA-functionalized nanoparticles
have now been shown to assemble
into crystals with long-range order[3,4] that possess
tunable lattice parameters and crystal symmetries based on DNA sequence
alone.[5] Through advances in nanoscale synthesis,
it has also become possible to assemble nanoparticles of different
shapes and properties.[6−9] The resulting materials exhibit intriguing properties, such as dynamic
reprogramming[10] and single crystal assembly
with well-defined facets,[11] and have been
predicted to demonstrate re-entrant melting.[12] Recent work has demonstrated that DNA-programmed assemblies have
useful, tunable plasmonic properties.[13−16] A largely underexplored aspect
of DNA-functionalized nanoparticle assemblies, however, is related
to the tunability of their mechanical properties. Though two-dimensional
films of DNA-functionalized nanoparticles have been assembled[17] and shown to have extraordinary mechanical properties,[18] little work[19] has
been done to characterize or tune the mechanics of DNA–nanoparticle
assemblies, especially in three dimensions.Our interest in
mechanically tunable DNA–nanoparticle assemblies
builds on recent work examining the mechanical response of nanoparticles
conjugated with other short organic ligands. Extremely strong, two-dimensional
nanoparticle sheets have been prepared with nanoparticles functionalized
with simple dodecanethiol ligands.[20−22] At the other end of
the chain-length spectrum, Williams et al.[23] have shown that polymer-grafted nanoparticles interacting via hydrogen
bonds assemble into a fcc crystal with a Young’s modulus of
26–82 MPa that is capable of self-healing.[23] Importantly, these authors demonstrated that the mechanical
and optical response can be tuned by varying the length of polymer
grafts, and that the optical properties can be altered by mechanical
deformation. More generally, the mechanical properties of ligand-conjugated
nanoparticle assemblies are of fundamental interest because they arise
from nonlinear combinations of their constituents; indeed, they possess
characteristics of both granular (due to the nanoparticles) and viscoelastic
(due to the ligands) systems.[24]In
this work, we present a first step toward the detailed characterization
of the mechanical response of DNA–nanoparticle assemblies.
To achieve this, we rely on a detailed molecular model to examine
the mechanical properties of DNA-conjugated nanoparticle assemblies in silico. Our results demonstrate that such properties
can indeed be tuned by using different DNA sequences, DNA loading
densities, and temperature, thereby providing a potentially useful
platform for the creation of mechanical metamaterials.
Results and Discussion
Mechanical
Response of DNA-Conjugated Nanoparticle Lattices
DNA-conjugated
nanoparticle lattices were assembled as described
in Methods, and their mechanical response
was measured under uniaxial extension (Figure ). The deformation was applied quasi-statically,
where a nanoparticle assembly was deformed to the specified strain
and then held fixed until the stress re-equilibrated. The resulting
stress–strain curve exhibits elasticity (i.e., linear response)
for all temperatures up to strains of 50%. Following this elastic
regime, the material stiffens until its peak stress at ≈125–150%
strain.
Figure 1
Stress–strain response of DNA–nanoparticle assembly
under uniaxial extension for sequence B (see Figure 2). Simulation snapshots show the material after 0%, 100%,
200%, and 300% strain. All DNA sequences of the same type are given
the same color (i.e., red or blue). Error bars denote a standard deviation
over three independently initialized nanoparticle assemblies.
Stress–strain response of DNA–nanoparticle assembly
under uniaxial extension for sequence B (see Figure 2). Simulation snapshots show the material after 0%, 100%,
200%, and 300% strain. All DNA sequences of the same type are given
the same color (i.e., red or blue). Error bars denote a standard deviation
over three independently initialized nanoparticle assemblies.
Figure 2
Different DNA sequences conjugated to nanoparticle
surface. Green
highlights the complementary “sticky end” region, while
blue highlights the nonreactive “linker” region. Snapshots
corresponding to the molecular topology of each DNA linker are shown.
“2× loading” denotes that Seq D contains twice
the number of DNA strands per nanoparticle. Note that Seq A’s
linker consists of two DNA strands and contains a nonreactive double-stranded
region, while the linkers of Seq B, C, and D consist of only a single
DNA strand.
Different DNA sequences conjugated to nanoparticle
surface. Green
highlights the complementary “sticky end” region, while
blue highlights the nonreactive “linker” region. Snapshots
corresponding to the molecular topology of each DNA linker are shown.
“2× loading” denotes that Seq D contains twice
the number of DNA strands per nanoparticle. Note that Seq A’s
linker consists of two DNA strands and contains a nonreactive double-stranded
region, while the linkers of Seq B, C, and D consist of only a single
DNA strand.At strains above the
peak stress, the material does not immediately
yield, but instead the stress decreases slowly: even at strains of
300% there is still a small but nonzero stress. Notably, even at these
large strains, the material does not exhibit necking and is characterized
by constant densities throughout the sample (Figure snapshots, Figure S2). Yet despite the lack of macroscopic defects (i.e., necking), the
microscopic structure of the nanoparticle assembly is significantly
perturbed under large strains. For deformations beyond the peak stress,
the long-range crystalline order within the nanoparticle network is
disrupted, and the assemblies become amorphous (Figure snapshots, Figures S3 and S4). This observation suggests that, under sufficiently
slow deformation (i.e., quasi-static), the microstructure of the assembly
can rearrange, thereby preventing the formation of failure-prone morphologies,
including necks or voids. This behavior can be thought of as a form
of microscopic self-healing, where individual nanoparticles reposition
themselves within the network to maintain the integrity of the material.Temperature also plays an important role in the mechanical response
(Figure ). Though
the material exhibits a response in the kPa range at low temperatures,
higher temperatures result in material softening and, eventually,
a negligible mechanical response (e.g., 330 K). The extreme softening
of the material occurs for this assembly between 310 and 330 K, corresponding
extremely well to the 310–315 K melting temperature of this
DNA sequence calculated previously.[25]In order to confirm that our measurements are representative of
a bulk material and do not suffer from finite-size effects, simulations
were also performed for systems consisting of 125 bcc unit cells,
corresponding to 121,000 total coarse-grained sites (Figure , red triangles). The results
from this larger system are largely indistinguishable from those of
the 27 unit cell assembly (N = 26,136), confirming
that our simulations are representative of a bulk material. Accordingly,
nanoparticle assemblies consisting of 27 unit cells will be used throughout
the remainder of this work.
Tunable Sequence-Dependent Mechanical Response
A potential
feature of DNA–nanoparticle assemblies is that subtle changes
in the linking DNA sequences may be used to generate materials with
different properties. To examine the effect of DNA sequence on the
mechanical response, we repeated our analysis above using different
DNA sequences (Figure ). Because the parameter space corresponding to all possible DNA
sequences is prohibitively large, we focused here on a subset of DNA
parameters that have been varied elsewhere in the DNA–nanoparticle
literature.[4,5,25,26] These include the effect of “one strand”
vs “two strand” linkers (i.e., Seq A vs Seq B), the
effect of linker length (Seq A vs Seq C), the effect of DNA loading
density (Seq C vs Seq D), and the effect of the complementary DNA
“sticky ends” (Seq A vs Seq B vs Seq C and D). Consistent
with experimental systems,[3,11,27] the sequences chosen here contain complementary “sticky”
DNA regions of 6–7 base pairs.The mechanical response
is shown to be dramatically dependent on DNA sequence (Figure ). One sequence-dependent effect
is the qualitative difference in mechanical response between sequences
with short linkers (i.e., C and D) relative to sequences with long
linkers (i.e., A and B). Sequences C and D demonstrate a stiff initial
response (E ≈ 700–2100 kPa) but exhibit
little strain hardening, and lose nearly all stiffness at strains
greater than 100%. In contrast, sequences A and B exhibit a softer
initial response (E ≈ 100 kPa) but a large
peak strain (≈500–750 kPa). Additionally, long linkers
enable strains of up to 300% without mechanical rupture. Thus, short
linkers give rise to “brittle” mechanical behavior,
while longer linkers result in more pliable materials. Curiously,
though sequence A and sequence B are formed from very different linker
types (i.e., double-stranded vs single-stranded), they nonetheless
demonstrate a qualitatively similar mechanical response. Though double-stranded
linkers are stiff, the similarities between our results for Seq A
and Seq B suggests that the mechanical response is predominantly driven
by the single-stranded linker of the assemblies constructed using
sequence A. This result suggests that it is not the type of DNA linker
but rather its single-stranded length that dictates the mechanical
response of DNA-nanoparticle assemblies.
Figure 3
DNA sequence-dependent
mechanical response. Stress–strain
response of sequences A, B, C, and D and corresponding Young’s
modulus, E, at different temperatures. Variations in both temperature
and sequence result in both qualitative and quantitative changes in
the stress–strain response of DNA–nanoparticle assemblies.
DNA sequence-dependent
mechanical response. Stress–strain
response of sequences A, B, C, and D and corresponding Young’s
modulus, E, at different temperatures. Variations in both temperature
and sequence result in both qualitative and quantitative changes in
the stress–strain response of DNA–nanoparticle assemblies.The effect of DNA coverage can
be assessed by comparing sequences
C and D. Assemblies using these linkers use identical DNA sequences
and differ only in the density (i.e., loading) of DNA strands conjugated
to the nanoparticle surface. That is, Seq D has twice the number of
DNA strands on the nanoparticle surface relative to Seq C. Our results
demonstrate that DNA loading density results in significant changes
to the stress−strain response. For example, by simply doubling
the DNA loading (i.e., nine strands for Seq C vs 18 strands for Seq
D), the Young’s modulus changes by a factor of 3 (≈700
kPa to ≈2100 kPa) and the peak stress more than doubles (≈300
kPa to ≈740 kPa). Yet, despite these changes, the qualitative
features of the mechanical responses of Seq C and D remain largely
unchanged: the stress increases linearly up until a peak strain at
γ ≈ 50% and then decreases significantly. This result
suggests that DNA loading represents an important parameter for tuning
mechanical behavior. Whereas the qualitative features of the mechanical
response can be adjusted by changing the characteristics of the DNA
sequences themselves, the magnitude of the response can be adjusted
independently by varying the DNA loading on the nanoparticle surface.
In that sense, DNA coverage represents a system parameter orthogonal
to the DNA sequence itself, which can be tuned to obtain the desired
mechanical response. Additionally, since the number of strands increases
approximately with the square of the nanoparticle radius, the larger
10–20 nm nanoparticles used experimentally[3,4,11] will possess even more particle–particle
connections and likely a significanlty stronger mechanical response.Interestingly, the different DNA sequences studied here exhibit
different temperature-dependent mechanical properties. The mechanical
response of Seq B is nearly unchanged between 273 and 290 K, for example,
while those of sequences C and D over this same temperature range
change dramatically. These different behaviors can be explained in
terms of the melting temperature, Tm,
of the DNA “sticky ends” that link complementary particles.
By choosing “sticky ends” with a higher Tm (as with Seq B), the nanoparticles demonstrate higher
thermal stability and are more mechanically robust. Because DNA–nanoparticles
are known to exhibit extremely sharp melting curves,[28] our results here suggest the possibility of extremely sensitive
thermoresponsive materials whose mechanical properties could change
by orders of magnitude with temperature changes of only several degrees.
Molecular Origin of Mechanical Response
Having considered
the mechanical properties of DNA–nanoparticle assemblies, we
now turn our attention to the molecular processes responsible for
specific sequence-dependent mechanical responses. Specifically, we
seek to provide a molecular explanation of the stress–strain
curves reported in Figure . In particular, we will examine whether the mechanical response
correlates more strongly with (a) the enthalpic penalty arising from
the disruption of base pairs or (b) the entropic penalty arising from
the anisotropic ordering of DNA strands on the nanoparticle surface.Since nanoparticle–nanoparticle interactions are mediated
by complementary DNA–DNA base pairs, deformation of the network
is expected to result in base pair disruption. Disruption of base
pairs will incur an enthalpic penalty, and therefore we anticipate
that disruption of base pairs might correlate strongly with the observed
stress–strain response. Figure a shows the network connectivity (expressed as the
number of base pairs in the network) for each DNA sequence as a function
of strain. As expected, strain disrupts the DNA–nanoparticle
network, and the number of base pairs is observed to decrease. Notably,
the slope of the base pair–strain curve (i.e., the derivative)
differs between different DNA sequences. For short DNA linkers (i.e.,
sequences C and D), the decrease in base pairs is more rapid than
for DNA–nanoparticles with longer linkers (sequences A and
B). The slope of the base pair–strain curve is quantified by
calculating the numerical derivative shown in the bottom panel of Figure a. Sequences C and
D demonstrate a sharply peaked derivative at 50% strain, corresponding
to the maximum in their respective stress–strain response (Figure ). This correlation
suggests that the stress–strain response is influenced by the
rate of base pair disruption and the associated enthalpic penalty.
This possibility, however, is only weakly supported by the results
for sequences A and B. For these two sequences, the derivatives are
approximately independent of strain and show only a subtle peak at
175%–200% strain, a value higher than the peak in the stress–strain
response at 125%–175%. Therefore, though the disruption of
base pairs influences the mechanical behavior, our results suggest
that it is not the predominant explanation for the observed sequence-dependent
mechanical response.
Figure 4
Effect of deformation on connectivity of DNA–nanoparticle
network. (a) Average number of base pairs, ⟨Nbp⟩, and numerical derivative, , and
(b) average coordination number, ⟨Z⟩,
and numerical derivative, , for
different DNA–nanoparticle
sequences at 273 K. Though the disruption of base pairs influences
the mechanical behavior, analysis of network connectivity alone is
insufficient to fully explain the mechanical response.
Effect of deformation on connectivity of DNA–nanoparticle
network. (a) Average number of base pairs, ⟨Nbp⟩, and numerical derivative, , and
(b) average coordination number, ⟨Z⟩,
and numerical derivative, , for
different DNA–nanoparticle
sequences at 273 K. Though the disruption of base pairs influences
the mechanical behavior, analysis of network connectivity alone is
insufficient to fully explain the mechanical response.A notable feature of Figure a is that the number of base pairs does not
decrease to zero.
Even after the assembly has been mechanically disrupted, 60% to 70%
of the original base pairs are still intact. This observation led
us to propose that it is not the absolute number of base pairs that
matters for the mechanical response, but it is instead the connectivity
of the network. To test this hypothesis, we measure the connectivity
of the network on the basis of nanoparticle coordination number. In
this context, we define the coordination number, Z, as the number of neighboring nanoparticles that a given nanoparticle
is base paired to, normalized by that expected in a bcc crystal lattice, Zbcc = 8, (Figure b). At rest, sequences with ordinary DNA loading densities
(sequences A, B, C) have coordination numbers that are ≈80%
of the ideal value. This result is expected since these particles
contain only nine DNA strands per particle, and therefore the probability
of forming DNA “bonds” between all 8 bcc neighbors is
small. However, for particles with a higher loading density (Seq D),
the connectivity of the network is essentially complete, with Z/Zbcc ≈ 1.0 at 0% strain.
The near perfect connectivity of sequence D helps explain its high
mechanical strength: as the connectivity approaches the ideal value,
mechanical properties increase considerably. Note, however, that our
analysis of the coordination number is still insufficient to completely
explain the sequence-dependent stress–strain response. As with
the number of base pairs, Nbp, shown in Figure a, the coordination
number in Figure b
decreases with strain and the derivative (lower panel) correlates
weekly with the stress–strain curves.Another possible
explanation for the role of sequence on mechanical
properties relates the deformation of individual DNA-conjugated nanoparticles
themselves to the overall deformation of the network. During network
deformation, it might be expected that the DNA strands conjugated
to the nanoparticle surface would anisotropically orient themselves
along the direction of the applied strain. Such ordering would incur
an entropic penalty and could be responsible for the observed sequence-dependent
mechanical response. Indeed, such entropic penalties dominate the
mechanical properties of polymer melts, and could be significant in
DNA–nanoparticle assemblies as well.To examine the role
of this entropic ordering, the shape of individual
nanoparticles was quantified by calculating the radius of gyration
tensor, S, for each DNA-conjugated nanoparticle, and then determining its
three eigenvalues, λ1 > λ2 >
λ3. The ratio of the two largest eigenvalues, λ1/λ2, gives the anisotropic shape of each
nanoparticle
with λ1/λ2 ≈ 1 representing
a sphere and λ1/λ2 → ∞
an infinite rod.[29] Since the nanoparticles
are very rigid, values of λ1/λ2 ≠
1 represent deformations of the conjugated DNA strands, and not the
nanoparticles themselves (Figure a, graphic). We will refer to λ1/λ2 as the “anisotropy” of the DNA–nanoparticles.
Figure 5
Anisotropic
deformation of individual nanoparticle shape. (a) Average
anisotropy of DNA–nanoparticle shape during deformation. The
anisotropy is qualitatively similar to the mechanical response (cf. Figure ). (b) Correlation
between DNA–nanoparticle anisotropy and calculated stress during
deformation. For all sequences and temperatures, a strong correlation
exists.
Anisotropic
deformation of individual nanoparticle shape. (a) Average
anisotropy of DNA–nanoparticle shape during deformation. The
anisotropy is qualitatively similar to the mechanical response (cf. Figure ). (b) Correlation
between DNA–nanoparticle anisotropy and calculated stress during
deformation. For all sequences and temperatures, a strong correlation
exists.The average anisotropy for different
values of strain and temperature
is shown in Figure a for sequence B. At zero strain, the anisotropy is small and the
individual DNA–nanoparticles are nearly spherical, as expected.
As strain is increased, the average anisotropy increases up to a peak
at 125% and then decays toward its initial value for strains of up
to 300%. The anisotropy is also temperature dependent; higher temperatures
lead to less anisotropy. The most important feature of this result,
however, is the striking similarity between the anisotropy and the
stress (cf. Figure ). In fact, both curves appear to be qualitatively identical, with
the same maximum, curvature, and temperature dependence. This observation
suggests that the shape anisotropy and the stress might be fundamentally
related within the DNA–nanoparticle network.To quantify
this relationship, the correlation between anisotropy
and stress was calculated for all sequences and temperatures used
in this study (Figure b). Confirming the previous observation for sequence B, a strong
correlation (0.8 < r < 0.96) exists between
anisotropy and stress for all DNA sequences considered here. This
striking result suggests that strain within the DNA–nanoparticle
network is strongly related to the anisotropic deformation of the
DNA strands on the particle surface, which gives rise to a free energy
penalty that manifests itself as a restoring stress when the network
is deformed.An important feature of Figure b is that each DNA sequence exhibits a different
relationship
between stress and anisotropic deformation; or in other words, each
DNA sequence shows a different slope. The softest assembly examined
here, sequence A, has the smallest slope (i.e., low stress per anisotropic
deformation), whereas increasing assembly stiffness (i.e., Seq D)
leads to increasingly large slopes (i.e., high stress per anisotropic
deformation). These results suggest that each DNA sequence possesses
an inherent property, which we refer to as “shape stiffness”,
that corresponds to the entropic penalty incurred by causing the DNA
strands to order anisotropically. Notably, shape stiffness is sequence
dependent: for sequence A, the long DNA linkers incur a relatively
small penalty upon ordering, leading to small “shape stiffness”.
In contrast, the short DNA linkers in sequences C and D give rise
to a larger penalty upon ordering, causing the “shape stiffness”
to be large. Therefore, our results indicate that the “shape
stiffness” of a single DNA–nanoparticle represents a
key parameter that dictates the mechanical response of the entire
DNA–nanoparticle network.The importance of “shape
stiffness” has several implications
for the design of DNA–nanoparticle assemblies. First, our results
suggest that by simply quantifying the “shape stiffness”
for a single nanoparticle the mechanical response of the network can
be estimated. As such, “shape stiffness” might provide
a simple metric for screening the high parameter space of different
DNA sequences in order to obtain the desired mechanical response.
Second, the importance of entropic, rather than enthalpic, contributions
to the mechanical response has important implications for tuning the
mechanical response of DNA–nanoparticle assemblies. Though
previous studies have emphasized the energy scale of the complementary
“sticky ends” in dictating DNA–nanoparticle assembly,[30,31] our results indicate that it is instead the properties of the unreactive
linker DNA that dominate the mechanical response. This observation
raises the intriguing prospect of tuning independently the mechanical
response and the underlying crystal structure, leading to the possibility
of creating DNA–nanoparticle assemblies with complex and precisely
tunable mechanical properties.
Conclusions
In
this work we have used a detailed molecular model of DNA-conjugated
nanoparticles to examine the mechanical properties of DNA–nanoparticle
assemblies. We demonstrate that this mechanical response is strongly
dependent on temperature and suggest the possibility of thermosensitive
materials whose mechanical properties could change by orders of magnitude
upon temperature changes of only several degrees. The mechanical response
is also shown to be strongly dependent on DNA sequence, and subtle
changes in the linking DNA can lead to significant changes in the
qualitative and quantitative features of the mechanical response.
Then, moving beyond existing experiments, we interrogate our molecular
model in order to identify the physics that dictates the observed
sequence-dependent mechanical response. By analyzing the connectivity
of the network, we show that the enthalpic penalty due to base pair
disruption partially explains the observed mechanical response. Most
importantly, however, we demonstrate that the overall mechanical response
of the network is strongly correlated with the deformation of a single
DNA-conjugated nanoparticle. From this observation we suggest a new
sequence-dependent parameter, which we refer to as “shape stiffness”,
that can be used to estimate the mechanical response of a nanoparticle
network from a single nanoparticle. The results presented here are
the first detailed characterization of the mechanical response of
DNA–nanoparticle assemblies, and are the first to demonstrate
that the mechanical response can be tuned. Consequently, they represent
a valuable step toward understanding the mechanical properties of
DNA–nanoparticle assemblies and are useful for dictating their
future directions and applications.
Methods
The molecular
model of DNA-conjugated nanoparticles adopted here
was introduced and validated in previous work.[25] In this model, DNA is represented by 3SPN.2,[32] the latest model in the 3SPN family.[33,34] As a coarse-grained model, 3SPN.2 represents each nucleotide of
DNA with three force sites, one at the center of mass of the sugar,
phosphate, and base. 3SPN.2 has been parameterized to reproduce the
structural (e.g., helix width, major and minor groove widths) and
mechanical (e.g., persistence length) properties of double- and single-stranded
DNA. Additionally, 3SPN.2 can reproduce the melting temperature of
double-stranded DNA and hairpins as a function of sequence and ionic
strength,[32] and has been used in detailed
studies of the single-stranded to double-stranded DNA transition.[35] The DNA-conjugated nanoparticles considered
here are constructed by tethering 3SPN.2 to a coarse-grained nanoparticle
consisting of a bonded network of sites placed on the surface of a
sphere. This model results in nanoparticle sites that are fixed at
their relative locations on the surface of a sphere, and therefore
the positions of DNA strands are also fixed and cannot migrate along
the particle surface. This model has been used to examine the precise
energetics of pairwise DNA–nanoparticle assembly and was shown
to reproduce the correct energy scales and temperature dependence
of DNA–nanoparticle association.[25] In this work, we use 5 nm diameter nanoparticles covered with a
DNA density of 19 pmol/cm2 (unless otherwise noted) as
shown experimentally.[26] This DNA density
corresponds to nine DNA strands on a 5 nm diameter nanoparticle, distributed
approximately uniformly across the particle surface. When referring
to “double DNA loading”, the DNA density was increased
to 38 pmol/cm2, corresponding to 18 strands per 5 nm particle.Several of the DNA sequences considered here (Figure , Seq A and B) are chosen to
correspond to those used in previous experimental studies.[3,27] As in previous work,[25] the reactive “sticky
end” of the DNA sequence (see Figure green box) is chosen to be identical to
that of the experiments. The unreactive “linker” region,
however, is scaled to account for differences between experimental
and simulated particle diameters. The net effect of this scaling has
been examined in detail previously.[25]DNA–nanoparticle lattices were formed using a binary mixture
of nanoparticles coated with different DNA sequences. The DNA sequences
were chosen so that interactions between nanoparticles with different
DNA sequences are attractive, whereas nanoparticles with the same
DNA sequence are not. As a result of these attractive and repulsive
interactions, binary nanoparticle mixtures assemble experimentally
into body centered cubic (bcc) crystal lattices. The protocol used
for assembling the bcc lattices in this work is described in the Supporting Information. When applying uniaxial
extension, constant strain was imposed in a single dimension while
constant stress was imposed in the nonstrained dimensions. To apply
the deformation quasi-statically, the desired strain was applied and
the resulting stress was measured following equilibration to its new
steady state.Simulations were performed in the NVT or NPT ensemble
using a Langevin
thermostat and/or a Parrinello–Rahman barostat with damping
coefficients of 1 and 20 ps, respectively, and a time step of 20 fs.
The Debye–Hückel approximation was used to model the
interactions between phosphate sites which carry a charge of −0.6.[32] Simulations were performed by implementing the
3SPN.2 nanoparticle model[25] into the LAMMPS
simulation package.[36] The approach described
by Thompson et al.[37] was used to calculate
the virial contribution to the pressure from 3SPN.2. The stress tensor
was calculated as the sum of the kinetic and virial components,Note
that while the kinetic component of the
stress was included, its contribution to the stress was observed to
be small.
Authors: Ting I N G Li; Rastko Sknepnek; Robert J Macfarlane; Chad A Mirkin; Monica Olvera de la Cruz Journal: Nano Lett Date: 2012-04-06 Impact factor: 11.189
Authors: Robert J Macfarlane; Byeongdu Lee; Matthew R Jones; Nadine Harris; George C Schatz; Chad A Mirkin Journal: Science Date: 2011-10-14 Impact factor: 47.728
Authors: Kaylie L Young; Michael B Ross; Martin G Blaber; Matthew Rycenga; Matthew R Jones; Chuan Zhang; Andrew J Senesi; Byeongdu Lee; George C Schatz; Chad A Mirkin Journal: Adv Mater Date: 2013-10-25 Impact factor: 30.849
Authors: Daniel J Park; Chuan Zhang; Jessie C Ku; Yu Zhou; George C Schatz; Chad A Mirkin Journal: Proc Natl Acad Sci U S A Date: 2014-12-29 Impact factor: 11.205