Assembly Dynamics of Plasmonic DNA-capped Gold Nanoparticle

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Invited Feature Article

Assembly Dynamics of Plasmonic DNA-capped Gold Nanoparticle Monolayers Thomas L. Derrien, Michelle Zhang, Patrick Dorion, Detlef-M. Smilgies, and Dan Luo Langmuir, Just Accepted Manuscript • DOI: 10.1021/acs.langmuir.8b00484 • Publication Date (Web): 21 May 2018 Downloaded from http://pubs.acs.org on May 21, 2018

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Assembly Dynamics of Plasmonic DNA-capped Gold Nanoparticle Monolayers Thomas L. Derrien, §† Michelle Zhang, † Patrick O. Dorion, ‡ Detlef-Matthias Smilgies, Luo†*

§‡*

Dan

†Biological & Environmental Engineering, Cornell University, Ithaca, NY 14853 ‡Chemical & Biomolecular Engineering, Cornell University, Ithaca, NY 14853 §Cornell High Energy Synchrotron Source, Cornell University, Ithaca, NY 14853 ABSTRACT: The self-assembly of nanoparticles in aqueous solutions promises wide applications but requires the careful balance of many parameters not present in organic solvents. While the presence of long-range electrostatic interactions in aqueous solutions may complicate such assemblies, they provide additional parameters through which to control self-assembly. Here, with DNA-capped gold nanoparticles and through variation of the ionic strength in aqueous solutions, we explored the influence of electrostatic interactions on the adsorption of negatively charged nanoparticles on a positively charged surface. Specifically, we studied the kinetics of nanoparticle adsorption from solution using quartz crystal microbalance with dissipation (QCM-D). We also characterized the structure of the adsorbed monolayers employing a combination of grazing incidence small-angle x-ray scattering (GISAXS) and scanning electron microscopy. We discovered that adsorption kinetics and monolayer structure were under

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control of the DNA ligand length, solution ionic strength, and the salt species. We also precisely fit the kinetics to a modified Langmuir model, which converged to the simple Langmuir model at high ionic strengths of magnesium chloride. We demonstrated that increasing the ionic strength and decreasing the DNA ligand lengths increased the surface coverage while decreasing the nanoparticle-nanoparticle spacing. The DNA-capped nanoparticle system reported here provides a readily applicable platform to control nanoparticle self-assembly in aqueous solution. Finally, we employ this tunability to create a system with tunable plasmonic response. Our kinetic studies of the assembly process and further

characterizations undertaken will facilitate the construction

of nanoparticle arrays with precise structure, and such control will aid in the design of future plasmonic and optoelectronic devices.

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The controlled assembly of nanoscale building blocks into highly ordered mesostructures has resulted in a new generation of nanomaterials with novel optical, electronic and magnetic properties, with applications ranging from data storage1 to biosensing2, 3, 4, 5, 6. In particular, the assembly of colloidal nanocrystals into long-range ordered superstructures has generated strong interest, due to the rich phenomena that are the result of the ordered assemblies7. One such system employing DNA as a designer ligand to mediate the assembly of nanoparticles has achieved remarkable success in rationally designing and building such “artificial solids.”8 While the processes controlling the assembly of such systems in solution is well characterized9, a detailed understanding of the solution phase processes controlling their ability to self-assemble on silicon substrates is not well understood. In order to rationally explore and technically ensure the further development of such self-assembled systems, it is imperative that these nanoscale building blocks can be readily integrated into the ubiquitous photolithography processes of silicon. Recently our group reported the ability to control the crystallization of DNA-AuNPs at the air-water interface by controlling the salt species and ionic strength of aqueous solutions10. While the findings extended 2D nanoparticle crystallization to conditions relevant to real world sensing and diagnostic applications as well as presented a semi-empirical model to predict the behavior of the DNA brush, the applicability of air-water interface crystallization is limited. Extending these phenomena to the liquid-solid interface instead and eventually in the dry state can enable the novel properties of nanoparticle assemblies to be incorporated into nanofabricated devices, merging top-down and bottom up processes thereby allowing unprecedented control at the nanometer scale.


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Characterization and preparation techniques of nanoparticle monolayers are well detailed,11, 12, 13

however, in order to facilitate the attachment of crystalline monolayers at the solid interface

a detailed understanding of the parameters governing the nanoparticles’ adsorption must be evaluated. Of particular importance is how the governing parameters affect the particle adsorption kinetics and the resultant structure of the adsorbed monolayer. While many solution phase parameters may influence assembly properties, control of both the adsorption kinetics and monolayer structure can be imparted by only one crucial parameter- ionic strength. Indeed, this has been shown to be the case for various nanoparticle compositions14, 15, 16 and even proteins17, where electrostatic repulsions between the adsorbates were reduced with increased ionic strength, a result of counterion screening. While such screening of repulsive electrostatics has been shown to increase the total coverage of gold nanoparticles on charged surfaces, it also serves to slow the adsorption kinetics have been fit to both the Langmuir

14, 15, 16, 18

18

. The kinetic trends observed in these studies

as well as the random sequential adsorption

7, 15, 16, 18

models with considerable success. However, to the best of our knowledge, a comprehensive study of the adsorption kinetics of DNA-AuNPs on silicon surfaces from solution has not been reported. DNA-AuNPs provide a nanoparticle construct with many finely tunable and dynamic parameters. Not only can the length of the DNA capping ligand be varied over a large range, and therefore the effective particle diameter, so can the rigidity of the system. For instance, single stranded DNA (ssDNA) leads to a soft, compressible ligand shell19, while double stranded DNA (dsDNA) imparts a rigid ligand shell. Indeed, as we previously demonstrated, ssDNA ligands were compressed to varying degrees by different ionic strength of the buffer solution10. Additionally, nanoparticlenanoparticle interactions were enhanced by the base-pairing regions on the terminal ends of the


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DNA, thereby more effectively guiding the assembly of nanoparticles9,

20, 21, 22, 23, 24

. These

unique properties distinguish the DNA-AuNP system from many of the previous kinetic studies where the “bare” nanoparticles, typically composed of metal cores with an electrostatically absorbed small molecule or ion, such as citrate, served solely to stabilize the nanoparticles in solution. Furthermore, aforementioned studies focused on adsorption in monovalent NaCl solutions, whereas divalent salts such as MgCl2 can greatly change the solution dynamics25, 26, 27, 28

. Here we investigated an entirely new system: the dynamics of the adsorption of ssDNA-

AuNPs on a positively charged silicon surfaces in aqueous solutions of both monovalent and divalent salts. In order to characterize and elucidate the processes controlling the adsorption of DNA-AuNPs on Si we undertook a comprehensive study of DNA-AuNP adsorption on functionalized silicon oxide surfaces using a combination of quartz crystal microbalance with dissipation (QCM-D), scanning electron microscopy (SEM) and grazing incidence small angle X-ray scattering (GISAXS). Specifically we examined the dynamics of gold nanoparticles functionalized with ssDNAs of several lengths, in solutions of various ionic strengths of NaCl and MgCl2, by monitoring the kinetics of adsorption using QCM-D. In addition, we characterized the adsorbed layer using both GISAXS and SEM. With this approach, QCM-D provided time resolved kinetic data, although without insight as to the structure of the adsorbed monolayer. We then observed structure in real-time GISAXS along with SEM. By combining these characterization techniques, a comprehensive understanding of the adsorption process was gained.


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RESULTS AND DISCUSSION Kinetics of particle Adsorption In order to understand the dynamics of DNA-AuNP adsorption on a positively charged silicon dioxide substrate, a broad range of parameters was explored. Specifically, QCM-D was used to probe the kinetics of adsorption and to calculate a final saturation adsorption as a function of three parameters: 1) DNA ligand length 2) ionic strength and, 3) counterion species. Comparing the two kinetic traces obtained in NaCl solutions for the shortest (T10) and longest (T60) ligands (where T10, T30, and T60 refer to the number of thymines of the ssDNA ligand) (Figure 1), two trends were immediately visible. First, for equivalent ionic strengths, the shorter T10 DNA ligands (figure 1A) reached higher saturation coverage than longer T60 DNA ligands (figure 2B). This was not surprising, as the longer DNA ligands occupied more surface area on the silicon surface, thereby reducing the total number of nanoparticles adsorbed. Secondly, increasing the ionic strength facilitated nanoparticle adsorption at saturation. The reason for this phenomenon was twofold. Firstly, increasing the ionic strength served to screen the electrostatic repulsion between the highly negatively charged nanoparticles29. Secondly, as we have previously shown, higher ionic strength also resulted in a more compressed flexible ssDNA ligand brush10,

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, effectively reducing the surface area occupied on the substrate surface per

nanoparticle. The patterns were further confirmed by comparing the saturation coverages at various NaCl ionic strengths for all the ligand lengths tested (figure 1C). It was interesting to note that while increasing the ionic strength increased the saturation coverage for all nanoparticles tested, a greater increase was seen for the smaller DNA ligands. Moreover, while more nanoparticles were adsorbed at higher ionic strengths, the kinetics of this adsorption was slower- it took notably longer to reach saturation coverage at increased ionic strengths. This


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slowed kinetics was again attributed to salt screening effects: the counterions screened not only the nanoparticle-nanoparticle interaction, but also nanoparticle-substrate interaction.

Figure 1: QCM-D adsorption profiles of DNA-AuNPs functionalized with two ligand lengths at various NaCl ionic strengths (top). (A) T10 DNA-AuNPs at (grey) 13 mM NaCl and (black) 133 mM NaCl and (B) T60 DNA-AuNPs at both (dark red) 13 mM and (light red) 133 mM. Two trends were readily visible 1) the time to reach maximum adsorption was longer for higher ionic strengths and 2) shorter ligands allowed a higher mass of adsorbed nanoparticles. Also shown are were the saturation coverages (C) obtained for the three ligand lengths tested, short, T10 ligands (black circles), intermediate, T30 ligands (blue circles), and long, T60 ligands (red circles).


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In previous studies, our group used MgCl2 to control the air-water interfacial assembly of non-base paring DNA-AuNPs. We discovered that DNA-AuNPs in MgCl2 experienced larger DNA compression than in NaCl solutions of equivalent ionic strength, allowing nanoparticles to pack even closer together10. Here, this same effect was found at the solid-liquid interface. Comparing the saturation adsorption of T30 DNA-AuNPs in both monovalent NaCl and divalent MgCl2, the same trend was observed again. For equivalent ionic strengths, MgCl2 (figure 2A) solutions enabled higher surface accumulations in comparison to NaCl solutions (figure 2B). The same reasoning that we applied to the air-water interface earlier 10 could be invoked here - higher DNA compression allowed DNA-AuNPs to pack closer together. This higher surface accumulation enabled by MgCl2 was coupled with a notable speed increase in adsorption kinetics. This effect is illustrated in the kinetic traces shown in figure 2A, where the light blue trace represents the MgCl2 solution and the dark blue the NaCl at ionic strengths of 266 mM in each case. At equivalent ionic strengths, MgCl2 solutions experienced markedly faster kinetics in both the early and later adsorption regimes, reaching the saturation coverage long before the NaCl solution. The T30 DNA-AuNPs in NaCl adsorbed in a more gradual manner, slowly climbing to saturation over the course of the experiment. On the other hand, the T30 DNAAuNPs in MgCl2 rapidly adsorbed to values near their saturation coverage and then quickly leveled off, and effectively ceased adsorption thereafter.


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Figure 2: Comparison of the saturation coverages of T30-DNA-AuNPs in NaCl (dark blue circles) and MgCl2 (light blue circles) at various ionic strengths (A). MgCl2 solutions show a marked increase in DNA-AuNP adsorption. QCM-D adsorption profiles of T30-DNA-AuNPs at 266 mM NaCl (dark blue trace) and MgCl2 (light blue trace) illustrating the faster kinetics and higher adsorption in MgCl2 solutions (B). The difference in the observed adsorption behavior implied that the DNA-AuNPs exhibited different adsorption mechanisms in monovalent and divalent solutions. The adsorption of charged nanoparticles on charged interfaces has been successfully described previously by the random sequential adsorption (RSA) model7,

15, 16, 18

. In the RSA model the adsorbing

nanoparticles are treated as hard disks, which randomly interact with the solid surface. The


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randomly placed disks only deposit when they do not overlap with an already adsorbed disk. Langmuir kinetics has also been successfully used to model the adsorption kinetics of nanoparticles on a charged surface18,

30

. However, the Langmuir model does not account for

adsorbate-adsorbate interactions. In the previously studies, where the nanoparticle surface is passivated with a charged ligand, citrate, electrostatic nanoparticle-nanoparticle interactions can extend several nm past the colloid surface 16. Further complications arise when considering a capping ligand shell, such as with the DNA-AuNPs used here. Not only can DNA ligands impart additional electrostatic considerations, but interparticle attractions can be induced by facilitating hybridization via the use of “sticky ends”

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. As the nanoparticles used here were composed of non-interacting

homomeric polythymine DNA oligomers, the latter interactions were ignored. In modeling the kinetic behavior of the DNA-AuNPs adsorption on the APTES functionalized silicon, a stretched exponential Langmuir model was considered, wherein a power law fit parameter was introduced into the exponential: ഁ

Γ௧ = Γ௠௔௫ ቂ1 − ݁ ିሺ௞௧ሻ ቃ

(1)

Where Γt, is the amount of adsorbed material at time t, Γmax, is the maximum adsorption, and k is the adsorption coefficient reflecting the kinetics. In the stretched exponential function, the fit parameter, β, describes a distribution of coefficients, k, with values closer to 0 describing a broader distribution and a β value of 1 corresponding to a single time constant for the system- a standard Langmuir model. Strong fits to the stretched exponential model were obtained for both the monovalent NaCl and divalent MgCl2 solutions, with the coefficient of determination, R2, ranging between 0.976 and 0.997 (figure 3).


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Figure 3: Kinetic traces obtained by QCM-D of T30-DNA-AuNPs at various ionic strengths of NaCl and MgCl2 along with fitting (black dashed traces) to a stretched exponential Langmuir model. The strong fit to the model observed is confirmed by R2 between 0.976 < R2 < 0.997. The slower adsorption kinetics as ionic strengths increased was seen by the decrease in the magnitude of the coefficient, k, at higher salt concentrations (figure 4, top), in both salt species tested. However, differing trends emerged for the stretched exponential parameter, β (figure 4A). In NaCl solutions, no clear trends occurred, while in MgCl2 the magnitude was higher and the general trend show an increase in β with increasing ionic strength. Remarkably, at the highest ionic strengths tested in MgCl2 solution, β eventually converged to unity. This striking trend indicated that at the highest ionic strengths, where β=1, the adsorbing DNAAuNPs followed Langmuir kinetics. As previously mentioned, a basic assumption of the Langmuir model is that no adsorbate-adsorbate interactions occur. In the case of the highly


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charged DNA-AuNPs used here interparticle Coulombic repulsions could not be neglected, due to the high negative charge of the DNA ligands. Indeed, zeta potential measurements in salt free milliQ water show the surface charge to be -67±2, -60±3, -64±4 mV for the T10, T30, and T60 respectively.

The effective range of these Coulombic repulsions can be related to the Debye

length, κ-1, by equation 2: ఌ ఌ௞ಳ ் మ ಲ௘ ூ

ߢ ିଵ = ට బ ଶே

(2)

where, ε0, is the permittivity of free space, ε, is the dielectric constant, kB, is the Boltzmann constant, T is temperature, NA is Avogadro’s number, and, e, is the elementary charge and I the ionic strength. At the experimental ionic strengths tested the Debye length decreased almost tenfold from ~2.6 nm at 13 mM to 0.30 nm at 1000 mM. In fitting the modified Langmuir model, it could be reasoned that the increase in the stretched exponential parameter, i.e. the narrowing of the distribution of the coefficient, k, was a result of this salt screening at higher ionic strengths. Finally, at the highest ionic strengths, this distribution became a single time constant, converging to Langmuir kinetics, indicating that the interparticle interactions were effectively screened out. While modifications to the Langmuir model such as the Temkin model31 could account for adsorbate-adsorbate interactions, our modified Langmuir model gave rise to the noteworthy finding that not only could the interparticle interactions between adsorbing nanoparticles be effectively eliminated by the addition of salt, but that the salt valency (Na+ vs Mg++) was critical.


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A

0.02 0.018 0.016

k (s-1)

0.014 0.012 0.01

Mg

0.008

Na

0.006 0.004 0.002 0 0

B

200

400 600 800 Ionic Strength (mM)

1000

1200

1.2 1 0.8

β

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

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0.6

Mg Na

0.4 0.2 0 0

200

400 600 800 Ionic Strength (mM)

1000

1200

Figure 4: (A) Plot of the kinetics coefficient, k, to the stretched exponential Langmuir model in NaCl (light blue circles) and MgCl2 (dark blue circles) at various ionic strengths. The reduction in the magnitude of k illustrates the slower kinetics at increasing ionic strengths. (B) Plot of the stretched exponential parameter, β, in NaCl (dark blue circles) and MgCl2 (light blue circles) at various ionic strengths (B). The convergence of the parameter, β, to unity in solutions of high


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MgCl2 ionic strengths indicates that the interparticle interactions can be effectively screened out at high ionic strength of MgCl2. Structure of the Adsorbed Monolayer The above characterization of the kinetics parameters controlling the two-dimensional assembly of DNA-AuNPs at the solid-liquid interface enabled fine-tuning of the nanoparticle deposition time to achieve a desired nanoparticle surface density. Of equal importance was the structure of the adsorbed monolayers. For example, by controlling the distance between adsorbed nanoparticles the plasmonic response could be tuned. In fact, at distances exceeding ~2.5 times the nanoparticle diameter, it has been reported that no significant coupling of the nanoparticles’ plasmons occurs32. For this reason, we sought to correlate these parameters to the structure of the adsorbed DNA-AuNPs via a combination of GISAXS and SEM. An ensemble average of the d-spacing of the nanoparticle monolayer was obtained using GISAXS. Images of the scattering intensity were obtained at 500 mM NaCl ionic strength for all three ligands, as well as at 500 mM MgCl2 for the T30 ligands. 2D images were integrated using the Fit2D software yielding integrated spectra I(q). In order to more easily compare the peak positions, the spectra were normalized by the maximum intensity of the first-order peak (Figure 5A). The trends observed for the saturation coverages in NaCl solutions by QCM-D, whereby longer ligands result in less surface density, suggested that the DNA-AuNPs with longer ligands adsorbed further apart on the positively charges silicon surface. Indeed, these results were consistent in the GISAXS experiments -- the spectra showed increasing interparticle spacing for the longer ligands. This was interpreted by calculating the d-spacing from the position of the first order GISAXS peak (d=2π/q, note d-spacing≠ nearest neighbor spacing). For the spectra shown,


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the d-spacings calculated were: ~16, 32, and 45 nm for the T10, T30, and T60 ligands, respectively. The variation in interparticle distance observed was consistent with what was been reported for three-dimensional DNA-AuNP crystals33. Similarly, the increased surface coverage recorded in MgCl2 solutions was reflected by the shorter d-spacing- T30-DNA-AuNPs adsorbed with a d-spacing of ~30 nm in 500 mM MgCl2 compared to ~32 nm in NaCl solution of equivalent ionic strength. GISAXS experiments were also carried out over a range of NaCl concentrations for the longest, T60 DNA ligands. Once more, the peaks shown here were normalized (figure 5B). The trends discerned in the QCM-D experiments were again confirmed -- increased solution ionic strengths led to a shorter interparticle spacing, i.e. a larger number of adsorbed nanoparticles. The range of spacings was wide: in pure water (no salt) the T60-DNA-AuNPs adsorbed to a final d-spacing of ~80 nm, while at 500 mM NaCl the d-spacing was ~44 nm. It is important to note that the largest peak shift occurred between 0 and 13 mM NaCl, where the spacing changed from ~80 nm to ~64 nm, illustrating the importance of solution ionic strength in controlling the adsorption of nanoparticles to the surface. A power law fit (SI) of the resulting DNA length (L) revealed that L~I-0.13. This scaling exponent is in contrast to that which was observed at the airwater interface10,

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of -0.2. The latter exponent matches well with theoretical predictions and

bulk solution experiments with spherical polyelectrolyte brushes. We ascribe this difference of the scaling exponent to the strong adsorbate-substrate interaction that pins arriving nanoparticles and prevents the monolayer from attaining its equilibrium density. In conjunction with the reduced spacing the appearance of an additional second-order peak was observed in the higher ionic strength solutions, most notably at q ≈ 0.28 nm-1. The appearance of this peak implied that


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at higher ionic strength the DNA-AuNPs were adsorbing in a more regular, more ordered arrangement, further confirming the influence of ionic strength.

A Normalized Scatering Intensity

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1.2

1 T60 Na T10 Na

0.8

T30 Na T30 Mg

0.6

0.4

0.2

0 0.05

0.15

0.25 q (nm-1)

0.35

0.45


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B

1.2 Increasing [NaCl]

Normalized Scattering Intesnity

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1 0.8 0 mM NaCl 13 mM NaCl

0.6

66 mM NaCl 133 mM NaCl

0.4

266 mM NaCl 500 mM NaCl

0.2 0 0.05

0.15

0.25 q (nm-1)

0.35

0.45

Figure 5: 1D GISAXS curves of the DNA-AuNPs monolayers. The curves, obtained at 500 mM ionic strength, show the shift of the first order peak to smaller values, i.e. increasing interparticle spacing, for longer ligand lengths, as well as the difference obtained in NaCl and MgCl2 for T30DNA-AuNPs (A). 1D GISAXS curved of T60-DNA-AuNP monolayers obtained at various ionic strengths of NaCl (B). From the curve, it can be seen that increasing ionic strength decreases interparticle spacing. The GISAXS spectra obtained above correlated well with the patterns recorded in the QCM-D experiments; yet, they did not provide information about the intermediate adsorption states. In order to acquire data from these transitional arrangements time-resolved GISAXS experiments were carried out. Spectra were collected, for T30-DNA-AuNPs in 266 mM MgCl2 in a sealed humidity chamber, with measurements taken every 10 minutes, so as to avoid damage to DNA by the X-ray beam. The evolution of the structure of the adsorbed nanoparticle


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monolayer was clearly seen in both the intensity and the position of the first order peak (figure 6A). The increasing intensity indicated the accumulation of nanoparticles while the peak shift was characteristic of the decreased interparticle spacing, as discussed above. The d-spacing and peak intensity were plotted in figure 6B. Upon the first detectable nanoparticle peak, after ca. 10 minutes, the d-spacing was ~68 nm, which rapidly decreased to ~41 nm before eventually leveling off around 38 nm d-spacing. Despite the difference in nanoparticle concentration, this rapid decline in spacing followed by a slow decrease closely mirrored the kinetics observed in the QCM-D profile in figure 2.


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Figure 6: Kinetic evolution of the structure of the adsorbed nanoparticle monolayer of T30DNA-AuNPs in 266 mM NaCl (A). The GISAXS curves show a rapid decrease in spacing at the early in spacing that then slowly approaches its saturation spacing (B). Further confirmation of the trends observed by both QCM-D and GISAXS was obtained by direct observation using SEM of the nanoparticle assemblies at 500 mM ionic strength. From the micrographs in Figure 7, the nanoparticle density, Γ, was precisely calculated and related to the QCM-D mass density measured, while the d-spacing, as estimated by GISAXS correlated closely to the average nearest neighbor spacing (Dnn) calculated from SEM. As expected, the images show increasing interparticle spacing, and thus decreasing surface density with increasing


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ligand length. Once again, the influence of the salt valency was evident; the T30-DNA-AuNPs in MgCl2 solution (figure 7B) formed a denser nanoparticle monolayer than in NaCl (figure 7C). These trends were quantitatively confirmed by the Dnn and the nanoparticle densities summarized in table 1. Interestingly, the Dnn values reported here were smaller than those we had previously reported at the air-water interface10. This new discovery highlighted a disparity between the assemblies at the two interfaces. While the DNA-AuNPs at the air-water interface were in a dynamic system, the nanoparticles assembles on APTES-functionalized silicon were in a static, irreversible arrangement16. This is because the Gibbs layer formed at the air-solution interface was stabilized by surface tension, while the particles adsorbed on the functionalized substrate were strongly bound by electrostatic interactions. This fact can be exploited to form robust nanoparticle monolayers capable of withstanding a variety of harsh environmental conditions. However this strong electrostatic adsorption may limit the lateral diffusion of the bound nanoparticles and therefore prevent the ordering of the system. Here, the stabilizing effect of the longer ligands was also apparent. Upon inspection of the T10-DNA-AuNPs (figure 7A) the clustering of the nanoparticles was indicative of precipitation, although no large precipitates were present in the sample. Conversely, all of the longer ligands, T30 in both NaCl and MgCl2 solutions, as well as T60 resulted in evenly distributed monolayers. Such stability to high ionic strengths is an advantage unique to DNA ligands. Whereas citrate stabilized nanoparticles showed aggregation at high ionic strengths34 18, DNA AuNPs facilitated the controlled assembly of nanoparticle superstructures in monovalent, divalent salts, and trivalent salts10, 21, 35, 36.


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Figure 7: Scanning electron micrographs of DNA-AuNP monolayers with varying ligand lengths. The images show the influence of ligand length and salt species on nanoparticle surface density, whereby longer ligands result in a less dense monolayer, and at equivalent ionic strength (500 mM), MgCl2 solutions (B) result in a higher surface density than NaCl solution (C). Each micrograph is 1000 x 1000 nm.


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Table 1: Average nanoparticle nearest neighbor spacing, Dnn, and nanoparticle density for various ligand lengths at 500 mM ionic strength NaCl as calculated from SEM images, the results obtained in 500 mM ionic strength MgCl2 are shown in parentheses. Ligand T10 T30 T60

Dnn (nm) 20.4 ± 5.9 31.2 ± 2.7 (25.6 ± 3.0) 39 ± 5.8

Γ (NPs/µm2) 1350 950 (1140) 490

The well-defined control of the nanoparticle monolayers described above was mainly due to employing DNA as a nanoparticle capping ligand. Our distinctive approach of using non-base pairing DNA gave rise to a simple system with multi-dimensional tunability. Nanoparticle coverage and monolayer structure were readily adjustable by a combination of three tunable parameters: 1) DNA ligand length, 2) ionic strength, and 3) salt species. Importantly, the fabrication consisted of only one simple step: drop-casting a nanoparticle solution on a substrate. The development of such a straightforward yet precise system capable of nanoscale control is essential and significant to the scalability of nanoparticle-based technologies. To this end, we easily applied our system to tune the optical response of our nanoparticle assemblies taking the advantage of the fact that the shorter interparticle spacings obtained fell well within the plasmonic regime32. As a demonstration, here we show that by simply assembling on APTES functionalized glass, the surface plasmon peak of the gold nanoparticles were shifted by varying the DNA ligand length. For instance, at 500 mM ionic strength of MgCl2, the plasmon peak scaled inversely to the expected interparticle distance (Figure 8A, B), consistent with previous observations37. Compared to the ~525 nm plasmon peak of the nanoparticles in solution, the peak shifts observed ranged from ~28 nm for the shortest T10 DNA ligands, to ~16 nm for the longest T60 DNA ligands. Surprisingly, the magnitude of the peak shit was greater than what


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would have been expected from theoretical calculations32, presumably due to the large variation in spacings seen. The magnitude of the plasmon peak, which was proportional to the number of adsorbed nanoparticles mirrored the trends seen by QCM, SAXS, and SEM whereby the smaller DNA ligands allowed a higher density of nanoparticles to adsorb onto the positively charged surface, thereby decreasing the interparticle distance. Significantly, the electrostatic adsorption of the negatively charged DNA-AuNPs on the positively charged SiO surface yielded extremely robust nanoparticle assemblies capable of withstanding a wide variety aqueous conditions incubating the assembled nanoparticles in high ionic strength solutions did not at all affect the resultant absorbance spectrum. This property can be potentially exploited to produce plasmonic biosensors capable of withstanding various aqueous environments in which other nanoparticle systems are unstable.


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Figure 8: Absorbance spectra for the T10 (purple trace), T30 (green trace), and T60-DNAAuNPs (blue trace) demonstrating the shift of the plasmon peak with respect to the aqueous (red trace) DNA-AuNPs (A). The position of the surface plasmon peak is plotted as a function of the DNA length (B). CONCLUSIONS The extensive set of experiments performed via a unique combination of QCM-D, GISAXS, and SEM studies gave rise to a comprehensive understanding of the parameters governing the adsorption of negatively charged DNA-AuNPs on a positively charged silicon surface. Tunability of the surface density of nanoparticles was afforded by altering three parameters: 1) DNA ligand length, 2) solution ionic strength, and 3) salt species. By increasing the DNA ligand length, the amount of nanoparticles adsorbed on the silicon surface decreased, due to the increased surface area occupied by the longer ligands. Of equal importance was the solution ionic strength. The accumulation of nanoparticles on the surface was directly proportional to the ionic strength. However, upon increasing the ionic strength the kinetics of adsorption were slowed. A final parameter, salt valency exhibited control over both the kinetics and the accumulation of nanoparticles. In NaCl solutions, DNA-AuNPs adsorbed to noticeably lower saturation values than in solutions of a divalent counterion, MgCl2. Moreover, modeling of the adsorption kinetics revealed the adsorption mechanism differed between the two salt solutions: at the highest ionic strengths of MgCl2 the adsorption followed Langmuir kinetics. GISAXS studies monitoring the evolution of the interparticle spacing as a function of the aforementioned three parameters further confirmed the previous trends. Additional analysis by SEM confirmed the above trends and enabled precise measurements of the nanoparticle nearest neighbor spacing and surface coverage. Finally, the applicability of this system is demonstrated


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by showing that the parameters characterized can lead to nanoparticle assemblies with tunable plasmonic response. The characterization of the parameters described herein will provide a framework from which to build nanoparticle monolayers of precise structure. Such nanoscale control will aid in the design of future plasmonic devices for biosensing and optoelectronics.38 Future experiments exploring the influence of nanoparticle size and base pairing interactions, as well as different nanoparticle compositions beyond gold will provide additional insight into these tunable nanoparticle platforms. Methods Synthesis of DNA-capped Gold Nanoparticles The gold nanoparticles (15 nm diameter) (AuNPs) were purchased from Ted Pella. The oligonucleotides were pre-conjugated with a 5’ thiol group from Integrated DNA Technologies. All solutions used were prepared in 18.2 MΩ water. Prior to attachment of the oligonucleotides to the AuNPs, the thiol group was first deprotected with tris(2-carboxyethyl)phosphine hydrochloride (TCEP) by incubating the oligonucleotides at a 1:5 (DNA:TCEP) ratio for 30 minutes. The oligonucleotides were then added to the AuNPs at a DNA:AuNP ratio of 1200:1 to ensure maximum surface coverage, then shaken overnight at 500 rpm at room temperature after which NaCl was slowly added over a period of 8 hours to a final concentration of 750 mM, reducing DNA-DNA repulsion and further increasing the DNA coverage. The nanoparticles were then purified of salt and excess DNA by several centrifugation cycles in pure water. Three different non-basing pairing single stranded sequences were used for the QCM studies, each comprising 10, 30, or 60 thymine bases, hereafter referred to as T10, T30, and T60, respectively.


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Quartz Crystal Microbalance with Dissipation Studies The primary instrument was a quartz crystal microbalance with dissipation system (QSense QCM-D E1, Biolin Scientific). The QSense QCM-D instrument is optimized to operate in a liquid environment. All measurements were conducted using the proprietary QSense software QSoft 401. QSense QCM-D sensors, with a 50 nm silicon oxide top coating and a 5 MHz quartz crystal oscillator were purchased from Biolin Scientific. Frequency shifts ∆f and attenuation D were measured simultaneously using various overtones. The frequency traces recorded in these studies were then converted to a real mass density (ng/cm2) using the Sauerbrey model39 in the QSense QTools data analysis software. The Sauerbrey model (Equation 1) relates the change in the fundamental resonance frequencies and its overtones to the adsorbed mass on the silicon oxide layer: ∆݉ = −

஼∆௙

(1)

௡

where, ∆m is the change in adsorbed mass, ∆f, is the change in frequency, n, is the overtone number and, C, is a constant specific to the substrate, which for silicon oxide-coated quartz oscillators is 17.7 ng cm-2 s-1. For soft films the viscoelastic model must be used which also takes into account the attenuation of the vibrations through the interaction of the adsorbate with the liquid phase. However, we found that the Sauerbrey model held for adsorbed DNA-AuNP monolayers, which was further confirmed by the lack of significant changes in the dissipation. In order to maximize the DNA-AuNP loading on the silicon surfaces, a positively charged silane, 3-aminopropyl triethoxysilane (APTES), was functionalized on the silicon surface to attract the negatively charged phosphate groups at the DNA backbone. The amine group of APTES has a pKa of about 10

40

, and hence is fully protonated to form a –NH3+

endgroup in aqueous solution and neutral pH. Similarly the DNA phosphate groups are mostly


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deprotonated and negatively charged. APTES self-assembled monolayers were obtained by first incubating the QCM-D sensor in a 2% APTES solution in 95% ethanol overnight. After rinsing in pure ethanol followed by a rinsing in isopropanol, the sensor was baked at 95 °C for 1 hour followed by another rinsing cycle. In order to obtain measurements with minimal noise and drift, dry sensors were allowed to equilibrate on the instrument for ca. 10 minutes, until there was no visible natural frequency change over ca. 60 s. Then a drop of approximately 200 µL of the appropriate ionic strength solution was deposited in the active area of the sensor and the sensor was allowed to equilibrate over approximately 15 minutes. Once the sensor was deemed equilibrated, a stock solution of nanoparticles was added to a final nanoparticle concentration of ~5 nM, and the sample covered to avoid drying. QCM-D traces were acquired, until no further frequency changes were detectable. Samples were tested at ionic strengths of 0, 13, 66, 133, and 266 mM in NaCl as well as up to 1000 mM in MgCl2. Grazing Incidence Small Angle X-ray Scattering Experiments Grazing incidence small angle X-ray scattering experiments (GISAXS) were performed at the D1 experimental station at the Cornell High Energy Synchrotron Source (CHESS). A multilayer monochromator delivered an incident X-ray beam with a flux of ~1012 photons s-1 mm-1 and a bandwidth of 1.5%. The dimensions of the collimated X-ray beam were 0.3 mm (horizontal) and 0.2 mm (vertical). During these experiments a MedOptics CCD detector with a pixel size of 46.9 x 46.9 microns was used, with a sample-to-detector distance of 1873 mm, a wavelength of 1.16 Å, and an incident angle of 0.25°. The gold electrodes of the QCM-D sensors complicate direct observation of the QCM-D samples by GISAXS. Therefore, GISAXS samples were prepared on APTES-functionalized by incubating the samples in a humidity chamber with a


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reservoir of equal salt concentration for ~4 hours. The samples were then washed several times with milli-Q water to remove unbound nanoparticles and excess nanoparticle solution. Time-resolved scattering images were collected by placing a ca. 5 µL droplet of DNAAuNPs in salt solution on a cleaned, freshly APTES functionalized Si substrate. In order to avoid drying effects, the substrate was placed in a sealed sample environment chamber with a water reservoir of equal salt concentration 21. The concentration of the nanoparticles in the droplet was approximately 0.05 nM, which is ~100 fold more dilute than the samples used for the QCM-D experiments. This concentration was chosen to minimize scattering from the bulk solution and to maximize scattering from surface adsorbed nanoparticles. To avoid DNA damage from the incident X-ray beam41, 3 s exposure images were taken every 2 minutes at different locations on the droplet, with the same location being illuminated every 10 minutes. Absorbance Measurements Optical absorbance measurements were obtained using a FIlmetrics F40 configured for transmission mode. Samples were prepared on glass coverslips by first cleaning the coverslips in a piranha solution for 15 minutes followed by rinsing and applying the same silanization protocol described above. Scanning Electron Microscopy SEM images of the dry GISAXS samples were obtained on a LEO 1550 FESEM. Nanoparticle density and nearest neighbor spacing, Dnn, were calculated using ImageJ. Zeta Potential Measurements


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Zeta potential measurements were carried out on a Malvern Zetasizer Nano in salt free water at a pH of 7.5. The

AUTHOR INFORMATION Corresponding Authors *Email: [email protected] *Email: [email protected] Notes The authors declare no competing financial interest. ACKNOWLEDGMENT T.L.D. acknowledges support from NSF IGERT under DGE-0903653. We thank Ruipeng Li, CHESS, for sharing his insights on the QCM-D system. This research is funded by NSF award SNM-1530522 and is based upon work at the Cornell High Energy Synchrotron Source (CHESS) which is supported by the NSF & NIH/NIGMH via NSF award DMR-1332208. This work also made use of the Cornell Center for Materials Research (CCMR) shared facilities supported by DMR- 1120296. REFERENCES REFERENCES 1. Sun, S.; Murray, C. B.; Weller, D.; Folks, L.; Moser, A. Monodisperse FePt nanoparticles and ferromagnetic FePt nanocrystal superlattices. Science 2000, 287 (5460), 1989-92. 2. Lee, J.; Hernandez, P.; Lee, J.; Govorov, A. O.; Kotov, N. A. Exciton-plasmon interactions in molecular spring assemblies of nanowires and wavelength-based protein detection. Nat Mater 2007, 6 (4), 291-5.


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21. Campolongo, M. J.; Tan, S. J.; Smilgies, D. M.; Zhao, M.; Chen, Y.; Xhangolli, I.; Cheng, W.; Luo, D. Crystalline Gibbs monolayers of DNA-capped nanoparticles at the air-liquid interface. ACS Nano 2011, 5 (10), 7978-85. 22. Park, S. Y.; Lytton-Jean, A. K.; Lee, B.; Weigand, S.; Schatz, G. C.; Mirkin, C. A. DNAprogrammable nanoparticle crystallization. Nature 2008, 451 (7178), 553-6. 23. Nykypanchuk, D.; Maye, M. M.; van der Lelie, D.; Gang, O. DNA-guided crystallization of colloidal nanoparticles. Nature 2008, 451 (7178), 549-52. 24. Zhang, Y.; Lu, F.; Yager, K. G.; van der Lelie, D.; Gang, O. A general strategy for the DNA-mediated self-assembly of functional nanoparticles into heterogeneous systems. Nat Nanotechnol 2013, 8 (11), 865-72. 25. Matubayasi, N.; Matsuo, H.; Yamamoto, K.; Yamaguchi, S.-i.; Matuzawa, A. Thermodynamic Quantities of Surface Formation of Aqueous Electrolyte Solutions. Journal of Colloid and Interface Science 1999, 209 (2), 398-402. 26. Guo, X.; Ballauff, M. Spherical polyelectrolyte brushes: Comparison between annealed and quenched brushes. Physical Review E 2001, 64 (5), 051406. 27. Koltover, I.; Wagner, K.; Safinya, C. R. DNA condensation in two dimensions. Proceedings of the National Academy of Sciences 2000, 97 (26), 14046-14051. 28. Chen, H.; Meisburger, S. P.; Pabit, S. A.; Sutton, J. L.; Webb, W. W.; Pollack, L. Ionic strength-dependent persistence lengths of single-stranded RNA and DNA. Proceedings of the National Academy of Sciences 2012, 109 (3), 799-804. 29. Bishop, K. J.; Wilmer, C. E.; Soh, S.; Grzybowski, B. A. Nanoscale forces and their uses in self-assembly. Small 2009, 5 (14), 1600-30. 30. Kakkassery, J. J.; Abid, J.-P.; Carrara, M.; Fermin, D. J. Electrochemical and optical properties of two dimensional electrostatic assembly of Au nanocrystals. Faraday Discussions 2004, 125 (0), 157-169. 31. Temkin, M., Pyzhev, V.. Adsorption of Benzene in Batch System in Natural Clay and Sandy Soil. Acta Physico Chemica URSS 1940, 12, 217-222. 32. Jain, P. K.; El-Sayed, M. A. Universal scaling of plasmon coupling in metal nanostructures: extension from particle pairs to nanoshells. Nano Lett 2007, 7 (9), 2854-8. 33. Hill, H. D.; Macfarlane, R. J.; Senesi, A. J.; Lee, B.; Park, S. Y.; Mirkin, C. A. Controlling the lattice parameters of gold nanoparticle FCC crystals with duplex DNA linkers. Nano Lett 2008, 8 (8), 2341-4. 34. Badawy, A. M. E.; Luxton, T. P.; Silva, R. G.; Scheckel, K. G.; Suidan, M. T.; Tolaymat, T. M. Impact of Environmental Conditions (pH, Ionic Strength, and Electrolyte Type) on the Surface Charge and Aggregation of Silver Nanoparticles Suspensions. Environmental Science & Technology 2010, 44 (4), 1260-1266. 35. Kewalramani, S.; Guerrero-Garcia, G. I.; Moreau, L. M.; Zwanikken, J. W.; Mirkin, C. A.; Olvera de la Cruz, M.; Bedzyk, M. J. Electrolyte-Mediated Assembly of Charged Nanoparticles. ACS Cent Sci 2016, 2 (4), 219-24. 36. Zhang, H.; Wang, W.; Hagen, N.; Kuzmenko, I.; Akinc, M.; Travesset, A.; Mallapragada, S.; Vaknin, D. Self-Assembly of DNA Functionalized Gold Nanoparticles at the Liquid-Vapor Interface. Advanced Materials Interfaces 2016, 3 (16), 1600180-n/a. 37. Cheng, W.; Campolongo, M. J.; Cha, J. J.; Tan, S. J.; Umbach, C. C.; Muller, D. A.; Luo, D. Free-standing nanoparticle superlattice sheets controlled by DNA. Nat Mater 2009, 8 (6), 519-25.


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Assembly Dynamics of Plasmonic DNA-capped Gold Nanoparticle

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