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Size Selective Adsorption of Gold Nanoparticles by Electrostatic Assembly Julian Andreas Lloyd, Soon Hock Ng, Timothy J. Davis, Daniel E. Gomez, and Udo Bach J. Phys. Chem. C, Just Accepted Manuscript • DOI: 10.1021/acs.jpcc.6b10218 • Publication Date (Web): 09 Jan 2017 Downloaded from http://pubs.acs.org on January 9, 2017

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The Journal of Physical Chemistry

Size Selective Adsorption of Gold Nanoparticles by Electrostatic Assembly Julian A. Lloyd1,3, Soon Hock Ng1,3, Timothy J. Davis2,3, Daniel E. Gómez2,3 and Udo Bach1,2,3* 1 Department of Materials Science and Engineering, Monash University, Clayton, VIC 3168, Australia 2 Commonwealth Scientific and Industrial Research Organisation, Manufacturing, Research Way, Clayton, VIC 3168, Australia 3 Melbourne Centre for Nanofabrication, Wellington Road 151, Clayton 3168, Australia

ABSTRACT: In this study we show that electrostatic interactions between charged substrates containing pre-attached nanoparticles and bi-disperse nanoparticle colloids can be engineered to achieve size selective adsorption and dimer formation. Electrostatic interactions enable the assembly of the dimers with high yields due to the interplay between attractive and repulsive forces resulting from charges confined on the particles and substrate surfaces. We investigate in detail the effects of temperature, incubation time and particle mixing ratios of the bidisperse solution and benchmark the size-selectivity for different scenarios. Driving forces of the assembly process are explained using DLVO theory (Derjaguin, Landau, Verwey and Overbeek).

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Introduction We have recently shown that electrostatic self-assembly can be used to form regular arrays of surface confined gold nanoparticle (AuNP) dimers in a self-limiting 2-step electrostatic assembly process.1 In this process, we carefully control the adsorption behavior of positively charged AuNPs (satellites) onto a substrate with negatively charged AuNPs (cores). The basic concept of the adsorption process is depicted in Figure 1. In a first step, negatively charged (core) particles are adsorbed onto a substrate that has a positive surface charge. In a second step, this substrate is immersed in a colloidal solution of positively charged (satellite) particles. The complex interplay between the electrostatic inter-particle and particle-surface forces creates a “funneling” potential energy barrier (see Figure 2a). This funnel guides the positively charged satellite particles towards the negatively charged cores. In this study we show that the potential energy barrier that the satellites have to overcome during their approach to the cores is strongly dependent on the size of the satellite particles. The size-dependence of the electrostatic barrier can be used to hinder the adsorption of bigger nanoparticles while facilitating the adsorption of smaller ones, thus providing a size-selective adsorption from a bi-disperse satellite particle solution. To investigate the size selectivity of the electrostatic dimer-forming process, we calculate interaction energy maps and activation energy barriers for different satellite particle sizes and experimentally study the adsorption of satellite particles from bi-disperse solutions. We present a statistical study of the adsorption yields and size-selectivity as a function of assembly temperature, time and mixing ratio of the bi-disperse colloid and explain the limits of the assembly process and the employed theoretical calculations.


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Figure 1: Schematic illustration of the electrostatic, 2-step assembly process. Starting with a positively charged (green) SiO2/Si substrate and negatively charged (red) particles (cores) an array of uniformly distributed cores is created in step 1. In a second step, these substrates are exposed to a colloidal solution of positively charged particles (satellites) of two different sizes. The cores act as adsorption centers for these satellites, facilitating the dimer-forming process and favoring the adsorption of smaller particle over bigger ones. Controlled adsorption techniques like this can be used to selectively deposit particle species from a mixed colloid onto a substrate. This selectivity could be exploited e.g. for targeted sensing and biomedical applications.2–6 Different from already successfully demonstrated magnetic separation methods,5,7–9 the proposed electrostatically driven process is independent of the nanoparticle material. The only requirement is a suitable surface chemistry to confine charged molecules on the nanoparticle surfaces. These chemistries are well established, as electrostatic self-assembly of nanoparticles already plays an important role in various bottomup fabrication techniques.10–14 Applications range from decorating solar cells with gold nanoparticles (AuNPs)15 and photocatalysts16 to nanoparticle assemblies for sensing applications17. S3 ACS Paragon Plus Environment


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Experimental Methods Commercially available AuNPs (TedPella Inc.) of three different sizes (20, 30 and 50 nm) were used without further purification. Sizes were confirmed using transmission electron microscopy (TEM). Functionalization of the particles to confine charge at their surface was achieved using known protocols.1 Positively charged particles An initial volume of one milliliter of 20 and 50 nm particles was washed once with 0.9 ml MilliQ water by centrifugation and then concentrated to 0.1 ml. 25 µl of a 24 mM N,N,Ntrimethyl-(11-mercaptoundecyl)ammonium chloride (TMAC, ProChimia) solution or 2.4 µl of a 12 mM TMAC solution were added, followed by addition of a cetyltrimethylammonium bromide (CTAB, GFS chemicals) solution (6 mM, 100 µl). After incubating overnight in a Thermomixer (Eppendorf ThermoMixer C) at 20 ˚C, the particles were washed by centrifugation with MilliQ water (see Supplementary Information). Negatively charged particles An initial volume of 1 ml of 30 nm AuNPs was concentrated to 0.1 ml and then mixed with 5 µl of a 2% TWEEN 20 (Sigma Aldrich) solution, 30 µl of 0.1 M phosphate buffer (pH 7), 50 µl of 2 M NaCl solution, 20 µl of 100 nM thiolated DNA solution and 5 µl 100 mM Bis(psulfonatophenyl)phenylphosphine dihydrate dipotassium (BSPP, Sigma Aldrich). Following an overnight incubation in the Thermomixer at 20 ˚C, the mix was washed by centrifugation (see Supplementary Information) and re-dispersed to 1 ml with MilliQ. Substrates functionalization A silica coated (100 nm) silicon wafer cut into 4 by 6 mm pieces was used as substrate for the self-assembly. After a cleaning step with piranha solution, the substrates where incubated in

a

95/3/2

volume

%

solution

of

99.9%

Ethanol,


MilliQ

water

and

(3-

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aminopropyl)triethoxysilane (APTES, Sigma Aldrich) for one hour. The substrates were then washed with ethanol and baked at 110 ˚C for 10 minutes. Particle assembly The negative core particles were electrostatically assembled on the functionalized substrates by immersing a substrate in 200 µl of a core particle solution of optical density 0.1 at 65 ˚C for two hours. The SiO2/Si samples were then washed in MilliQ and dried under a nitrogen stream. The so prepared templates were then immersed in a 200 µl mix of 20 nm and 50 nm satellite particles with a density of 1.7 * 1011 particles/ml for a given time at a defined temperature and afterwards washed in MilliQ again. Particle concentrations of the initial solutions were calculated from UV-Vis data of the colloidal solutions as specified by TedPella Inc. based on mean-free-path corrected Mie-theory calculations (Supplementary Information Figure S1).18 The particles were stable for several days before precipitation started to occur. Theoretical considerations In order to calculate the barrier heights and the effect of the particle size and charge, the electrostatic interactions have been modeled by means of DLVO theory (Derjaguin, Landau, Verwey and Overbeek).1,19–21 This theory accounts for the attractive interaction between the differently charged particles (Eatt), van der Waals interactions (EVdW) and repulsive electrostatic interaction between approaching particle and surface (Erep). The total interaction energy (Etot) can therefore be written as a linear combination:

= + +

(1)

EVdW was calculated as in previous studies of similar systems (see Supplementary Information, Theoretical modelling).1,22,23 The electrostatic interactions were taken into account as linear combinations of sphere-plane and sphere-sphere interactions:



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= 4

/

=

exp (−$%)

, '()* )+ 0 1 .

20 31

3 exp (−$(% − 23 ))

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(2)

(3)

In these equations, ε0 and εr are the permittivity of free space and the relative dielectric constant of water, respectively. The Boltzmann constant is given by kB, the electron charge by

e. The radii r+, r- and z are geometric parameters as depicted in the inset in Figure 2a. T represents the absolute temperature during the assembly process. κ is the Debye-Hückel parameter, which depends on the ionic strength of the electrolyte solution (see Supplementary Information, theoretical modelling). The most important parameters are the scaled effective surface potentials Yx (where x = “+”, “-“ or “APTES”) as they provide a measure for the surface charge of the substrate and particles. They can be approximated according to the method of Ohshima (see Supplementary Information, theoretical modelling) and ultimately depend on the surface zeta potentials ζ.24,25 Thus, the variable experimental input parameters for the calculations are the zeta potentials of the particles and substrate along with the temperature and ionic strength of the solution. Calculating Etot at different coordinates (d, z) (Figure 2a, inset) yields the interaction energy maps shown in Figure 2a. The maps show the expected funnel effect:19 i.e. a gradient in the (repulsive) interaction energy guiding the approaching particle towards the adsorption site for two different sized satellite particles (left: 50 nm, right: 20 nm). It is also evident that there is a barrier present that particles have to overcome in order to reach the core particle (Figure 2b).


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Figure 2: Interaction energy landscapes: a) Calculated maps of the total interaction energy (Etot) of a positively charged AuNP (left: 50 nm, right: 20 nm) at position (d, z) and a negative 30 nm AuNP (indicated in yellow) sitting on a positive charged surface at (0, 0). Blue colors indicate attractive and red indicate repulsive interaction energies. The dotted lines mark where the Etot equals the mean thermal energy of the particles (at 20 ˚C). Inset: Schematic of the geometric setup for the calculations in a) and b). b) Dependence of Etot for different sized particles on z when approaching vertically towards the core particle (d = 0). The black dashed line indicates the thermal energy at 20 ˚C. c) Maxwell-Boltzmann distribution (orange; see Supplementary Information, theoretical modelling) at T = 20 ˚C. The black dashed line indicates the mean thermal energy of the particles, the blue and the green line mark the energies of the barriers for 50 and 20 nm particles (as shown in b). S7 ACS Paragon Plus Environment


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At 20 ˚C the barrier for a 20 nm particle is 50 meV. This is only 0.5 kBT (12 meV) higher than its mean thermal (kinetic) energy (Figure 2b, green line). For the 50 nm AuNPs, the barrier is in turn 4.8 kBT (120 meV) higher than its mean thermal energy (Figure 2b, blue line). While for the 20 nm particles the barrier height is in a range where experiments have shown high yield electrostatic dimer assembly1, for the 50 nm ones the barrier is in a range where dimer formation is not efficient.1 To roughly estimate the implications of this difference in barrier heights for the potential assembly of nanoparticles, we have calculate the Maxwell-Boltzmann kinetic energy distribution (Supplementary Information, theoretical modelling) of the particles at 20 ˚C (Figure 2c). In Figure 2c A20 (A20 = 0.266) and A50 (A50 = 0.007) represent the fraction of the population of the 20 or 50 nm particles (respectively) that has a thermal energy higher than the corresponding barrier. Using this very simple approach, the adsorption of the 20 nm AuNPs is favored (by a factor of 38:1) as there is a higher fraction of 20 nm AuNPs with an energy higher than their adsorption barrier. With these calculated population fractions, we can now compare the concentrations of the different sized particles in the area where the repulsive interaction reaches its maximum (the location of the barrier). The particles are exposed to a repulsive potential corresponding to their size. Therefore, only particles with an energy equal or higher than this potential are expected to be located in this area. Particles with lower energy are driven away to areas with lower Etot. We therefore expect a 38 times higher concentration of 20 nm particles at this point (assuming equal numbers of 20 nm and 50 nm particles in the initial solution). This, in turn, would lead to a higher probability for 20 nm satellite particles to adsorb on the cores and thus a sizediscriminative adsorption process. The theoretical effect of the core and satellite particle zeta potentials on the sizedependence of the barrier was investigated as well. From these calculations (see Supplementary Information, Figure S6) it could be seen that in order to increase the barrier S8 ACS Paragon Plus Environment

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height differences for 20 and 50 nm particles, a higher zeta potential for the satellite particles is beneficial and thus a maximization of these potentials was pursued experimentally. Besides these surface charge induced selectivity effect, we can further use the StokesEinstein-Sutherland (SES) equation to estimate how the particle size affects their diffusion and whether that leads to an enhanced selectivity:26

5 =

(4)

6 ( 7

with 8 as dynamic viscosity and r the radius of a spherical particle. Due to this inverse proportionality to the particle radius, we expect that the 20 nm particles diffuse 2.5 times faster than the 50 nm ones. This higher diffusion speed is another factor that contributes to the preferential adsorption of the 20 nm particles (assuming a kinetically driven process).

Experiments In order to investigate the system described above, silica coated silicon (SiO2/Si) substrates and colloidal AuNPs were functionalized with charge carrying molecules (thiolated DNA for negative charge, N,N,N-trimethyl-(11-mercaptoundecyl)ammonium chloride for positively charged AuNPs and (3-aminopropyl)triethoxysilane for the substrate). Negatively charged 30 nm AuNPs were then assembled onto the positively charged substrates to provide evenly distributed adsorption centers for positive particles as described by Zheng et al.1. Positively charged 20 and 50 nm AuNPs were mixed to form a bi-disperse colloid (satellite particle solution). For the size-selective adsorption step, dried substrates with the core assembly were immersed in the satellite particle solution for a fixed amount of time at a constant temperature.



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Assembly performance was assessed using SEM imaging (FEI Nova NanoSEM 430 or FEI Magellan 400 SEM) and UV-Vis spectroscopy (for glass substrates, Agilent Technologies Cary 60 UV-Vis spectrometer). As a measure of the effectiveness of the size-selective assembly process, we have defined a selectivity factor (SF):

9: =

(;/* :;=* )>?@AB+.C (;/* ∶;=* )EFGBAHFI

(5)

Where N is the number of particles, either captured on the substrate or initially present in solution. The selectivity factor is a measure of how much the 20 to 50 nm particle ratio has increased on the substrate when compared to the solution. A SF=1 means that the substrate is not selective, SF 1000 counts for each substrate). We thus concluded that no significant desorption of satellite particles occurs after adsorption to a core which indicates a diffusion controlled process rather than a thermodynamically controlled one. This also explains why the considerations presented in Figure 2 are more accurate for shorter incubation times where many unoccupied core particles are available for adsorption of satellite particles. Mixing ratio: The dependence of the selectivity on the initial mixing ratios of the two different sized satellite species in the bi-disperse colloid was investigated. The results shown here were achieved with an incubation time of 3 h at 20 ˚C. A summary of the results is shown in Figure 4, where the initial mixing ratios between 20 and 50 nm AuNPs of the different batches (#1 #4) were 19:1, 2:1, 1:1, and 1:2 (respectively).


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Figure 4: Effects of the mixing ratio in solution on the selectivity of the adsorption process. Top: SEM-based adsorption statistics showing the amount of adsorbed 50 nm particles on the surface (blue) when using different 20 to 50 nm particle mixing ratios in the initial assembly solution (orange: percentage of 50 nm particles in solution). The batch numbers are a reference for the different mixing ratios (batch 1: 19:1, batch 2: 2:1, batch 3: 1:1, batch 4: 1:2). Bottom: The selectivity factor for different mixing ratios calculated from the adsorption statistics according to equation (5). Due to the superior number of 20 nm particles in batch 1, it is not surprising to have mainly 20 nm particles adsorbing on the core particles. The number of the small satellites adsorbed on the surface did indeed increase to 98% as can be seen in Figure 4, batch 1, blue bar (indicating a 3-fold increase of the 20 nm particle concentration at the surface). This initial mixing ratio is approximately equal to an optical density ratio of 1:1. Therefore it was used (at a highly diluted absolute particle concentration) to evidence the preferential adsorption by comparing the UV-Vis spectra before and after the adsorption (see Supplementary Information, Figure S3). The AuNP colloids show a pronounced plasmon resonance peak in the UV-Vis absorbance spectrum, which is at a different wavelength for 20 and 50 nm S15 ACS Paragon Plus Environment


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AuNPs.27,28 The measured spectra for a bi-disperse colloid are therefore a sum of those two spectra. Depending on the mixing ratio, the peak position of this sum is closer to the absorption peak of the particle species with the higher optical density (~ particle concentration) in the mix. We could thereby detect a drop of 20 nm particle concentration in the solution during the adsorption experiments, confirming the trend observed by statistical evaluation of the SEM micrographs. When increasing the fraction of the 50 nm particles in the bi-disperse colloid further, we did also observe a significant increase in the selectivity factor to a maximum value of 28 which is reached with equal particle ratios in solution (batch #3). This result shows that the electrostatic self-assembly method is suitable to increase the fraction of the 20 nm AuNPs to over 96% when starting with a 1:1 mix of 20 and 50 nm AuNPs. An SEM image of the resulting adsorption pattern is depicted in the Supplementary Information Figure S7. Increasing the 50 nm particle fraction further to 67% leads to an increased fraction of adsorbed 50 nm particles of 23.1 % indicating that the selectivity of the adsorption process decreases significantly when increasing the 50 nm content further. These observed variations of the selectivity factor show strong dependence of the sizeselective adsorption process on the assembly conditions. While the process shows the predicted preference for the adsorption of smaller particles (which cannot be explained based on a simple diffusion model), the observed variations of the selectivity factor cannot be described by the considerations summarized in Figure 2 alone. As discussed earlier, the electrostatic interaction model describes the formation of a dimer, neglecting multi-particle effects (e.g. neighboring core particles, multimer formation or satellite particle interactions in the solution). A possible approach to further enhance the selectivity of the size-selective adsorption process at higher initial mixing ratios is to increase the zeta potential on the TMAC-AuNPS S16 ACS Paragon Plus Environment

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(Supplementary Information, Figure S6) which may require the use of different surfacecapping ligands. This increase is expected to increase the difference in the adsorption barriers of the different sized particles and therefore also for the adsorption yields for the different species. Conclusion In conclusion, we have studied the size selective adsorption process of bi-disperse satellite particles on core particles surface-confined to a charged substrate. We found the process to be kinetically controlled. The highest selectivity towards adsorption of small particles from a solution containing a bi-modal size distribution of Au nanoparticles was achieved for an initial (number) mixing ratio of 1:1. For this case, the small particles were adsorbed preferentially by number ratio (selectivity factor) of 28. Using DLVO theory we explain the driving force of the adsorption process as well as its size-selectivity. Interestingly, the selectivity factor depends strongly on the assembly conditions, which was not reflected by the initial considerations based on the electrostatic dimer forming process. Our calculations also show the effect of the zeta potential of the particles on the barrier height. They suggest that by tuning the zeta potential of otherwise identical particles, a sorting mechanism similar to the here presented one should be achievable. Possible applications of the size-selective adsorption process can be found in the fields of microfluidics and targeted sensing. Unlike other separation methods such as ultracentrifugation or filtration,9,29 the technique presented here does not require a full separation of the different species in the colloid. Additionally, no further preparation (like drop casting) is required for surface deposition for subsequent investigations (e.g. spectroscopy of captured molecules). Once captured, the satellite and core form asymmetric nano-dimers providing ideal conditions for a spectroscopy method like surface enhanced Raman spectroscopy, due to the strong plasmonic enhancement of the E-field in the inter-particle gap.30–33 S17 ACS Paragon Plus Environment


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ASSOCIATED CONTENT Supporting Information: More details on theoretical modelling of the assembly process; Temperature dependence of the selectivity; UV-Vis measurements; Schematic of desorption test; Schematic of experimental workflow; Particle size and zeta potential dependence of the adsorption barrier height; Exemplary SEM images used for statistical analysis. AUTHOR INFORMATION Corresponding Author *Udo Bach, [email protected] Author Contributions The manuscript was written through contributions of all authors. All authors have given approval to the final version of the manuscript. ACKNOWLEDGMENT This study has been supported by CSIRO through the OCE Science Leader program and the Australian research Council through an Australian Research Fellow grant (DP110105312) to UB and a Future Fellowship to DEG (FT140100514). This work was performed in part at the Melbourne Centre for Nanofabrication, the Victorian Node of the Australian National Fabrication Facility. A company established under the National Collaborative Research Infrastructure Strategy to provide nano- and micro-fabrication facilities for Australia’s researchers.


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The authors acknowledge use of facilities within the Monash Centre for Electron Microscopy. This research used equipment funded by Australian Research Council grant LE140100104. ABBREVIATIONS AuNP, Gold nanoparticle; SF, selectivity factor REFERENCES

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