CdS Nanocomposites

Feb 11, 2012 - Institute of Crystallography, Russian Academy of Sciences, 59 Leninsky Pr., 117333 Moscow, Russia. ‡ A.N.Nesmeyanov Institute of Orga...
0 downloads 12 Views 5MB Size
Article pubs.acs.org/JPCC

Unusual Structural Morphology of Dendrimer/CdS Nanocomposites Revealed by Synchrotron X-ray Scattering Eleonora V. Shtykova,† Nina V. Kuchkina,‡ Zinaida B. Shifrina,‡ Lyudmila M. Bronstein,*,§ and Dmitri I. Svergun*,∥ †

Institute of Crystallography, Russian Academy of Sciences, 59 Leninsky Pr., 117333 Moscow, Russia A.N.Nesmeyanov Institute of Organoelement Compounds, Russian Academy of Sciences, 28 Vavilov St., Moscow, 119991 Russia § Indiana University, Department of Chemistry, 800 East Kirkwood Avenue, Bloomington, Indiana 47405, United States ∥ EMBL, Hamburg Outstation, Notkestrasse 85, D-22603 Hamburg, Germany ‡

S Supporting Information *

ABSTRACT: Low-resolution structure of CdS nanoparticles (NPs) grown in the presence of the third-generation rigid polyphenylenepyridyl dendrimers (PPPDs) is analyzed by synchrotron small-angle X-ray scattering (SAXS) and transmission electron microscopy (TEM). The combination of rigidity of the PPPDs and a high local concentration of chelating nitrogens strongly interacting with growing CdS NPs yields anisometric particles instead of conventional spherical ones. The scattering data from the free PPPDs and from the composite CdS/PPPD NPs are interpreted in terms of 3-D models revealing a peculiar morphology of the nanocomposite whereby the PPPDs enclose the CdS NPs like a “flattened ball-in-hands”. The sizes of the CdS NPs found by SAXS are in good agreement with the TEM data. The presented approach to elucidate particle morphology should open the ways of detailed characterization of the modern composite materials from the SAXS data.

1. INTRODUCTION Recently structural studies of different types of dendrimers received great attention due to promising applications of both dendrimers and dendrimer-based nanocomposites.1−10 Their structure has been studied experimentally by various methods including small-angle scattering, both X-ray (SAXS) and neutron (SANS) along with theoretical works.11−14 SAXS and SANS are powerful techniques to obtain information on internal structure and overall shape of dendrimers, fractal dimension, distribution of chain ends, and radial density profiles.15−20 It should be noted, however, that most dendritic structures obtained are based on a priori conceptual models of spatial dendrimer organization making interpretation of the experimental scattering data model-dependent. The recently developed advanced SAXS data analysis methods allow one to build ab initio particle shapes at low resolution21 and construct models of multisubunit composites with rigid body modeling.22 The advanced approaches were successfully employed to analyze various polymer systems including those containing metal nanoparticles (NPs) and to build ab initio structural models of complex natural or artificial materials.23−28 © 2012 American Chemical Society

Because of unique structure and properties of dendrimers, they can serve as a promising template for NP formation and stabilization.7−9 Here SAXS is especially powerful because it allows one to determine sizes and shapes of various NPs, their distributions and locations in a nanocomposite,29−35 and structural information about internal organization of the entire system.23,24,36−39 Various SAXS and SANS studies were mostly devoted to poly(amido amine) (PAMAM) dendrimers, for example, employed as Au NP templates.40 A time-resolved in situ SAXS study of the association process of G1-NH2 PAMAM dendrimers interacting with Pd(OAc)2 and of the reduction of Pd ions into Pd atoms along with the formation of Pd NPs was reported.41 SAXS was used to quantify the interparticle spacing for Au NPs functionalized with a carboxylic acid monolayer and assembled with excess of PAMAM dendrimers,42 and to characterize gold, platinum, and copper NPs formed in dendrimers dispersed within polymer networks.43 Ab initio Received: November 15, 2011 Revised: February 2, 2012 Published: February 11, 2012 8069

dx.doi.org/10.1021/jp210998h | J. Phys. Chem. C 2012, 116, 8069−8078

The Journal of Physical Chemistry C

Article

denoted DNC-1 (DNC stands for dendrimer-based nanocomposites). DNC-2 was prepared under the similar conditions but with tetra-PPPDs, whereas DNC-3 was synthesized with tetra-PPPDs, the concentration of which was lower: 0.23 mmol/L. 2.2. Electron Microscopy Experiments. Electron-transparent specimens for TEM were prepared by placing a drop of diluted solution onto a carbon-coated Cu grid. Images were acquired at an accelerating voltage of 80 kV on a JEOL JEM1010 TEM. Images were processed with the Adobe Photoshop software package and analyzed with the ImageJ program to estimate NP diameters. Typically, 150 to 300 NPs were used for analysis. 2.3. SAXS Data Collection and Analysis. Synchrotron SAXS measurements were performed at the European Molecular Biology Laboratory (EMBL) on the storage ring DORIS III of the Deutsches Elektronen Synchrotron (DESY, Hamburg) on the X33 beamline50 equipped with a robotic sample changer51 and a PILATUS detector (DECTRIS, Switzerland). The scattering was recorded in the range of the momentum transfer 0.07 < s < 5.5 nm−1, where s = (4π sin θ)/ λ, 2θ is the scattering angle, and λ = 0.15 nm is the X-ray wavelength. The measurements were carried out in a vacuum cuvette with exposure times of 2 min to diminish the parasitic scattering. Both dendrimers, tri-PPPD and tetra-PPPD, and the CdS/PPPD nanocomposites DNC-1, DNC-2, and DNC-3 were studied in tetrahydrofuran. The experimental scattering profiles from all solutes were corrected for the background scattering from the appropriate solvent and processed using standard procedures.52 All of these samples were measured at the three different solute concentrations, 10.0, 5, and 2.5 mg/ mL, to exclude the concentration effect. The concentration dependence was absent for all solutes, and the highest concentration data were used for further analysis. The particle radii of gyration Rg were calculated using Guinier approximation Iexp(s) = I(0) exp(−s2Rg2/3), which is valid in the range (sRg) < 1.3.53 The distance distribution functions p(r) were computed using GNOM,54 which provided also independent estimates of the Rg values. The excluded (Porod) volume of the particles was computed using the equation55

SAXS analysis was recently employed to determine lowresolution structure of polycarbosilane dendrimers of the fourth, fifth, sixth, seventh, and eighth generations.44 The results showed good agreement with independent theoretical predictions of the dendrimer structures. Modern technologies allow one to fabricate various nanostructured objects with a rather low polydispersity. The methods of interpretation of the SAXS patterns originally developed for monodisperse solutions of biological macromolecules (e.g., proteins)45 are now also applicable to novel synthetic materials. We have already employed the ab initio and rigid body modeling to characterize the structure and clustering effects of magnetic NPs protected by phospholipids and copolymers.46,47 In most studies, to achieve more comprehensive characterization of the material and to avoid a possible ambiguity of interpretation, SAXS studies are complemented by other techniques such as transmission electron microscopy (TEM), dynamic light scattering (DLS), and so on. In the present study, using synchrotron SAXS and modern tools of SAXS data interpretation combined with TEM data, we establish unusual shapes of CdS NPs (also called quantum dots, QDs) formed in the presence of the third generation of polyphenylenepyridyl dendrimers (PPPDs) and the novel architecture of CdS/PPPD nanocomposites. The present work is, to our knowledge, the first attempt to visualize the 3-D morphology of composite particles by SAXS. Here the analysis of the scattering data from the individual dendrimers and from the nanocomposites allowed one not only to reveal the overall structure but also to depict the packing of the dendrimers around the QDs.

2. EXPERIMENTAL PART 2.1. Nanocomposite Syntheses. PPPDs based on 1,3,5triethynylbenzene (tri-PPPD) and tetrakis(4-ethynylphen-1yl)methane (tetra-PPPD) cores were synthesized according to a procedure described elsewhere.48,49 The CdS/PPPD nanocomposite syntheses were carried out in the following way. A three-necked round-bottomed flask (with elongated necks) equipped with a magnetic stir bar, a reflux condenser, and two septa, one of which contained an inserted thermometer, was charged with a mixture of 0.05 g (6.18 × 10−3 mmol) of tri-PPPD, 0.0028 g (2.2 ·10−2 mmol) of CdO, and 7.2 mL of benzyl ether yielding the 0.85 mmol/L PPPD concentration. Then, the flask was placed in a heating mantle attached to an output temperature controller and placed on a magnetic stirrer. The flask was degassed four times using “evacuation-filling with argon” cycles. After filling the reaction setup with argon, the reaction mixture was heated to 250 °C under vigorous stirring. Meanwhile, the sulfur solution was prepared as follows: the two-necked round-bottomed flask was charged with 0.007 g (0.22 mmol) of sulfur (10 mol of S per 1 mol of CdO) and 1 mL of benzyl ether (for the N:Cd:S 1:0.2:2 molar ratio). The mixture was degassed four times; then, the sulfur suspension was heated to 200 °C to obtain a clear solution. After that, a gastight syringe was purged with argon three times and the sulfur solution was quickly injected through the septum into a hot reaction solution. The reaction mixture was allowed to cool to 220 °C for the CdS NP growth taking place for 7 min. Then, the reaction mixture was cooled, filtered, and precipitated with hexane. The precipitate was isolated by filtration, dissolved in chloroform, and reprecipitated with hexane. The reprecipitation was repeated three times. The final product was dried in a vacuum oven overnight. This sample is

V = 2π 2I(0)/

∫0



s 2Iexp(s) ds

(1)

The low-resolution shapes of the PPPDs and CdS/PPPD nanocomposites were reconstructed ab initio from the scattering patterns using DAMMIN.21 This program represents the particle shape by an assembly of densely packed beads and employs simulated annealing (SA) to construct a compact interconnected model fitting the experimental data Iexp(s) minimizing the discrepancy 1 χ = N−1 2

⎡ Iexp(sj) − cIcalc(sj) ⎤2 ⎥ ∑⎢ σ(sj) ⎢ ⎥⎦ j ⎣

(2)

where N is the number of experimental points, c is a scaling factor, and Icalc(s) and σ(sj) are the calculated intensity and the experimental error at the momentum transfer sj, respectively. 2.4. Molecular Modeling of the SAXS Data. Molecular modeling of the CdS/PPPD nanocomposites was performed by the method of molecular tectonics implemented in SASREF.22 The program utilizes available models of subunits to build multisubunit complexes using a SA protocol, finding the 8070

dx.doi.org/10.1021/jp210998h | J. Phys. Chem. C 2012, 116, 8069−8078

The Journal of Physical Chemistry C

Article

nanocomposites. The scattering patterns collected from the five samples are displayed in Figure 3. Despite the absence of the concentration dependence for all of these samples (Section 2.3), a sharp upturn of the scattering profiles at the very small angles is observed. This upturn points to the coexistence of small objects (presumably, individual macromolecules) with rather large entities (permanent associates of macromolecules). For such systems, where the presence of the large associates is concentration-independent, it is possible to separate the contributions from the individual particles and those of the associates simply by the analysis of the appropriate portions of the experimental data. To estimate the shape and size of individual scattering objects, distance distribution functions p(r) were calculated using the program GNOM54 by excluding the initial portions of the scattering data (s < smin), bearing the information about the large supramolecular formations. To find the proper intervals to remove, we used the Guinier approximation to find out sufficiently long linear portions matching the condition sRg < 1.3,53 thus excluding the scattering from the associates. The portions of the scattering patterns for s > smin were used to evaluate the functions p(r), which, in turn, were employed to extrapolate the scattering data to zero angle and to restore the shapes of the individual particles by DAMMIN.21 3.1. Shapes and Sizes of Free Dendrimers. For both dendrimers, the cutoff at smin = 0.8 nm−1 was sufficient to remove the influence of the associates and to evaluate the characteristics of the individual macromolecules. The average radii of gyration Rg and the maximum sizes rmax of individual triPPPD and tetra-PPPD particles as estimated from the program GNOM are summarized in Table 1. These sizes correlate well with the data previously obtained by AFM for tetra-PPPD.48 The results of the shape restoration for tri-PPPD and tetraPPPD by DAMMIN are displayed in Figure 4. The ab initio restoration reveals irregular shapes, having a branched organization resembling to some extent the branched ball-and-stick models of the dendrimers (Figure 1). It is worth noting that the individual PPPD molecules are not completely rigid bodies despite the fact that they consist of only aromatic rings. They can obtain different configurations in solution due to certain mobility of their branches caused by twisting of the aromatic fragments around the C−C bonds. The mobility of the branches leads to the formation of a compact shape that is dynamically more stable.57 For higher generations, the structures become more compact, closer to spherical, whereas anisometry is more typical for low generations. The ab initio models depicted in Figure 4 can be considered to be a good representation of the average shapes of the third-generation dendrimers in solution, and, specifically, the observed anisometry is in agreement with the earlier evidence.44,58 3.2. Shapes and Sizes of Dendrimer Associates. The initial portions of the scattering profiles from the dendrimer solutions (up to s = smin ≈ 0.8 nm−1) provide information about the shape of the associates. For both tri-PPPD and tetra-PPPD, the distance distribution functions p(r) calculated using this part of the scattering data (insets of Figure 5) reveal the maximum size of ∼70 nm and the average cross-section of ∼25 nm. (The latter corresponds to the maximum of the p(r) function.) The shapes reconstructed by DAMMIN and shown in Figure 5 demonstrate chains of smaller bodies having the sizes coinciding with those of the individual dendrimer macromolecules, namely, 4.5 to 5.5 nm. (The shapes of the single

optimal positions and orientations of the subunits to fit the scattering patterns computed from the entire construct to the experimental scattering data. Here two components were used, the QD core and the dendrimer envelope. The latter was represented by several (two to four) individual dendrimer macromolecules with the shapes as determined by DAMMIN. The QD core was represented by an ellipsoid with appropriate dimensions (or by two ellipsoids for a dumbbell structure) filled with densely packed beads. The theoretical scattering patterns of these components required for the SASREF modeling were calculated by the program CRYSOL56 from the bead coordinates of the two components. Here the difference in the electron density between the QDs (1603 e/nm3) and PPPDs (354 e/nm3) was taken into account in the following way. Given the electron density of the tetrahydrofuran (297 e/nm3), the scattering contrasts of the two components are 1306 e/nm3 and 57 e/nm3 for the QD core and for the dendrimer shell, respectively. The models were therefore created in such a way that the effective bead density of the OD moiety was ∼20 times that of the dendrimer moiety. In SASREF runs, the ellipsoidal QDs were fixed at the origin, and a single PPPD macromolecule was allowed to move and rotate as rigid body around the QDs. Symmetry was applied to the PPPD to generate the configurations either with two (twofold symmetry P2), three (three-fold symmetry P3), or four (tetrahedral symmetry P222) dendrimers. In this way, the program was producing models with two, three, or four symmetrically related PPPD molecules while keeping the number of variable parameters to a minimum. Multiple SASREF runs with different symmetries and with variable sizes of the ellipsoidal cores were performed, and those producing the best fits to the experimental data were selected.

3. RESULTS AND DISCUSSION The schematic models of two dendrimers used in this work, triPPPD and tetra-PPPD, are presented in Figure 1.

Figure 1. Ball-and-stick models of tri-PPPD (a) and tetra-PPPD (b) obtained using MMFF in the Spartan software.

Figure 2 shows TEM images of three CdS/PPPD samples employed in this work. The diameters of CdS QDs are 4.3 nm with standard deviation of 20.0% for DNC-1, 3.9 nm with standard deviation of 15.4% for DNC-2, and 2.4 nm with standard deviation of 20.8% for DNC-3. Larger irregular gray spots indicated by blue arrows are extra PPPD molecules aggregated on the TEM grid.49 To characterize comprehensively the morphology of the CdS/PPPD nanocomposites, SAXS was employed assessing the solution properties of both the dendrimers alone and the 8071

dx.doi.org/10.1021/jp210998h | J. Phys. Chem. C 2012, 116, 8069−8078

The Journal of Physical Chemistry C

Article

Figure 2. TEM images of DNC-1 (a), DNC-2 (b), and DNC-3 (c). Regular circular dark spots are CdS NPs, whereas larger irregular gray spots (indicated by blue arrows) are the PPPD aggregates.

the dendrimer signal is present in the scattering patterns from the composites, and this has to be taken into account when trying to obtain the shapes of the CdS NPs from the SAXS data. For the DNC-1 and DNC-2 samples, the scattering profiles by the composites (curves 3 and 4 in Figure 3) are similar to the scattering from the related dendrimers (curves 1 and 2, respectively) at higher angles (starting from s ≈ 2 nm−1). It seems therefore plausible to subtract the scattering by the free dendrimers from the scattering by the composites to better approximate the scattering from the QDs. The subtracted patterns along with the computed p(r) functions are presented in Figure 6a,b, and the overall parameters are given in Table 1. The restored ab initio shapes of the QDs composites depicted in Figure 6a,b appear as slightly elongated dense bodies, with the maximum sizes of 6.0 (DNC-1) and 8.0 nm (DNC-2) and a cross-section of ∼2.5 nm. The two sizes exceed those obtained by TEM, most likely due to the residual influence of the dendrimers. Indeed, even after the subtraction of the free dendrimer scattering, the signal still contains the cross-term between the ODs and dendrimers in the nanocomposite, which leads to an overestimate of the apparent size of the QDs and to a distortion of the shapes. It is noteworthy that the sizes obtained by SAXS are consistent with the DLS data presented for CdS/PPPD nanocomposites in ref 49. As for the size of 2.5 nm, it is not showing in TEM images but is wellsupported by UV−vis data.49 For DNC-3 (curve 5, Figure 3), the scattering is strongly changed compared with the free dendrimer scattering (curve 2, Figure 3), and a meaningful subtraction of the latter was impossible. We have therefore evaluated the particle parameters and reconstructed the overall shape of this nanocomposite directly from the scattering data in the range starting from smin = 1 nm−1. The Rg and rmax of DNC-3 (Table 1) are the smallest among all nanocomposites, in agreement with the above TEM data. The ab initio particle shape in Figure 6c appears as an irregular body, somewhat more isometric compared with the shapes of DNC-1 and DNC-2 (Figure 6a,b). Irregular shapes were also reconstructed for DNC-1 and DNC-2, when the data without subtraction of the dendrimer scattering were used (Figure S1, the Supporting Information). These irregularities clearly stem from the contribution of the PPPD shell; however, as the DNC particles are rather inhomogeneous in density, approximating it with a homogeneous body has its limitations and more adequate modeling is required. Already the above low-resolution models of the PPPD molecules and of the nanocomposites allow one to speculate about the mechanisms of QD encapsulation by dendrimers.

Figure 3. Experimental SAXS curves from tri-PPPD (1), tetra-PPPD (2), DNC-1 (3), DNC-2 (4), and DNC-3 (5).

Table 1. Characteristic Sizes of the PPPDs and CdS/PPPD Nanocomposites individual particles specimen

Rg, nm

tri-PPPD tetra-PPPD DNC-1 DNC-2 DNC-3

1.7 ± 0.1 2.0 ± 0.1 2.1 ± 0.1 2.6 ± 0.1 1.65 ± 0.05

rmax, nm 5.0 6.0 6.0 8.0 4.5

± ± ± ± ±

0.5 0.5 0.5 0.8 0.3

dendrimers are also displayed for comparison.) The dendrimer associates appear to contain on average about 10 individual macromolecules. Volume fraction of the monomers and associates in each sample was quantitatively estimated using the scattering intensity at zero scattering angle I0 as described in the Supporting Information, and the results are presented in Table S1 (Supporting Information). Presence of the associates in solution does not exceed several percent (their number does not go beyond 0.01%). Of course, the associates do not have fixed configuration in solution, and the models presented in Figure 5 are just average representations of their shape. Still, the chain-like appearance of the associates indicates that they consist of interacting dendrimer molecules retaining their individual shapes and sizes. 3.3. Shapes and Sizes of CdS/PPPD Nanocomposites. Similarly to TEM where the dendrimers surrounding QDs are largely invisible (Figure 2), X-rays are also mainly scattered by the QD component because of the much higher density of CdS compared with that of the PPPD: 4.8 versus 1.06 g/cm3. Still, 8072

dx.doi.org/10.1021/jp210998h | J. Phys. Chem. C 2012, 116, 8069−8078

The Journal of Physical Chemistry C

Article

Figure 4. Shape restoration of the individual PPPD molecules in solution for tri-PPPD (a) and tetra-PPPD (b): experimental curves (1); scattering from the DAMMIN models (2); and the processed scattering patterns extrapolated to zero angle (3). Insets: distance distribution functions calculated by GNOM from the experimental SAXS curves (lower left) and ab initio bead models reconstructed from the scattering data (upper right).

Figure 5. Shape restoration of the tri-PPPD (a) and tetra-PPPD (b) associates in solution: experimental curves (1); scattering from the DAMMIN models (2); and the processed curves extrapolated to zero angle (3). Insets: distance distribution functions calculated by GNOM from the experimental SAXS curves (lower left) and ab initio bead models reconstructed from the scattering data (upper right; the shape reconstructions of the single dendrimer are encircled).

Figure 6. Shape restoration for the CdS/PPPD nanocomposites DNC-1 (a), DNC-2 (b), and DNC-3 (c): experimental curves (1); scatterings from the DAMMIN model (2); and the processed curves extrapolated to zero angle (3). Insets: distance distribution functions calculated by GNOM from the experimental SAXS curves (lower left) and ab initio bead models reconstructed from the scattering data (upper right).

The most natural hypothesis, that a single CdS NP is encapsulated by a single dendrimer forming a dendrimer encapsulated nanoparticle (DEN),8 clearly does not hold as the

NP sizes are far too large for that. The second common scenario is the formation of a dendrimer-stabilized nanoparticle composite (DSN),8 when a NP is surrounded by dendrimers as 8073

dx.doi.org/10.1021/jp210998h | J. Phys. Chem. C 2012, 116, 8069−8078

The Journal of Physical Chemistry C

Article

latter approach permits one to build models of composite particles by rigid body movements and rotations of their individual components. As described in Section 2.4, the shapes of the PPPDs were taken for the modeling as obtained ab initio (Figure 4); for QDs, oblate ellipsoids of rotation having the sizes and anisometry compatible with the ab initio QD models were tried. Importantly, the numbers of beads in the models representing the QDs were selected to take into account adequately the difference in contrast between the QDs and PPPDs. For each of the composites, multiple SASREF runs were performed, allowing for different number of PPPDs (from two to four) and for the different shapes of the QD cores. For the DNC-1 composite, where tri-PPPD was employed for the stabilization, ellipsoid with half axes 1.7 × 2.0 × 2.3 nm was tried first, having the average sizes compatible with those reported by TEM (taking into account the QD polydispersity). The rigid body modeling by SASREF yielded a reasonable fit to the experimental data from DNC-1 with discrepancy χ = 3.5 (Figure 7, curve 2) by the model in Figure 7, panel 2a, displaying the four PPPDs surrounding the QD core and covering its surface. To find a physically sensible model better agreeing with the experimental data, a systematic search of possible ellipsoidal cores was performed. The models of the cores as ellipsoids of revolution (with half axes a = b and c) were generated and for each core SASREF was run with different number of dendrimer molecules. Figure 7, panel 3, displays the surface plot of the goodness-of-fit for the DNC-1 models with four dendrimers per QD and the ellipsoidal parameters of the cores 10 ≤ a ≤ 35 nm, 10 ≤ c ≤ 35 nm with a 2.5 nm increment (121 model runs in total). The plot reveals a clear minimum in a well-defined range of oblate ellipsoids (a > c), whereas prolate and spherical QD shapes yield systematically worse fits. (For comparison, the best fit using a spherical QD is presented in Figure S2 of the Supporting Information.) This result correlates well with the TEM images, as it is known that oblate particles do tend to display only spherical projections due to surface tension forces when a drop of solution containing particles dries on the grid.59 An ellipsoidal QD core with half axes 2.5 × 2.5 × 1.5 nm (agreeing well with the ab initio model in Figure 6a) yielded the best fit with discrepancy χ = 1.6 (Figure 7, curve 3), displaying the arrangement of the four PPPDs (Figure 7, panel 2b) very similar to that shown in Figure 7, panel 2a.

conventional surfactants, but then the DSNs would have been much larger than those observed in the experiments with PPPDs.49 The number of the PPPD macromolecules per QD can be roughly estimated from the Porod volumes of the ab initio models. The nanocomposites DNC-1, DNC-2, and DNC-3 have the volumes of about 70 ± 7, 90 ± 8, and 40 ± 4 nm3, respectively, whereas the volumes of the tri- and tetraPPPD are about 10 ± 1 and 15 ± 2 nm3, respectively. Accounting for the volumes of the QD cores, about two to four PPPD macromolecules are expected to be recruited by a single QD. The encapsulation of the QDs could metaphorically be represented as a flattened ball (CdS NP) held by hands (dendrimers) in a way that the ball surface is covered (i.e., not exposed to the solvent). We would call this a “flattened ball-inhands” morphology (Scheme 1). This scenario is also Scheme 1. Hypothetical Morphology of CdS/PPPD Nanocomposites

consistent with the tri- and tetra-PPPD structures where the peripheral groups are phenyl rings, which are unable to interact with the CdS NP surface, whereas the pyridine moieties, which can adsorb on the NP surface, are located in the PPPD interior. 3.4. Modeling of the CdS/PPPD Nanocomposites by Molecular Tectonics. Although the above ab initio shape analysis yielded valuable and consistent low-resolution information about the size and organization of the of CdS/ PPPD nanocomposites, the procedure had limitations. In the shape reconstruction, one assumes that the particle is uniform, which is obviously not the case here as CdS has much higher contrast compared with that of PPPD (Section 2.4). To construct more adequate and detailed models, we made use of the available approximate shapes of the dendrimers and of the QDs and employed the method of molecular tectonics.22 The

Figure 7. Rigid body modeling of the DNC-1 composite. Panel 1: experimental scattering curve (1); scattering curve from the model with the core of 1.7 × 2.0 × 2.3 nm displayed in Panel 2 (a) (2); and scattering curve from the model with the core of 2.5 × 2.5 × 1.5 nm displayed in Panel 2 (b) (3). Panel 2: SASREF reconstruction (blue: QD core, other colors: tri-PPPD molecules). Panel 3: a surface plot of the discrepancy versus the parameters of the ellipsoidal QD cores with half axes a, b, and c. The values are reflected in the color coding. A distinct minimum is observed in the area of oblate particles around a = 2.5 nm, c = 1.5 nm. 8074

dx.doi.org/10.1021/jp210998h | J. Phys. Chem. C 2012, 116, 8069−8078

The Journal of Physical Chemistry C

Article

Figure 8. Rigid body modeling of the DNC-2 composite. Panel 1: experimental scattering curve (1) and scattering curve from the model with a core of 1.5 × 3.0 × 3.0 nm (2). Panel 2: rigid body reconstruction (color coding as in Figure 7). Panel 3: a surface plot of the discrepancy versus the parameters of the ellipsoidal QD cores with half axes a, b, and c. The values are reflected in the color coding. A distinct minimum is observed in the area of oblate particles around a = 3.0 nm, c = 1.5 nm.

Figure 9. Rigid body modeling of the DNC-3 composite. Panel 1: experimental scattering curve (1) and scattering curve from the model with a core of 1.3 × 1.9 × 1.9 nm (2), displayed in Panel 2 (color coding as in Figure 7). Panel 3: a surface plot of the discrepancy versus the parameters of the ellipsoidal QD cores with half axes a, b, and c. The values are reflected in the color coding.

discrepancy χ = 1.7 was obtained when using the oblate ellipsoidal core with half axes 1.3 × 1.9 × 1.9 nm. (The model and the fit are displayed in Figure 9.) In this modeling, the symmetry restrictions had to be abandoned to better fit the experimental data. Still, the fit in Figure 9, despite the nominally good discrepancy, displays noticeable systematic deviations from the experiment. Also, the surface plot (Figure 9, panel 3) appears more shallow than those for DNC-1 and DNC-2 but still favors the oblate QD shapes (the best fit using a spherical QD is presented in Figure S2, the Supporting Information). Recalling also that the scattering pattern changes significantly upon formation of the nanocomposites compared with the scattering from the free dendrimer (cf. Figure 3, curves 2 and 5), it is conceivable that for this sample the dendrimers may noticeably change the conformation during the encapsulation of the QDs. Overall, the results of the rigid body modeling fully support the hypothesis of the “flattened ball-in-hands” morphology of the CdS/PPPD nanocomposites. It should be noted here that DNC-1 and DNC-2 are not obliged to be symmetric, and the

The spatial organization of the DNC-2 composite was modeled in a similar way using the restored shape of the tetraPPPD macromolecule. The best fit with discrepancy χ = 1.5 (Figure 8, curve 2) was obtained when using an oblate ellipsoid with the sizes 3.0 × 3.0 × 1.5 nm as a core. (The model is presented in Figure 8, right panel.) The surface plot of the goodness-of-fit for DNC-2 (Figure 8, panel 3) displays a minimum in the defined range of oblate shapes, similar to DNC-1. (The best fit using a spherical QD is presented in Figure S2 of the Supporting Information.) The QD core yielding the nominally best fit for DNC-2 has a slightly larger axis than that for DNC-1 (3.0 vs 2.5 nm), but the fit obtained for DNC-2 with a = 2.5 nm is nearly the same with χ = 1.55. Therefore the QDs formed for DNC-1 and DNC-2 have practically the same size, which correlates well with the TEM results in Figure 2 (accounting for the 15−20% size variations observed by TEM). DNC-3 has the smallest size, and, as might be expected, the better agreement to the experimental data was found for two and not four dendrimers per the QD core. The best fit with 8075

dx.doi.org/10.1021/jp210998h | J. Phys. Chem. C 2012, 116, 8069−8078

The Journal of Physical Chemistry C

Article

Figure 10. Distance distribution functions p(r) for the CdS/PPPD associates DNC-1 (1), DNC-2 (2), and DNC-3 (3) (left) and their shapes (right) denoted as (a), (b) and (c), respectively. Note the shapes (a), (b), and (c) are not presented in their actual sizes.

were seen, in good agreement with sizes obtained from the SAXS measurements. It was also demonstrated that besides the individual CdS/PPPD composite particles, large associates are formed in solution consisting of several interlinked CdS/PPPD particles. In contrast with the PPPD associates, which are long chains, the CdS/PPPD associates are much shorter (four to five units) and practically linear with a rigid conformation. The fraction of associates expressed in the total number of particles does not exceed 1 number percent. To the best of our knowledge, the present work is the first attempt to visualize the 3-D morphology of composite particles by SAXS. These particles have a limited polydispersity. (Indeed, the NPs display a moderate size polydispersity according to the TEM data, whereas the PPPDs may display some conformational polydispersity.) The SAXS reconstruction methods designed for monodisperse systems can be applied to moderately polydisperse objects if the structural variability does not exceed the resolution of the models. As the resolution of the SAXS models is about 1.5 to 2 nm, this condition is definitely fulfilled. The SAXS models are compatible with the evidence from the other methods, including TEM, but go significantly beyond these methods. Therefore, the SAXS allows one to model the dendrimer moiety of the DNCs, which is not seen in the TEM due to the low contrast of the dendrimers compared with the QDs. Ambiguities in the 3-D interpretation of the 1-D scattering data must always be remembered, and SAXS is always best used in multipronged studies to crossvalidate the results. We strongly believe that the presented results, apart from revealing the peculiar structural morphology of the CdS/PPPD nanocomposites, will play a catalyzing role in yet more effective use of SAXS in the characterization of the modern composite materials.

symmetry was imposed here only to reduce the number of variable parameters. We did perform calculations with several dendrimers attached to a QD without symmetry restrictions, and the models were of course asymmetric but still with the overall organization of the composites similar to the symmetric ones. Remarkably, satisfactory fits to the experimental data could be obtained only in rather narrow ranges of shapes and sizes of the modeling bodies. As a matter of fact, no good fits were found when using dozens of different tentative bodies of various shapes or sizes, indicating that the scattering data constrain well the allowed organization of the NPs. 3.5. Shapes and Sizes of Associates of the CdS/PPPD Nanocomposites. The distance distribution functions p(r) for the DNC-1, DNC-2, and DNC-3 specimens calculated at the very small angles (below smin = 1 nm−1), that is, in the regions of scattering from the associates, show the maximum particle sizes about 60−65 nm (Figure 10a), which are smaller than those for the PPPD associates of parent PPPDs (Figure 5) with the cross-section of ∼7 nm for DNC-1 and DNC-2 specimens and ∼12 nm for DNC-3. The shapes of these associates restored by DAMMIN (Figure 10b) display interconnected particles with the sizes corresponding to those of individual CdS/PPPD NPs in solution. In contrast with the PPPD associates, which are long, branched chains, the CdS/PPPD associates are much shorter (four to five units) and nearly linear. We believe that the presence of the CdS QD in the composite particle makes their connection less probable because dendrimers are adsorbed on the NP surface, but when the connection occurs, the whole structure is more rigid because the movements of the CdS/PPPD particles are more restricted. It is worth noting that similar to the case of free PPPD the association process yields chains of wellseparated CdS/PPPD particles, which allows us to separate the scattering from the individual nanocomposites and from the associates.



4. CONCLUSIONS The detailed study of the CdS/PPPD nanocomposites using SAXS revealed that the NPs are not spherical but can be presented as flattened balls surrounded by densely attached dendrimers, independently of the NP sizes or dendrimer architectures. This unusual shape is consistent with the optical measurements,49 where several characteristic sizes for the CdS NPs were observed, and with TEM, where spherical projections

ASSOCIATED CONTENT

S Supporting Information *

Contents of clusters in the samples, irregular shapes reconstructed for DNC-1 and DNC-2 without subtraction of dendrimer scattering and best fits for spherical QD shapes. This material is available free of charge via the Internet at http:// pubs.acs.org. 8076

dx.doi.org/10.1021/jp210998h | J. Phys. Chem. C 2012, 116, 8069−8078

The Journal of Physical Chemistry C



Article

(28) Sonaje, K.; Chen, Y.-J.; Chen, H.-L.; Wey, S.-P.; Juang, J.-H.; Nguyen, H.-N.; Hsu, C.-W.; Lin, K.-J.; Sung, H.-W. Biomaterials 2010, 31, 3384. (29) Svergun, D. I.; Shtykova, E. V.; Kozin, M. B.; Volkov, V. V.; Dembo, A. T.; Shtykova, E. V. J.; Bronstein, L. M.; Platonova, O. A.; Yakunin, A. N.; Valetsky, P. M.; Khokhlov, A. R. J. Phys. Chem. B 2000, 104, 5242. (30) Svergun, D. I.; Kozin, M. B.; Konarev, P. V.; Shtykova, E. V.; Volkov, V. V.; Chernyshov, D. M.; Valetsky, P. M.; Bronstein, L. M. Chem. Mater. 2000, 12, 3552. (31) Bronstein, L. M.; Linton, C.; Karlinsey, R.; Ashcraft, E.; Stein, B.; Svergun, D. I.; Kozin, M.; Khotina, I. A.; Spontak, R. J.; WernerZwanziger, U.; Zwanziger, J. W. Langmuir 2003, 19, 7071. (32) Bonini, M.; Fratini, E.; Baglioni, P. Mater. Sci. Eng., C 2007, 27, 1377. (33) Ramaye, Y.; Neveuand, S.; Cabuil, V. J. Magn. Magn. Mater. 2005, 289, 28. (34) Ramallo-López, J. M.; Giovanett, L.; Craievich, A. F.; Vicentin, F. C.; Marín-Almazo, M.; José-Yacaman, M.; Requejo, F. G. Phys. B 2007, 389, 150. (35) Thünemann, A. F.; Rolf, S.; Knappe, P.; Weidner, S. Anal. Chem. 2009, 81, 296. (36) Sakamoto, N.; Harada, M.; Hashimoto, T. Macromolecules 2006, 39, 1116. (37) Sen, D.; Spalla, O.; Taché, O.; Haltebourg, P. Langmuir 2007, 23, 4296. (38) Riello, P.; Mattiazzi, M.; Pedersen, J. S.; Benedetti, A. Langmuir 2008, 24, 5225. (39) Shtykova, E. V.; Svergun, D. I.; Chernyshov, D. M.; Khotina, I. A.; Valetsky, P. M.; Spontak, R. J.; Bronstein, L. M. J. Phys. Chem. B 2004, 108, 6175. (40) Groehn, F.; Bauer, B. J.; Akpalu, Y. A.; Jackson, C. L.; Amis, E. J. Macromolecules 2000, 33, 6042. (41) Tanaka, H.; Koizumi, S.; Hashimoto, T.; Itoh, H.; Satoh, M.; Naka, K.; Chujo, Y. Macromolecules 2007, 40, 4327. (42) Srivastava, S.; Frankamp, B. L.; Rotello, V. M. Chem. Mater. 2005, 17, 487. (43) Groehn, F.; Kim, G.; Bauer, A. J.; Amis, E. J. Macromolecules 2001, 34, 2179. (44) Ozerin, A. N.; Svergun, D. I.; Volkov, V. V.; Kuklin, A. I.; Gordelyi, V. I.; Islamov, A. K.; Ozerina, L. A.; Zavorotnyuk, D. S. J. Appl. Crystallogr. 2005, 38, 996. (45) Mertens, H. D.; Svergun, D. I. J. Struct. Biol. 2010, 172, 128. (46) Shtykova, E. V.; Huang, X.; Remmes, N.; Baxter, D.; Stein, B. D.; Dragnea, B.; Svergun, D. I.; Bronstein, L. M. J. Phys. Chem. C 2007, 111, 18078. (47) Shtykova, E. V.; Gao, X.; Huang, X.; Dyke, J. C.; Schmucker, A. L.; Remmes, N.; Baxter, D. V.; Stein, B.; Dragnea, B.; Konarev, P. V.; Svergun, D. I.; Bronstein, L. M. J. Phys. Chem. C 2008, 112, 16809. (48) Shifrina, Z. B.; Rajadurai, M. S.; Firsova, N. V.; Bronstein, L. M.; Huang, X.; Rusanov, A. L.; Muellen, K. Macromolecules 2005, 38, 9920. (49) Kuchkina, N. V.; Morgan, D. E.; Stein, B. D.; Puntus, L. N.; Sergeev, A. M.; Peregudov, A. S.; Bronstein, L. M.; Shifrina, Z. B. Nanoscale 2012, accepted; DOI: 10.1039/C2NR12086K. (50) Roessle, M. W.; Klaering, R.; Ristau, U.; Robrahn, B.; Jahn, D.; Gehrmann, T.; Konarev, P.; Round, A.; Fiedler, S.; Hermes, C.; Svergun, D. J. Appl. Crystallogr. 2007, 40, s190. (51) Round, A. R.; Franke, D.; Moritz, S.; Huchler, R.; Fritsche, M.; Malthan, D.; Klaering, R.; Svergun, D. I.; Roessle, M. W. J. Appl. Crystallogr. 2008, 41, 913. (52) Konarev, P. V.; Volkov, V. V.; Sokolova, A. V.; Koch, M. H. J.; Svergun, D. I. J. Appl. Crystallogr. 2003, 36, 1277. (53) Feigin, L. A.; Svergun, D. I. Structure Analysis by Small-Angle Xray and Neutron Scattering; Plenum Press: New York, 1987. (54) Svergun, D. I. J. Appl. Crystallogr. 1992, 25, 495. (55) Porod, G. In Small-Angle X-ray Scattering; Glatter, O., Kratky, O., Eds.; Academic Press: London, 1982; p 17. (56) Svergun, D. I.; Barberato, C.; Koch, M. H. J. J. Appl. Crystallogr. 1995, 28, 768.

AUTHOR INFORMATION

Corresponding Author

*E-mail: [email protected] (L.M.B.), [email protected] (D.I.S.). Notes

The authors declare no competing financial interest.



ACKNOWLEDGMENTS This work has been partially supported by the IU FRSP grant. N.K., L.B., and Z.S. thank the Federal Program “Scientists and Educators of Innovative Russia” 2009-20013, contract no. 14.740.11.0380, and the RFBR grants 11-03-00064 and 10-0301114-a. D.S. acknowledges support from the BMBF Research Grant SYNC-LIFE (contract number 05K10YEA).



REFERENCES

(1) Tomalia, D. A.; Dvornic, P. R. Nature 1994, 617. (2) Uhrich, K. Trends Polym. Sci. 1997, 5, 388. (3) Bielinska, A.; Kukowska-Latallo, J. F.; Johnson, J.; Tomalia, D. A.; Baker, J., J. R. Nucleic Acids Res. 1996, 24, 2176. (4) Shah, D. S.; Sakthivel, T.; Toth, I.; Florence, A. T.; Wilderspin, A. F. Int. J. Pharm. 2000, 208, 41. (5) Hughes, J. A.; Aronsohn, I. A.; Avrutskaya, A. V.; Juliano, R. L. Pharm. Res. 1996, 13, 404. (6) Yoo, H.; Sazani, P.; Juliano, R. L. Pharm. Res. 1999, 16, 1799. (7) Bronstein, L. M.; Shifrina, Z. B. Chem. Rev. 2011, 111, 5301. (8) Astruc, D.; Boisselier, E.; Ornelas, C. Chem. Rev. 2010, 110, 1857. (9) Crooks, R. M.; Zhao, M. Q.; Sun, L.; Chechik, V.; Yeung, L. K. Acc. Chem. Res. 2001, 34, 181. (10) Chandler, B. D.; Gilbertson, J. D. Top. Organomet. Chem. 2006, 20, 97. (11) deGennes, P. G.; Hervet, H. J. Phys., Lett. 1983, 44, 351. (12) Mansfield, M. L.; Klushin, L. I. Macromolecules 1993, 26, 4262. (13) Chen, Z. Y.; Cui, S.-M. Macromolecules 1996, 29, 7943. (14) Grest, G. S.; Kremer, K.; Witten, T. A. Macromolecules 1987, 20, 1376. (15) Groehn, F.; Bauer, B. J.; Amis, E. J. Macromolecules 2001, 34, 6701. (16) Jana, C.; Jayamurugan, G.; Ganapathy, R.; Maiti, P. K.; Jayaraman, N.; Sood, A. K. J. Chem. Phys. 2006, 124, 204719. (17) Rathgeber, S.; Monkenbusch, M.; Kreitschmann, M.; Urban, V.; Brulet, A. J. Chem. Phys. 2002, 117, 4047. (18) Baars, M. W. P. L; Kleppinger, R.; Koch, M. H. J.; Yeu, S. L.; Meijer, E. W. Angew. Chem., Int. Ed. 2000, 39, 1285. (19) Tan, N. C. B.; Balogh, L.; Trevino, S. F.; Tomalia, D. A.; Lin, J. S. Polymer 1999, 40, 2537. (20) Jin, S.; Jin, K. S.; Yoon, J.; Heo, K.; Kim, J.; Kim, K.-W.; Ree, M.; Higashihara, T.; Watanabe, T.; Hirao, A. Macromol. Res. 2008, 16, 686. (21) Svergun, D. I. Biophys. J. 1999, 76, 2879. (22) Petoukhov, M. V.; Svergun, D. I. Biophys. J. 2005, 89, 1237. (23) Bronstein, L. M.; Sidorov, S. N.; Zhirov, V.; Zhirov, D.; Kabachii, Y. A.; Kochev, S. Y.; Valetsky, P. M.; Stein, B.; Kiseleva, O. I.; Polyakov, S. N.; Shtykova, E. V.; Nikulina, E. V.; Svergun, D. I.; Khokhlov, A. R. J. Phys. Chem. B 2005, 109, 18786. (24) Bronstein, L. M.; Dixit, S.; Tomaszewski, J.; Stein, B.; Svergun, D. I.; Konarev, P. V.; Shtykova, E.; Werner-Zwanziger, U.; Dragnea, B. Chem. Mater. 2006, 18, 2418. (25) Shtykova, E. V.; Shtykova, E. V., Jr.; Volkov, V. V.; Konarev, P. V.; Dembo., A. T.; Makhaeva, E. E.; Ronova, I. A.; Khokhlov, A. R.; Reynaers, H.; Svergun, D. I. J. Appl. Crystallogr. 2003, 36, 669. (26) Fagan, R. P.; Albesa-Jové, D. Mol. Microbiol. 2009, 1308−1322, 1308. (27) Mott, D.; Yin, J.; Engelhard, M.; Loukrakpam, R.; Chang, P.; Miller, G.; Bae, I.-T.; Chandra Das, N.; Wang, C.; Luo, J.; Zhong, C.-J. Chem. Mater. 2010, 22, 261. 8077

dx.doi.org/10.1021/jp210998h | J. Phys. Chem. C 2012, 116, 8069−8078

The Journal of Physical Chemistry C

Article

(57) Brocorens, P.; Zojer, E.; Cornil, J.; Shuai, Z.; Leising, G.; Mullen, K.; Bredas, J. L. Synth. Met. 1999, 100, 141. (58) Petkov, V.; Parvanov, V.; Tomalia, D.; Swanson, D.; Bergstrom, D.; Vogt, T. Solid State Commun. 2005, 134, 671. (59) Sun, Y.; Frenkel, A. I.; Isseroff, R.; Shonbrun, C.; Forman, M.; Shin, K.; Koga, T.; White, H.; Zhang, L.; Zhu, Y.; Rafailovich, M. H.; Sokolov, J. C. Langmuir 2006, 22, 807.

8078

dx.doi.org/10.1021/jp210998h | J. Phys. Chem. C 2012, 116, 8069−8078