J. Phys. Chem. C 2007, 111, 16717-16723
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Ligand Dynamics in Spin-Labeled Au Nanoparticles Petre Ionita,† Joanna Wolowska,‡ Victor Chechik,*,† and Agneta Caragheorgheopol*,§ Department of Chemistry, UniVersity of York, Heslington, York YO10 5DD, United Kingdom, EPR National SerVice, Department of Chemistry, UniVersity of Manchester, Oxford Road, Manchester M13 9PL, United Kingdom, and Institute of Physical Chemistry “Ilie Murgulescu”, Spl. Independentei 202, 060021 Bucharest, Romania ReceiVed: May 12, 2007; In Final Form: August 19, 2007
Variable temperature electron paramagnetic resonance (EPR) spectra of spin-labeled Au nanoparticles in toluene solution were recorded at X-, Q- and W-bands. The chain length of the nitroxide-based spin-labeled ligand and the surrounding alkanethiol ligands was systematically varied. The spectra were analyzed using the NLSL program (Budil, D. E.; Lee, S.; Saxena, S.; Freed, J. H. J. Magn. Reson., Ser. A 1996, 120, 155) which simulates slow motion spectra using the stochastic Liouville approach. The simulation results show that the rotational diffusion parameters for particles (∼2.6 nm Au core diameter) are dominated by the local motion of the ligand. The length of the spin label has the biggest effect on the nitroxide dynamics followed by the chain length of the surrounding ligands. The results are consistent with the loose packing of ligands on the nanoparticle surface. The packing density of ligands further decreases with the increasing distance from the Au surface. The Arrhenius analysis of the dynamic parameters obtained at different temperatures showed an activation energy for rotational diffusion of ∼2.5-4 kcal/mol, regardless of the nature of the spin label and the surrounding ligand. This result is also consistent with the very open, disordered structure of the organic ligands on the nanoparticle surface in toluene.
Introduction Since Brust et al. reported a simple way to stabilize gold nanoparticles by the adsorption of organic thiols,1 these unusual materials have attracted much interest. Easy to prepare and handle, these supermolecules behave like common organic compounds. On the other hand, the nanoscale metal core is characterized by physical properties which are intermediate between small metal complexes and bulk metals. The organic shell in the nanoparticles exposes a 2D monolayer wrapped in a 3D shape,2 which is often exploited for probing nanoscale physical properties not accessible in planar monolayers.2,3 New approaches in chemistry also emerged by using the unique spatial organization of functionalities offered by these particles.4-6 Ligand exchange in solution is a simple way to introduce functionalized ligands in the organic shell. Multifunctional nanoparticles, possessing several different functionalities on the same particle, can be used as sensors or catalysts (sui generis nanoreactors which mimic enzyme functioning). Homofunctionalized nanoparticles with high coverage show unique properties due to the high local concentration of the ligands. For example, nanoparticles functionalized with redox-active substituents behave as freely diffusing nanoelectrodes.4,6 Today, the applications of monolayer-protected Au nanoparticles span the entire range of natural sciences from physics and chemistry to materials science, biology and medicine. Many interesting properties of Au nanoparticles depend on the functionalities and the morphology of the ligand monolayer. Several groups have made important efforts to characterize the * To whom correspondence should be addressed. E-mail: vc4@ york.ac.uk (V.C.);
[email protected] (A.C.). † University of York. ‡ University of Manchester. § Institute of Physical Chemistry, Bucharest.
packing and dynamics of the alkanethiols on Au nanoparticles using differential scanning calorimetry (DSC), Fourier transform infrared (FTIR) spectroscopy, and 13C and 2H NMR spectroscopies.7,8 The results basically showed that, in the solid state, the alkane chains of the long alkanethiol ligands on the nanoparticle surface are well-ordered in predominantly all-trans conformations at low temperatures, but undergo a phase transition at ∼30-60 °C. This transformation occurs via rapid trans-gauche bond isomerization and axial chain rotation and results in the conformational changes from all-trans to a disordered configuration of alkane chains. Badia et al. reported that ligands with weak H-bonding groups such as hydroxyl groups pack in a similar way as alkanethiols, but strong H-bonding groups (e.g., COOH) help to induce conformational order in chains which are too short to order via van der Waals interactions.9 Stellaci et al. studied homo- and heterofunctionalized Au nanoparticles by scanning tunneling microscopy and were able to visualize individual ligands on the Au surface. Their results did not support the model of tight packing of ligands on either faceted or spherical gold cores; instead, they observed that the ligands have the tendency to splay and find more space for their head-groups relative to sulfur, with the effect being stronger the smaller the diameter.10 However, these results also refer to dry particles in the solid state. Murray and co-workers explored the solution reactivity of terminal functionalities on C3, C8, and C12 ligands surrounded by a C12-alkyl monolayer.4 They found that the reactivity in SN2 substitution is affected by the steric bulk of the incoming reagent and the relative chain length of terminally substituted bromoalkanethiolate and surrounding chains. However, unlike self-assembled monolayers on planar surfaces, the functionalized ligands on Au nanoparticles show SN2 reactivity comparable
10.1021/jp073633+ CCC: $37.00 © 2007 American Chemical Society Published on Web 10/18/2007
16718 J. Phys. Chem. C, Vol. 111, No. 45, 2007 to that of the free ligand in solution. Solution IR spectroscopy demonstrated that, in nonpolar solvents, the alkanethiolate ligands on Au nanoparticles show the level of disorder approaching that of liquid alkanes. These results support a model of decreasing chain packing density as the distance from gold increases, a model which simply results from the curvature of the small gold particles. The packing and dynamics of ligands have an important influence on nanoparticle solubility as well as on the kinetics and mechanisms of reactions of functional groups in nanoparticles. Access of reagents, for instance, could be decisively influenced by ligand packing. Ligand exchange kinetics suggested that a small number of ligands presumably located on defect or special (e.g., vertex, edge) sites are more easily exchanged than the ligands on the terrace sites.11,12 We have recently showed that electron paramagnetic resonance (EPR) of spin-labeled nanoparticles can provide direct data on the ligand dynamics. Our previous qualitative work showed that the chain length of the spin label and the surrounding ligand have a strong influence on the EPR line shapes at room temperature.13 The aim of this contribution is to systematically characterize the dynamics of ligands attached to gold nanoparticles in solution from simulations of EPR spectra of spin-labeled ligands on Au in the slow motional domain. To achieve this goal, we recorded EPR spectra of a series of spinlabeled nanoparticles at variable temperature and at different frequencies.
Ionita et al. SCHEME 1: Protecting Ligands and Spin Labels Used in This Work
Results and Discussion Spin-Labeled Nanoparticles. We have prepared a series of Au nanoparticles protected by triphenylphosphine or alkanethiols of different chain lengths following literature recipes (Scheme 1). The spin labels were introduced into the nanoparticles by ligand exchange reaction with the corresponding disulfides. Three different spin labels were used with different chain lengths and orientations of the nitroxide fragment (Scheme 1). The stoichiometry used ensured low coverage of spin label (∼1 spin label per nanoparticle) to avoid contribution from spin-spin interactions between spin labels adsorbed on the same nanoparticle. The spin-labeled nanoparticles were purified from unbound ligands by gel permeation chromatography. The purified nanoparticle samples were dissolved in toluene to make 0.1 mM solutions and analyzed by EPR at different temperatures. Spectra Simulations. Line-shape simulations were carried out using the NLSL program developed by Freed and Budil.14,15 In this program, the dynamic parameters of the molecular motion result from a nonlinear least-squares fit of the experimental spectrum to the spectra calculated using the stochastic Liouville equation. Axial symmetry was assumed as a consequence of the molecular geometry of ligands attached at one terminus to gold. Molecular motion was thus defined by an axially symmetric rotational diffusion tensor whose components Rpll and Rprp (expressed as logarithms throughout the paper) correspond to rotations around the long molecular axis and the directions perpendicular to it, respectively. Conventionally, in the molecular frame, the direction of the pπ-orbital containing the unpaired electron is defined as z, the direction along the N-O bond is called x, while y is perpendicular to both. In the case of the doxyl-labeled ligand Dx, Rpll is directed along the z-axis of the doxyl nitrogen and rotation around it averages the x and y components of the hyperfine tensor. This has only a minor effect on the spectral line shape, as Axx ≈ Ayy. Therefore, Rpll values cannot be accurately extracted from the
slow motion doxyl spectra. By contrast, Rprp averages the large Azz value with Axx or Ayy and produces significant changes in the spectral shape. On the other hand, for TEMPO-substituted ligands, both Rpll and Rprp (corresponding to parallel or perpendicular rotational diffusion of ligands) contribute to the spectral shape changes and their values can be extracted from the slow motion spectra. We chose the least sophisticated model which permitted good simulations of the spectra, i.e., simple Brownian diffusion model. We felt that a number of complications (e.g., potentially different diffusion of ligands adsorbed on different binding sites, polydispersity of the nanoparticle size, etc.) precluded the use of more sophisticated models. Although, in some cases, the simulations did not fit the spectral line shape exactly, the quality of simulations was at least adequate in all cases, and the main features of the line shape were well reproduced. We believe therefore that the values of the dynamic parameters were reliably determined by the simulations within the constraints of the chosen model. No ordering potential was considered, since the appearance of doxyl spectra did not suggest high order. Trial simulations made with the microscopic order-macroscopic disorder (MOMD) model yielded very low values for the order parameter. Principal values of g and A tensors (see Table 1) were selected after careful examination of the data obtained by simulations of the spectra of frozen solutions of spin-labeled particles at
Ligand Dynamics in Au Nanoparticles
J. Phys. Chem. C, Vol. 111, No. 45, 2007 16719
Figure 1. EPR spectra of frozen solutions (solid lines) and simulations (dashed lines) of D11-Au-C4 nanoparticles at 150 K in toluene at the X- (a) and W-bands (b), respectively. The simulations shown have identical magnetic parameters.
TABLE 1: Magnetic Parameters for the Spin Labels Used in All Simulations spin probes
gxx
gyy
gzz
TEMPO-based 2.0097 2.0061 2.0020 doxyl-based 2.0090 2.0060 2.0020
Axx (G) Ayy (G) Azz (G) 6.80 4.54
6.70 4.83
33.4 33.3
X-, Q- and W-bands.16 All g component data, while not completely identical, were very close to the literature data on similar radicals. Axx and Ayy values were also close to the literature values; only the polarity-dependent Azz parameter had to be slightly adjusted (all experiments were carried out in toluene). Typical EPR spectra of frozen solutions and simulations are shown in Figure 1 for D11-Au-C4 nanoparticles. Here, D11 denotes the spin label (∼one per nanoparticle), and C4 refers to the surrounding ligand (which makes up the rest of the organic shell). The same code is used throughout the paper. Although the best fits of the spectra of frozen solutions gave slight variations the of g and A tensors for different nanoparticles, we felt that these differences were mostly due to errors and in any case have a minimal effect on the dynamics simulations. In slow motion simulations, the dynamic effects are prevalent in determining the line shapes and small changes in A and g values do not significantly influence the simulated spectra. This was confirmed by trial modifications of A and g values in preliminary simulations. Therefore, two sets of magnetic parameters (for TEMPO and doxyl-type ligands) were used throughout this work without further modification. The tilt angle relating the z-axis to the main diffusion axis was considered as 0° for the doxyl label and 90° for the TEMPO derivatives. Attempts to introduce tilt angle as an adjustable parameter during simulations also did not lead to significant changes of tilt angle or to improved simulations. Our fitting procedure started with the simulation of a chosen spectrum and then continued for the next higher/lower temperature using the previous results as a starting set of parameters. Provided the initial data are good, one can easily simulate a whole series of spectra in a consistent way with minimal changes to parameters except diffusion rates. In a similar way, we have simulated multifrequency data starting from the corresponding X-band spectrum and changing only the value of the magnetic field. Only slight optimization of the dynamic parameters or no optimization at all was necessary to obtain a best fit. Good simulations at several fields with nearly the same dynamic parameters indicated their correct assessment (Figure 2).
Figure 2. EPR spectra (solid lines) and simulations (dashed lines) of Au-C18 nanoparticles labeled with ligands of different length measured at X- and W-bands. Spectra were recorded in toluene at 295 K.
Dynamic Parameters of Nanoparticle-Attached Spin Labels. Although an overview of the spectra clearly shows restricted tumbling of the spin labels on the Au surface, at roomtemperature most spectra are close to the fast motional regime. EPR spectra are most sensitive to the molecular dynamics in the slow motion regime when Redfield theory can no longer be applied. Spectra in this region of incomplete averaging of anisotropies have more features to be matched by simulated spectra and therefore yield more reliable data. To extract most information, we carried out variable temperature EPR measurements over the entire slow motional range, which usually extended from ∼200 K to room temperature. We used three frequencies in our work: X, Q, and W. High frequency measurements present numerous advantages connected with the higher resolutions of the gxx, gyy, and gzz features, which dominate the spectrum, providing a more accurate determination of their values. Also, the onset of slow motional effects for the same nitroxide/solvent system occurs at a higher temperature in higher frequency bands compared to the X-band. Hence, the fast motion spectra at the X-band could appear as slow motion at the W-band (Figure 2), which provides more adequate data for assessing the dynamic parameters. This effect may also help separate the slow components in complex movements, as these become selectively frozen at high frequencies (Vide infra). Finally, comparison of EPR data at several frequencies provides a robust consistency test for the simulation results. The results of dynamics simulations for TEMPO-derived spin labels on Au particles protected with alkanethiols and other ligands are shown in Table 2. Only selected values of Rprp are presented; full results are given in the Supporting Information. In all cases, the Rpll values obtained from the simulations were higher than Rprp by a few decimal units (on the logarithmic scale). The simulations for the doxyl-type spin labels are shown in Table 3. Due to the large number of variables and unknowns, it is difficult to assess errors of the simulations; we believe that the errors in tumbling rates (on a logarithmic scale, as reported in the tables) are approximately (0.1. The rotational diffusion of nanoparticle-attached ligands can include contributions from two types of motion: local motion of the ligand in the monolayer surrounding the nanoparticle and isotropic tumbling of the nanoparticle as a whole. The differentiation between these types of motion is not trivial. Since
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TABLE 2: Rprp Component of the Rotational Diffusion Tensor (in s-1)a for TEMPO-Based Labels on Au Nanoparticles Coated with Different Ligandsb T (K)
D3-Au-C4
D11-Au-C4
D3-Au-C8
D11-Au-C8
210 220 230 260 289 295 310
6.9 7.3 7.4 [7.5] 7.8 [7.8] 8.0 {8.2}
[7.9] 8.1 [8.2] 8.6 9.0
6.8
7.9
7.4 7.6
8.0
D3-Au-C18
7.8 {7.8}
D11-Au-C18
8.5c {8.7}
D3-Au-PEG 7.0 7.1 7.4 {7.6} 7.8
D11-Au-PEG 7.7 8.0 8.5 {8.6}
a As decimal logarithms. b Numbers without brackets, in square brackets, and in curly brackets were calculated from X-, Q- and W-band spectra, respectively. c Recorded at 285 K.
TABLE 3: Rprp Component of the Rotational Diffusion Tensor (in s-1)a for Doxyl-Based Labels (Dx) on Au Nanoparticlesb T (K)
Dx-Au-C4
Dx-Au-C8
Dx-Au-PEG
220 240 260 280 295
7.4 [7.4] 7.7 8.0 8.2 [8.2]
7.3 7.6 7.9 8.0c
7.2 7.5 7.7 7.8c 8.0 {8.0}
a
As logarithms. b Numbers without brackets, in square brackets, and in curly brackets were calculated from X-, Q- and W-band spectra, respectively. c Measured at 275 K.
C4, C8, and PEG-coated nanoparticles have similar sizes, the isotropic tumbling of these particles should have similar rates. As the diffusion rate for the overall motion is always greater than the contributions of the local motion and of the isotropic tumbling, the upper limit for the contribution of the isotropic tumbling cannot exceed the slowest diffusion rate (e.g., D3Au-PEG, Rprp ) 7.6 at 295 K, Table 2). Since most other nanoparticles have significantly higher diffusion rates (see Tables 2 and 3 and the Supporting Information; Rprp’s are logarithms of the tumbling rates), one can assume that for these the overall rates are dominated by local motion. It is interesting to note that the Debye-Stokes-Einstein equation17 predicts much faster isotropic diffusion if one calculates the hydrodynamic radius of the nanoparticle as a sum of the Au core radius and the thickness of the organic shell. For instance, for D3Au-PEG, the nanoparticle radius is 1.2 nm (Au core) + 1.0 nm (PEG ligand), and according to the Debye-Stokes-Einstein equation Rprp ) Rpll ) 8.2 at 295 K. However, the hydrodynamic radius for nanoparticles quite often very significantly exceeds similar estimates.18 Several other observations also suggest that the overall rotational diffusion parameters are dominated by the local motion of the ligands and not the tumbling of the particle as a whole. For instance, the tumbling of a spherical nanoparticle should be isotropic, yet diffusion parameters show significant anisotropy (e.g., Rprp * Rpll, data are in the Supporting Information). If isotropic tumbling had dominated, nanoparticles with the same surrounding ligand (e.g., C4) would have shown the same diffusion parameters regardless of the nature of the spin label (at a very low coverage of spin label used, e.g., ∼1 label per nanoparticle, the spin label is not expected to make a significant impact on the particle tumbling). However, the data in Table 2 clearly show that the D3 and D11 spin labels are characterized by markedly different diffusion parameters in nanoparticles with the same surrounding ligand (e.g., C4). It thus seems certain that the diffusion in nanoparticles is dominated by the local motion of the ligand. The tumbling of the nanoparticle as a whole can only appreciably contribute to the movement in the most immobilized cases, for example, D3Au-PEG and D3-Au-C18. The conclusion that the rotational
diffusion of nanoparticles is dominated by only one type of motion is further confirmed by the good fits and good correspondence between the dynamic parameters obtained at different EPR spectrometer frequencies. X- and W-band spectra are sensitive to molecular motion in rather different ranges, and significant discrepancies are expected if spectra of a complex motion are fitted with the same parameters. In triphenylphosphine-protected Au-P nanoparticles, the Au core is smaller (radius is ∼0.75 nm); hence, the contribution of the tumbling of the whole particles in this case may not be negligible. We observed earlier that fractionation of these particles by size using gel permeation chromatography led to somewhat different rotational correlation times for spin-labeled ligands in different fractions.19 This is consistent with the noticeable contribution of the tumbling of the whole particles (which is of course particle size-dependent) to the overall dynamics of the spin label. It is interesting to note that the rotational diffusion of D3-Au-P nanoparticles is nearly isotropic (see the Supporting Information). Inspection of the data in Tables 2 and 3 shows that both the chain length of the spin-labeled ligand and the chain length of the surrounding ligands affect the diffusion parameters. The effect of the chain length of the spin-labeled ligand (e.g., the longer the linker, the faster the tumbling; cf. diffusion parameters for nanoparticles labeled with D3, Dx, and D11 labels, Tables 2 and 3) is consistent with the decreased packing and increased molecular flexibility further away from the Au nanoparticle surface. The positioning of the nitroxide moiety at the end or in the middle of the chain does not seem to influence this result. For all spin-labeled nanoparticles, the increased chain length of the surrounding ligand led to slower tumbling (e.g., P > C4 g C8 > C18). This appears very logical and presumably reflects the packing density in the ligand shell. However, the tumbling rates for spin labels were very similar for nanoparticles coated with C4 and C8 ligands (Tables 2 and 3). This implies that the packing of ligands in these nanoparticles is quite loose. This conclusion is supported by the absence of order in the Dxlabeled nanoparticles (Figure 3). The Dx label is particularly sensitive to the ordered environments, as the orbital of the unpaired electron is parallel to the long molecular axis. Attempts to introduce the order parameter into the simulations for these nanoparticles resulted in very low values. Interestingly, while C4 and C8 particles had very similar diffusion parameters, the very long ligand (C18) visibly reduced the tumbling rates. Although the differences are small, this result was reproduced for several different batches of nanoparticles. It appears that a tighter packing can be achieved with the C18 ligand compared to the shorter chain ones. A similar disorderorder transition has been observed for alkanethiol monolayers on planar Au substrates.20 The slowest dynamics was consistently observed in PEG-coated nanoparticles, presumably because the interactions of the polar groups with each other and
Ligand Dynamics in Au Nanoparticles
Figure 3. Temperature variation of Dx-Au-C4 spectra recorded at the X- and Q-bands in toluene. Experimental spectra and simulations are shown as solid and dashed lines, respectively.
Figure 4. X-band EPR spectra (solid lines) and simulations (dashed lines) of Au-C4 nanoparticles labeled with ligands of different lengths.
with spin-labeled ligands are hindering the rotational diffusion of the labels. Comparison of Rprp and Rpll values provides a measure of the anisotropy of spin label diffusion. For all TEMPO-based labels, we always found Rpll > Rprp (see the Supporting Information). This is consistent with the more rapid rotation around the long axis of the spin-labeled ligands. The anisotropy however is not the same for different nanoparticles. Triphenylphosphine (P)-coated Au nanoparticles show nearly isotropic tumbling; the tumbling rates are also quite fast. This could be due to the steric bulk of triphenylphosphine which causes rather loose packing of this ligand on the Au surface. Additionally, the motion in this case can have a significant contribution from the tumbling of the particle as a whole (Vide supra). For the doxyl-based label, only Rprp values affect the spectral line shape (Vide supra) and hence can be obtained by spectra simulations. Activation Parameters of Rotational Diffusion for Nanoparticle-Attached Ligands. With increased temperature, the rotational diffusion of the nanoparticle-bound spin labels becomes faster (Figure 4). The comparison of the values in Tables 2 and 3 is consistent with this statement, supporting the validity of the simulations. Some discrepancies can be observed for very fast diffusion (Rpll parameter approaching 10-11; see the Supporting Information). For very fast motion, the EPR spectra become insensitive to the dynamic parameters, particularly at low frequencies, which may introduce significant errors in their determination.
J. Phys. Chem. C, Vol. 111, No. 45, 2007 16721 As the diffusion parameters Rprp and Rpll are logarithms of the rates of tumbling, they are linearly proportional to the energy of tumbling. Hence, the temperature dependence of these parameters can be used to obtain the activation parameters of the rotational diffusion using an Arrhenius-type relationship. We obtained good correlations with Rprp values (Figure 5). Although Rpll values changed monotonously with temperature, the linear relationships in many cases showed significant scatter and were not suitable for calculations of activation parameters. The large errors in determining the Rpll values are due to the fact that the rotation parallel to the molecular axis is faster than that in other directions, and hence, the spectral line shape is dominated by the smaller Rprp values. Although Rpll values also contribute to the line shape, an accurate determination of this parameter is difficult. Nonetheless, a good correlation with the Rpll parameter was obtained for the most immobilized samples, for example, D3-Au-PEG nanoparticles (Figure 5). Unfortunately, we were unable to monitor the temperature dependence of the dynamic parameters for the Au-C18 nanoparticles, as their solubility was very low below room temperature. The activation energies calculated from the Arrhenius plots are shown in Table 4. All activation energies have small, similar values of ∼3 kcal/mol. For comparison, the activation energy of the rotational diffusion of 16-doxylstearic acid (a spin probe similar to Dx) in dialkanoylphosphatidylcholine liquid crystalline phase is 7 kcal/mol for the C14 chain length, while for the longer chain (C12-C22) lipids it is between 8 and 10 kcal/mol.21 For diphosphatidylcholine, the activation energy for the tumbling of spin-labeled cholestane is 6.5 kcal/mol.22 These data show that the rotational diffusion in thiol-coated Au nanoparticles is characterized by lower activation energies compared to liquid crystals. This is not surprising, as due to the high curvature of the Au nanoparticles the packing density decreases significantly with the increased distance from the particle surface. Unlike liquid crystals, the thiol monolayer on the Au particles shows no order (as observed with the Dx probe, Vide supra, Figure 3). Our data are closer to the activation energy of segmental rotational diffusion of spin-labeled polystyrene (∼3 kcal/mol) and are similar to the activation energy of viscous flow in toluene.23 Our results therefore suggest a rather open structure of the ligand shell in gold nanoparticles (in nonpolar solvents). This is also true for the PEG ligand, despite the somewhat slower dynamics of spin labels in this monolayer. Our results thus support the conclusions of Murray et al. based on the reactivity and IR data that, in nonpolar solvents, the alkanethiolate ligands on Au nanoparticles have a disorder approaching that of liquid alkanes.4 The arrangement of ligands in nanoparticles is significantly different from that of monolayers on planar surfaces: in well-packed planar monolayers, semicrystalline order extends throughout the monolayer unless it is disrupted by bulky functional groups. The curved surface of the nanoparticles, on the other hand, leads to a very mobile, open structure; only the atoms closest to the Au surface exhibit high packing and low mobility. Interestingly, the values of all activation energies are very similar. The location of the nitroxide in the molecule (e.g., at the terminus for D11 and D3 or in the middle of the molecule for Dx) has minimal impact on the activation energy. The fact that, in D3-labeled nanoparticles, the length of the spin label approaches that of the surrounding ligand (e.g., PEG or C8) also has remarkably little impact on the activation energy. The small differences show no logical trend, and they are in the range of possible experimental errors. This further supports our
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Figure 5. Correlation of dynamic parameters with temperature. Frequencies are coded as circles (X-band), triangles (Q-band), and squares (Wband). Filled, open, and gray points correspond to different types of nanoparticles as indicated on the graphs directly or with dotted arrows. Lines are linear fits for the indicated types of nanoparticles.
TABLE 4: Activation Energies for Rotational Diffusion Perpendicular to the Long Molecular Axis Au nanoparticles
∆Ea (kcal/mol)
D3-Au-P D3-Au-C4 D3-Au-C8 D3-Au-PEG Dx-Au-C4 Dx-Au-C8 Dx-Au-PEG D11-Au-C4 D11-Au-C8 D11-Au-PEG
2.9 3.9 3.6 2.4 3.7 3.5 3.5 3.9 3.3 3.0
conclusion of a disorganized, solventlike structure of the organic monolayer on the surface of Au nanoparticles. Conclusions We have prepared a series of Au nanoparticles protected by a monolayer of organic ligands and labeled them with disulfidefunctionalized nitroxides. The chain length of the spin labels and the surrounding ligands was systematically varied. We found that the rotational diffusion rate of the spin labels increases with the length of the linker connecting the nitroxide unit to the Au surface. Packing of the organic shell also influences the diffusion parameters. For example, the increased chain length of the surrounding ligand (e.g., tighter packing) led to a slower rotational diffusion rate. Interestingly, packing of the organic shell showed a nonlinear dependence on the chain length: the packing in C4- and C8-alkanethiols was similar, while the C18thiol showed significantly tighter packing. The slowest tumbling was observed with the PEG ligand, which is probably due to the hindering effect of the polar groups. The temperature dependence of the dynamic parameters showed that the activation energies for the rotational diffusion of Au-nanoparticle-attached ligands are very similar for all spin
labels and surrounding ligands. The activation energies were smaller than those observed in liquid crystals and were comparable to viscous flow in solvents or segmental rotational diffusion of polymer chains in solution. These results are consistent with the very open structure and loose packing of the ligand in the monolayer shell on the nanoparticle surface (particularly further away from the curved Au surface). The lack of order observed for the doxyl-based ligand further supports this conclusion. Experimental Section EPR Spectroscopy. EPR spectra were recorded on Bruker ESP-300E (X- and Q-bands) and Elexsys (W-band) spectrometers. The samples were dissolved in toluene to maintain an ∼0.1 mM concentration of nanoparticles. Spin-Labeled Ligands. Spin-labeled ligands D3 and D11 were synthesized and characterized as described previously.13 Doxyl-based ligand Dx was prepared as follows. 5-Doxyl-stearic acid (75 mg, 0.2 mmol), dicyclohexyl carbodiimide (41 mg, 0.2 mmol), and 4-(dimethylamino)pyridine (25 mg, 0.2 mmol) were added to a solution of cystamine (15 mg, 0.1 mmol) in dichloromethane (5 mL). The reaction mixture was stirred at room temperature for 3 days, washed with diluted aqueous hydrochloric acid and water, and then dried. The residue obtained after solvent removal was purified on a silica gel column using a mixture of dichloromethane/methanol 8/2 (v/v) as an eluent. Yield: 27%. Thin-layer chromatography (TLC): Rf 0.19 (DCM/MeOH 9/1). ESI-MS: calcd for C48H92N4O6S2, 884; found, 907 [M + Na]+. Au Nanoparticles. C4-, C8, and C18-protected Au nanoparticles were prepared and purified by the Brust et al. method using a 1:1 ligand/Au ratio and characterized by transmission electron microscopy (TEM).1 The alkanethiol-protected nanoparticles had the same diameter ∼2.4 nm with ∼0.6 nm standard
Ligand Dynamics in Au Nanoparticles deviation. The P-protected nanoparticles were prepared by the Hutchison et al. method24 and purified by gel permeation chromatography using Biobeads S-X1 gel and dichloromethane as an eluent. These nanoparticles had a diameter of ∼1.5 nm; the standard deviation was ∼0.3 nm. Spin-Labeled Au Nanoparticles. Spin-labeled ligands were introduced in the monolayer on Au by a ligand exchange reaction in solution. The solution of the ligand in dichloromethane (0.1 mM) was added to an equal volume of the Au nanoparticle solution in toluene (0.1 mM) and left overnight. On the next day, the solution was evaporated, and the nanoparticles were dissolved in a minimal amount of toluene and separated from the unreacted ligand and other small molecule contamination using gel permeation chromatography (Biobeads S-X1 gel; tolene as an eluent). Acknowledgment. The authors thank the EPSRC (GR/ S45300/1) for funding. A.C. thanks the Romanian Ministry for Education and Research (Grant CNCSIS 1308/2005 and Project CEEX-2/2005) for supporting her visits to the University of York. Supporting Information Available: Full list of diffusion parameters for all nanoparticle types (Tables S1-S3). This material is available free of charge via the Internet at http:// pubs.acs.org. References and Notes (1) Brust, M.; Walker, M.; Bethell, D.; Schiffrin, D. J.; Whyman, R. J. Chem. Soc., Chem. Commun. 1994, 801. (2) Andres, R. P.; Bein, T.; Dorogi, M.; Feng, S.; Henderson, J. I.; Kubiak, C. P.; Mahoney, W.; Osifchin, R. G.; Reifenberger, R. Science 1996, 272, 1323. (3) Terrill, R. H.; Postlethwaite, T. A.; Chen, C.; Poon, C.-D.; Terzis, A.; Chen, A.; Hutchison, J. E.; Clark, M. R.; Wignall, G.; Londono, J. D.; Superfine, R.; Falvo, M.; Johnson, C. S., Jr.; Samulski, E. T.; Murray, R. W. J. Am. Chem. Soc. 1995, 117, 12537. (4) Green, S. J.; Pietron, J. J.; Stokes, J. J.; Hostetler, M. J.; Vu, H.; Wuelfing, W. P.; Murray, R. W. Langmuir 1998, 14, 5612.
J. Phys. Chem. C, Vol. 111, No. 45, 2007 16723 (5) Hicks, J. F.; Zamborini, F. P.; Osisek, A.; Murray, R. W. J. Am. Chem. Soc. 2001, 123, 7048. (6) Ingram, R. S.; Murray, R. W. Langmuir 1998, 14, 4115. (7) Badia, A.; Cuccia, L.; Demers, L.; Morin, F.; Lennox, R. B. J. Am. Chem. Soc. 1997, 119, 2682. (8) Hoestetler, M. J.; Wingate, J. E.; Zhong, C.-J.; Harris, J. E.; Vachet, R. W.; Clark, M. R.; Londono, J. D.; Green, S. J.; Stokes, J. J.; Wignall, G. D.; Glish, G. L.; Porter, M. D.; Evans, N. D.; Murray, R. W. Langmuir 1998, 14, 17. (9) Badia, A.; Lennox, R. B.; Reven, L. Acc. Chem. Res. 2000, 33, 475. (10) Jackson, A. M.; Hu, Y.; Silva, P. J.; Stellacci, F. J. Am. Chem. Soc. 2006, 128, 11135. (11) Ionita, P.; Caragheorgheopol, A.; Gilbert, B. C.; Chechik, V. Langmuir 2004, 20, 11536. (12) Hostetler, M. J.; Templeton, A. C.; Murray, R. W. Langmuir 1999, 15, 3782. (13) Chechik, V.; Wellsted, H. J.; Korte, A.; Gilbert, B. C.; Caldararu, H.; Ionita, P.; Caragheorgheopol, A. Faraday Discuss. 2004, 125, 279. (14) Schneider, D. J.; Freed, J. H. In Spin Labeling: Theory and Application, Biological Magnetic Resonance; Berliner, L. J., Reuben, J., Eds.; Plenum: New York, 1989; Vol. 8. (15) Budil, D. E.; Lee, S.; Saxena, S.; Freed, J. H. J. Magn. Reson., Ser. A 1996, 120, 155. (16) EPR spectra of frozen solutions were fitted using EasySpin simulation software (Stoll, S.; Schweiger, A. J. Magn. Reson. 2006, 178, 42; http://www.easyspin.ethz.ch) and Mfit fitting library (http://www.ill.fr/ Computing/resources/software/matlab/doc/mfit4/index.html). (17) The Debye-Stokes-Einstein equation (τ ) {4πηRh3}/{3kT}) estimates the rotational correlation time τ of a spherical particle with hydrodynamic radius Rh in a continuous medium with viscosity η at temperature T (k is Boltzmann’s constant); see Hwang, J. S.; Mason, R. P.; Hwang, L. P.; Freed, J. H. J. Phys. Chem. 1975, 79, 489. (18) Pons, T.; Uyeda, H. T.; Medintz, I. L.; Mattoussi, H. J. Phys. Chem. B 2006, 110, 20308. (19) Wellsted, H.; Sitsen, E.; Caragheorgheopol, A.; Chechik, V. Anal. Chem. 2004, 76, 2010. (20) Porter, M. D.; Bright, T. B.; Allara, D. L.; Chidsey, C. E. D. J. Am. Chem. Soc. 1987, 109, 3559. (21) Subczynski, W. K.; Markowska, E.; Sielewiesiuk, J. Biochim. Biophys. Acta 1993, 173-181, 1150. (22) Shimayama, Y.; Eriksson, L. E. G.; Ehrenberg, A. Biochim. Biophys. Acta 1978, 508, 213. (23) Pilar, J.; Labsky, J. Macromolecules 1994, 27, 3977. (24) Weare, W. W.; Reed, S. M.; Warner, M. G.; Hutchison, J. E. J. Am. Chem. Soc. 2000, 122, 12890.
