Self-assembly of soft nanoparticles with tunable patchiness

Transcription

1 SUPPLEMENTARY INFORMATION Self-assembly of soft nanoparticles with tunable patchiness THOMAS M. HERMANS 1,5, MAARTEN A. C. BROEREN 5, NIKOS GOMOPOULOS 2, PAUL VAN DER SCHOOT 4, MARCEL H. P. VAN GENDEREN 1,5, NICO A. J. M. SOMMERDIJK 3, GEORGE FYTAS 2, E. W. MEIJER *,1,5 1 Institute for Complex Molecular Systems, Eindhoven University of Technology, P.O. Box 513, 5600 MB Eindhoven, The Netherlands 2 Department of Materials Science and Technology, University of Crete and F.O.R.T.H., P.O. Box 1527, Heraklion, Greece 3 Soft Matter CryoTEM Research Unit, Eindhoven University of Technology, P.O. Box 513, 5600 MB Eindhoven, The Netherlands 4 Group Theory of Polymers and Soft Matter, Eindhoven University of Technology, P.O. Box 513, 5600 MB Eindhoven, The Netherlands 5 Laboratory of Macromolecular and Organic Chemistry, Eindhoven University of Technology, P.O. Box 513, 5600 MB Eindhoven, The Netherlands * To whom correspondence should be addressed: e.w.meijer@tue.nl This document includes: Figures S1 to S5 Additional 1 H-DOSY NMR measurements Box-counting analysis References nature nanotechnology 1

2 supplementary information Additional Figures Figure S1: Full structure of the fifth generation urea-adamantyl terminated poly(propylene imine) dendrimer host molecule as shown in its abbreviated form in Figure 1A in the main text. Figure S2: 300 kv cryo-electron projection image showing a larger part of the network structure found using G/H=64 at a concentration of M (see Figure 3 in the main text). The scale-bar is 100 nm. 2 nature nanotechnology

3 supplementary information Figure S3: Larger part of the WBP reconstruction of the cryo-electron tomography reconstruction at a concentration of M and a guest-to-host ratio G/H=64 (see Figure 3B in the main text). The branching points (mostly y-junctions) are colored purple. On average there are about y-junctions per μm3. Figure S4: 200 kv cryo-electron projection images of the trapped-core particles obtained at a guest-tohost ratio G/H=32 at the concentrations (with respect to the guest molecules) a) M b) M c) M. On average three host molecules are present in the core of the trapped core particles. Often, large scale globular structures are observed, which consist of guest and host molecules as we have described befores1. The scale-bar is 50 nm in all images. 3 nature nanotechnology 3

4 supplementary information Additional 1 H-DOSY analysis: influence of guest-guest interactions a b Diffusion coefficient [10-10 m 2 s -1 ] Guest molecule only Host molecule in G/H = 64 Guest molecule in G/H = Concentration guest molecule [M] Hydrodynamic radius [m] Guest molecule only Host molecule in G/H = 64 Guest molecule in G/H = Concentration guest molecule [M] Figure S5: a) 1 H-DOSY NMR measurements as depicted in Figure 2 in the main text, now showing as a reference the diffusion coefficient of only the guest molecule (without the host) in D 2 O versus concentration. b) The hydrodynamic radii calculated form the diffusion coefficients shown in A) using the Stokes-Einstein equation. To assess the contribution of guest-guest interactions in the dilution-induced selfassembly process that is described in the main text, we performed additional 1 H-DOSY NMR measurements on the guest molecule in D 2 O in absence of the host molecule (Figure S5). Towards higher concentrations we measure a slight decrease in the guest molecule s diffusion coefficient, while the HDO self-diffusion is staying constant (not shown). This indicates that at concentrations above ~0.015 M weak guest-guest interactions are possible. However, the guest molecule diffuses significantly slower in the presence of the patchy particles, than in the absence of the particle (triangles versus squares in Figure S5A and B), which indicates that the main contribution to the decrease in diffusion coefficient of the guest molecule is due to binding to the host molecule and not due to guest-guest interactions. Moreover, a significant number of guest molecules are needed to keep the patchy particle solubilized in aqueous solution. The concentration of unbound guest molecules available for participation in guest-guest interactions is therefore even lower. These results support the notion that guest-guest interactions are not relevant to the description of the process of dilution-induced self-assembly. The fraction of guest molecules bound to the dendrimer host particle (f b ) is estimated using the equation: D obs D g, unbound D obs D mono f b = = D D D D g, bound g, unbound D obs : The observed diffusion coefficient of the guest h g, mono D unbound : The diffusion coefficient of the unbound guest, which can be approximated using the diffusion of the guest in its monomeric state (D mono = 2.6 x m 2 s -1 ) D bound : The diffusion coefficient of the guest bound to the patchy particle, which can be approximated using the diffusion coefficient of the host molecule observed in the 1 H- DOSY NMR measurements (D h ). At 4.92 x 10-2 M, the estimated amount of bound guest 4 nature nanotechnology

5 supplementary information molecules to the patchy particles is 53% using the stated equation. Dilution causes further desorption of the guest molecules (i.e. a lower f b ) from the patchy particle as is described in the main text. 3-Dimensional box-counting TruSoft Int'l Inc.'s Benoit fractal analysis software (3D-FD) was used to calculate the fractal dimension of the network of patchy particles. The WBP reconstructed 3D volume was analyzed using the build-in algorithm described below. Using 3D data to calculate the 3D fractal dimension is of key importance, because it was found that adding 1 to the 2D fractal dimension is inappropriate S2 The used algorithm works as follows: a given set of points is covered by boxes with linear size d. Let N(d) is the minimum number of boxes necessary to cover this set. For each d 3D-FD counts N(d) and plots logarithm of N(d) on vertical axis versus logarithm of d on horizontal axis. If set is indeed fractal, this plot should follow a straight line with negative slope D, and D is a fractal dimension of given set. So algorithm consists of following steps: a) Let the linear box size d is maximum. b) Let current N(d)=0. Divide the entire set (which is 3D-box filled with white and black points) to a number of boxes with linear size d. c) For each sub box enumerate all it s points and check if at least one of them is data point (it can be white or black). If it is true, then increment N(d) number. For the visualization of the self-assembled structures in cryo-electron tomography underfocus values of -4 µm were applied. The resulting Fresnel fringes cause structures to appear larger than they are in reality. However, the threshold, which distinguishes between what is part of the network structure what is not i.e. solvent (water), was set to the volume fraction that corresponds to the actual concentration of the solution. Therefore, we expect the Fresnel fringes not to influence the calculation of the fractal dimension. S1 Hermans, T.M. et al. Stepwise noncovalent synthesis leading to dendrimer-based assemblies in water. J. Am. Chem. Soc. 129, (2007) S2 Tan D., Marangoni, A.G. 3D fractal dimension of fat crystal networks. Chem. Phys. Lett. 433, (2006) nature nanotechnology 5