We report the functionalization of cross-linked poly(divinylbenzene) (pDVB) microspheres using both thiol-ene chemistry and azide-alkyne click reactions. The RAFT technique was carried out to synthesize SH-functionalized poly(N-isopropylacrylamide) (pNIPAAm) and utilized to generate pNIPAAm surface-modified microspheres via thiol-ene modification. The accessible double bonds on the surface of the microspheres allow the direct coupling with thiol-end functionalized pNIPAAm. In a second approach, pDVB microspheres were grafted with poly(2-hydroxyethyl methacrylate) (pHEMA). For this purpose, the residual double bonds on the microspheres surface were used to attach azide groups via the thiol-ene approach of 1-azido-undecane-11-thiol. In a second step, alkyne endfunctionalized pHEMA was used to graft pHEMA to the azide-modified surface via click-chemistry (Huisgen 1,3-dipolar cycloaddition). The surface-sensitive characterization methods X-ray photoelectron spectroscopy, scanning-electron microscopy and FT-IR transmission spectroscopy were employed to characterize the successful surface modification of the microspheres. In addition, fluorescence microscopy confirms the presence of grafted pHEMA chains after labeling with Rhodamine B.

Diffusion in crowded fluids, e.g. in the cytoplasm of living cells, has frequently been reported to show anomalous characteristics (socalled 'subdiffusion'). Several random walk models have been proposed to explain these observations, yet so far an experimentally supported decision in favor of one of these models has been lacking. Here, we show that experimentally obtained trajectories in a prototypical crowded fluid show an asphericity that is most consistent with the predictions of fractional Brownian motion, i.e. an anticorrelated, anti-persistent generalization of normal Brownian motion that is related to the fluid's viscoelasticity.

Many reactions in complex fluids, e.g. signaling cascades in the cytoplasm of living cells, are governed by a diffusion-driven encounter of reactants. Yet, diffusion in complex fluids often exhibits an anomalous characteristic ('subdiffusion'). Since different types of subdiffusion have distinct effects on timing and equilibria of chemical reactions, a thorough determination of the reactants' type of random walk is key to a quantitative understanding of reactions in complex fluids. Here we introduce a straightforward and simple approach for determining the type of subdiffusion from single-particle tracking data. Unlike previous approaches, our method also is sensitive to transient subdiffusion phenomena, e.g. obstructed diffusion below the percolation threshold. We validate our strategy with data from experiment and simulation.

We provide experimental results on the accuracy of diffusion coefficients obtained by a mean squared displacement (MSD) analysis of single-particle trajectories. We have recorded very long trajectories comprising more than 1.5 × 10(5) data points and decomposed these long trajectories into shorter segments providing us with ensembles of trajectories of variable lengths. This enabled a statistical analysis of the resulting MSD curves as a function of the lengths of the segments. We find that the relative error of the diffusion coefficient can be minimized by taking an optimum number of points into account for fitting the MSD curves, and that this optimum does not depend on the segment length. Yet, the magnitude of the relative error for the diffusion coefficient does, and achieving an accuracy in the order of 10% requires the recording of trajectories with about 1000 data points. Finally, we compare our results with theoretical predictions and find very good qualitative and quantitative agreement between experiment and theory.

No abstract