No Arabic abstract
We introduce an elegant method which allows the application of diffusing-wave spectroscopy (DWS) to nonergodic, solid-like samples. The method is based on the idea that light transmitted through a sandwich of two turbid cells can be considered ergodic even though only the second cell is ergodic. If absorption and/or leakage of light take place at the interface between the cells, we establish a so-called multiplication rule, which relates the intensity autocorrelation function of light transmitted through the double-cell sandwich to the autocorrelation functions of individual cells by a simple multiplication. To test the proposed method, we perform a series of DWS experiments using colloidal gels as model nonergodic media. Our experimental data are consistent with the theoretical predictions, allowing quantitative characterization of nonergodic media and demonstrating the validity of the proposed technique.
We present a detection scheme for diffusing wave spectroscopy (DWS) based on a two cell geometry that allows efficient ensemble averaging. This is achieved by putting a fast rotating diffuser in the optical path between laser and sample. We show that the recorded (multi-speckle) correlation echoes provide an ensemble averaged signal that does not require additional time averaging. We find the performance of our experimental scheme comparable or even superior to camera based multi-speckle techniques that rely on direct spatial averaging. Furthermore, combined with traditional two-cell DWS, the full intensity autocorrelation function can be measured with a single experimental setup covering more than 10 decades in correlation time.
Diffusing wave spectroscopy (DWS) can be employed as an optical rheology tool with numerous applications for studying the structure, dynamics and linear viscoelastic properties of complex fluids, foams, glasses and gels. To carry out DWS measurements, one first needs to quantify the static optical properties of the sample under investigation, i.e. the transport mean free path $l^ast$ and the absorption length $l_a$. In the absence of absorption this can be done by comparing the diffuse optical transmission to a calibration sample whose $l^ast$ is known. Performing this comparison however is cumbersome, time consuming and prone to mistakes by the operator. Moreover, already weak absorption can lead to significant errors. In this paper, we demonstrate the implementation of an automatized approach, based on which the DWS measurement procedure can be simplified significantly. By comparison with a comprehensive set of calibration measurements we cover the entire parameter space relating measured count rates (CR$_t$, CR$_b$) to ($l^ast$, $l_a$). Based on this approach we can determine $l^ast$ and $l_a$ of an unknown sample accurately thus making the additional measurement of a calibration sample obsolete. We illustrate the use of this approach by monitoring the coarsening of a commercially available shaving foam with DWS.
While a significant body of investigations have been focused on the process of protein self-assembly, much less is understood about the reverse process of a filament breaking due to thermal motion into smaller fragments, or depolymerization of subunits from the filament ends. Indirect evidence for actin and amyloid filament fragmentation has been reported, although the phenomenon has never been directly observed either experimentally or in simulations. Here we report the direct observation of filament depolymerization and breakup in a minimal, calibrated model of coarse-grained molecular simulation. We quantify the orders of magnitude by which the depolymerization rate from the filament ends $k_mathrm{off}$ is larger than fragmentation rate $k_{-}$ and establish the law $k_mathrm{off}/k_- = exp [( varepsilon_| - varepsilon_bot) / k_mathrm{B}T ] = exp [0.5 varepsilon / k_mathrm{B}T ]$, which accounts for the topology and energy of bonds holding the filament together. This mechanism and the order-of-magnitude predictions are well supported by direct experimental measurements of depolymerization of insulin amyloid filaments.
We carry out a coarse-grained molecular dynamics simulation of phospholipid vesicles with transmembrane proteins. We measure the mean and Gaussian curvatures of our protein-embedded vesicles and quantitatively show how protein clusters change the shapes of their host vesicles. The effects of depletion force and vesiculation on protein clustering are also investigated. By increasing the protein concentration, clusters are fragmented to smaller bundles, which are then redistributed to form more symmetric structures corresponding to lower bending energies. Big clusters and highly aspherical vesicles cannot be formed when the fraction of protein to lipid molecules is large.
A small, bimetallic particle in a hydrogen peroxide solution can propel itself by means of an electrocatalytic reaction. The swimming is driven by a flux of ions around the particle. We model this process for the presence of a monovalent salt, where reaction-driven proton currents induce salt ion currents. A theory for thin diffuse layers is employed, which yields nonlinear, coupled transport equations. The boundary conditions include a compact Stern layer of adsorbed ions. Electrochemical processes on the particle surface are modeled with a first order reaction of the Butler-Volmer type. The equations are solved numerically for the swimming speed. An analytical approximation is derived under the assumption that the decomposition of hydrogen peroxide occurs mainly without inducing an electric current. We find that the swimming speed increases linearly with hydrogen peroxide concentration for small concentrations. The influence of ion diffusion on the reaction rate can lead to a concave shape of the function of speed vs. hydrogen peroxide concentration. The compact layer of ions on the particle diminishes the reaction rate and consequently reduces the speed. Our results are consistent with published experimental data.