Taylor dispersion analysis is an absolute andstraightforward characterization method that allows determiningthe diffusion coefficient, or equivalently the hydrodynamicradius, from angstroms to submicron size range. In this work,we investigated the use of the Constrained Regularized LinearInversion approach as a new data processing method to extractthe probability density functions of the diffusion coefficient (orhydrodynamic radius) from experimental taylorgrams. Thisnew approach can be applied to arbitrary polydisperse samplesand gives access to the whole diffusion coefficient distributions,thereby significantly enhancing the potentiality of Taylordispersion analysis. The method was successfully applied toboth simulated and real experimental data for solutions ofmoderately polydisperse polymers and their binary and ternary mixtures. Distributions of diffusion coefficients obtained by thismethod were favorably compared with those derived from size exclusion chromatography. The influence of the noise of thesimulated taylorgrams on the data processing is discussed. Finally, we discuss the ability of the method to correctly resolvebimodal distributions as a function of the relative separation between the two constituent species

We use dynamic light scattering to investigate the effects of charge polydispersity and chargeresidence time on the dynamics of a micellar system. While in the corresponding uncharged system onlyone exponential relaxation is observed, two relaxation modes are seen when charging the micelles byadding charged co-surfactant molecules with a long residence time. We attribute the existence of thesetwo relaxation modes to the combined effect of size polydispersity and charge polydispersity, i.e. frozenfluctuations of the number of charges per micelle. Further support to this scenario is provided by controlexperiments on a similar charged system, but where the charge residence time is short compared to thetime scales probed by dynamic light scattering. Here, charge polydispersity is effectively suppressed dueto the rapid exchange of charged molecules between micelles and only one single relaxation mode is seen,thereby demonstrating the key role of frozen charge fluctuations in the complex dynamics of our micellarsystem.

This work aims at demonstrating the interest ofmodern Taylor dispersion analysis (TDA), performed in narrow internal diameter capillary, for monitoring biopolymer degradations. Hydrolytic and enzymatic degradations ofdendrigraft poly-L-lysine taken as model compounds havebeen performed and monitored by TDA at differentdegradation times. Different approaches for the dataprocessing of the taylorgrams are compared, including simpleintegration of the taylorgram, curve fitting with a finite numberof Gaussian peaks, cumulant-like method and ConstrainedRegularized Linear Inversion approach. Valuable informationon the kinetics of the enzymatic/hydrolytic degradation reactions and on the degradation process can be obtained by TDA.

Fracture propagation involves the coupling of many length scales ranging from the sample loading geometry to the molecular level. In brittle materials, the length scales of the damage process zone are reduced to a submicrometric scale and the coupling with the macroscopic scale is expected to be the domain of linear elastic fracture mechanics (LEFM). However, although 2D elastic analyses are generally adequate to describe the sample deformation at macroscopic scales, local investigations of failure mechanisms at the sample free surface require the use of 3D mechanical tools due to the crack front local curvature and to the corner point singularities at the intersection between the crack front and the external surfaces of the sample. We present here a thorough multiscale investigation of-2-the slow crack growth of a sharp crack in oxide glasses in the stress-corrosion regime, combining experimental and numerical analyses of the displacement fields from the millimeter scale to the nanoscale range. The principal aim of the study is identifying the length and time scales of the mechanisms of damage and interaction between water and glass, which have been the subject of an extensive debate in the last decades.

We introduce a new estimator of particle size polydispersity for dynamic light scattering data, which quantifies the relative width of the intensity-weighted distribution of diffusion coefficients. Simulated dynamic light scattering data are analyzed to (i) compare the accuracy and precision of the new polydispersity indicator to polydispersity measurements from standard cumulant and moment analysis (MA) fits and (ii) establish for each method the optimum data range for fitting. Although MA is preferable at low polydispersity, the new estimator is the most accurate and precise at intermediate and large polydispersities. Finally, we successfully apply the method proposed here to real data from colloidal particles, microgels, and polymer solutions.