Thermoresponsive Pentablock Copolymer on Silica : Temperature Effects on Adsorption, Surface Forces, and Friction

The adsorption of hydrophilic or amphiphilic multiblock copolymers provides a powerful means to produce well-defined "smart" surfaces, especially if one or several blocks are sensitive to external stimuli. We focus here on an A-B-A-B-A copolymer, where A is a cationic poly((3acrylamido-propyl)-trimethylammonium chloride) (PAMPTMA) block containing 15 (end blocks) or 30 (middle block) repeat units and B is a neutral thermosensitive water-soluble poly(2-isopropyl-2-oxazoline) (PIPOZ) block with 50 repeat units. X-ray reflectivity and quartz crystal microbalance with dissipation monitoring were employed to study the adsorption of PAMPTMA(15)-PAMPTMA(30)-PIPOZ(50)-PAMPTMA(15) on silica surfaces. The latter technique was employed at different temperatures up to 50 degrees C. Surface forces and friction between the two silica surfaces across aqueous pentablock copolymer solutions at different temperatures were determined with the atomic force microscopy colloidal probe force and friction measurements. The cationic pentablock copolymer was found to have a high affinity to the negatively charged silica surface, leading to a thin (2 nm) and rigid adsorbed layer. A steric force was encountered at a separation of around 3 nm from hard wall contact. A capillary condensation of a polymer-rich phase was observed at the cloud point of the solution. The friction forces were evaluated using Amontons' rule modified with an adhesion term.Peer reviewe

Nonequilibrium thermodynamics of the sedimentation potential and electrophoresis

The thermodynamics of irreversible processes is developed for a system placed in a centrifugal field and consisting of a number of components, some of which carry electrical charges. It is found that an Onsager reciprocal relation connects the sedimentation potential with a quantity which we call barycentric electrophoresis (i.e. the quotient of the total mass flow and the electrical field at zero centrifugal field). The latter quantity turns out to be ordinary electrophoresis in a colloid (i.e. in a system of one neutral and a number of charged components, one of which consists of colloidal particles) under certain limiting, but frequently realized, circumstances. If conduction relaxation exists, it appears in both connected phenomena described here.SCOPUS: ar.jinfo:eu-repo/semantics/publishe

Protein Charge Determination

The most popular current method of determining protein valence entails the calculation of net charge from amino acid sequence/composition. However, the inaccuracy of that approach was recognized long before the advent of the protein data banks and computer programs to facilitate its adoption. Capillary zone electrophoresis affords the simplest and most economical procedure for obtaining a reliable estimate of the net charge of a protein in the buffer system of interest. This unit explains the major pitfalls in the calculation of net charge from protein sequence data

General discussion

SCOPUS: no.jinfo:eu-repo/semantics/publishe

Bayesian inversion of joint SH seismic and seismoelectric data to infer glacier system properties

International audienceIn glacial studies, properties such as glacier thickness and the basement permeabilityand porosity are key to understand the hydrological and mechanical behaviour ofthe system. The seismoelectric method could potentially be used to determine keyproperties of glacial environments. Here we analytically model the generation of seis-mic and seismoelectric signals by means of a shear horizontal seismic wave sourceon top of a glacier overlying a porous basement. Considering a one-dimensionalsetting, we compute the seismic waves and the electrokinetically induced electricfield. We then analyse the sensitivity of the seismic and electromagnetic data to rele-vant model parameters, namely depth of the glacier bottom, porosity, permeability,shear modulus and saturating water salinity of the glacier basement. Moreover, westudy the possibility of inferring these key parameters from a set of very low noisesynthetic data, adopting a Bayesian framework to pay particular attention to theuncertainty of the model parameters mentioned above. We tackle the resolution ofthe probabilistic inverse problem with two strategies: (1) we compute the marginalposterior distributions of each model parameter solving multidimensional integralsnumerically and (2) we use a Markov chain Monte Carlo algorithm to retrieve acollection of model parameters that follows the posterior probability density func-tion of the model parameters, given the synthetic data set. Both methodologies areable to obtain the marginal distributions of the parameters and estimate their meanand standard deviation. The Markov chain Monte Carlo algorithm performs betterin terms of numerical stability and number of iterations needed to characterize thedistributions. The inversion of seismic data alone is not able to constrain the values ofporosity and permeability further than the prior distribution. In turn, the inversion ofthe electric data alone, and the joint inversion of seismic and electric data are usefulto constrain these parameters as well as other glacial system properties. Furthermore,the joint inversion reduces the uncertainty of the model parameters estimates andprovides more accurate results