Diffusant polymer interaction

O. Lumpkin. Diffusion of a reptating polymer interacting with a random matrix. Phys Rev E 45 1910-1915, 1993. 

There is no quantitative model yet describing the observed electro-osmotic drag coefficients as a function of the degree of hydration and temperature. However, the available data provide strong evidence for a mechanism that is (i) hydrodynamic in the high solvation limit, with the dimensions of the solvated hydrophilic domain and the solvent—polymer interaction as the major parameters and (ii) diffusive at low degrees of solvation, where the excess proton essentially drags its primary solvation shell (e.g., H3O+). 

The basic difference between Mconcentration-dependentM and dual-mode, models is in their assumption about penetrant-polymer interactions. Concentration-dependent sorption and transport models are based on the assumption that the concentration-dependence of the solubility and diffusion coefficients arises... 

The gas-polymer-matrix model for sorption and transport of gases in polymers is consistent with the physical evidence that 1) there is only one population of sorbed gas molecules in polymers at any pressure, 2) the physical properties of polymers are perturbed by the presence of sorbed gas, and 3) the perturbation of the polymer matrix arises from gas-polymer interactions. Rather than treating the gas and polymer separately, as in previous theories, the present model treats sorption and transport as occurring through a gas-polymer matrix whose properties change with composition. Simple expressions for sorption, diffusion, permeation and time lag are developed and used to analyze carbon dioxide sorption and transport in polycarbonate. 

The above results illustrate the utility of multiparticle Brownian dynamics for the analysis of diffusion controlled polymerizations. The results presented here are, however, qualitative because of the assumption of a two-dimensional system, neglect of polymer-polymer interactions and the infinitely fast kinetics in which every collision results in reaction. While the first two assumptions may be easily relaxed, incorporation of slower reaction kinetics by which only a small fraction of the collisions result in reaction may be computationally difficult. A more computationally efficient scheme may be to use Brownian dynamics to extract the rate constants as a function of polymer difflisivities, and to incorporate these in population balance models to predict the molecular weight distribution [48-50]. We discuss such a Brownian dynamics method in the next section. 

Sorption of water vapor by polymers is a diffusions process (9). The rate and extent of water sorption depends on the diffusion coefficient of water in the polymer, on the water/polymer interaction, and on the temperature. 

IGC can be used to determine various properties of the stationary phase, such as the transition temperatures, polymer—polymer interaction parameters, acid-base characteristics, solubility parameters, crystallinity, surface tension, and surface area. IGC can also be used to determine properties of the vapor-solid system, such as adsorption properties, heat of adsorption, interaction parameters, interfacial energy, and diffusion coefficients. The advantages of IGC are simplicity and speed of data collection, accuracy and precision of the data, relatively low capital investment, and dependability and low operating cost of the equipment. 

In the short distance (time) limit, the D plot makes a plateau at the value almost equal to D0 and is invariant on addition of mesh materials. In this area only a minority of diffusing particles interact with polymer chains during their short travel. 

Xsn is the solvent-polymer interaction parameter for a solvent concentration of s. We will assume that the concentrations 4>s and < )p are much larger than the diffusant concentration (i so that Xs and Xp can be replaced by Xs and Xp. In this limit... 

In this section 10.2, we review the various solid-state NMR methods used to investigate interpolymer interactions, molecular motion and the spatial structure of a polymer blend. An interaction between component polymers affects the chemical shifts and lineshapes (see Section 10.2.2.1) and the molecular motions of the component polymers (see Section 10.2.2.2). In Section 10.2.3.1, microheterogeneity from 2 to 50 nm is studied by measuring spin diffusion indirectly from its effects on H spin-lattice relaxation. The spin-diffusion processes can also be monitored by several methods based on the Goldman-Shen experiment [8] (see Section 10.2.3.2). Homonuclear and heteronuclear two-dimensional correlation experiments reveal how and to what extent component polymers interact with each other (see Section... 

Chitosan and several of its innumerable derivatives have the ability to form thin membranous films of use in packaging [254-256], encapsulation and drug delivery systems. Due to drug polymer interactions, high viscosity chitosan films showed better sustainable release and the mechanism of release followed Fickian diffusion control with subsequent zero order release [257]. 

In conventional polymers, their chemical nature influences both the molecular interaction of the polymers and the molecular interaction of the polymers and water. The former situation largely determines diffusivity, and the latter influences solubility. For example, the polarity of polymers will increase the interaction between polymers and decrease the diffusivity, whereas a water-polymer interaction increases with an increase in the polarity of polymers and leads to an increase in solubility. These situations may be seen in the schematic representations of S, D, and P in Figure 2 as functions of cohesive energy density. 

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