Solubility parameter, glass transition polymers

The standard molecular structural parameters that one would like to control in block copolymer structures, especially in the context of polymeric nanostructures, are the relative size and nature of the blocks. The relative size implies the length of the block (or degree of polymerization, i.e., the number of monomer units contained within the block), while the nature of the block requires a slightly more elaborate description that includes its solubility characteristics, glass transition temperature (Tg), relative chain stiffness, etc. Using standard living polymerization methods, the size of the blocks is readily controlled by the ratio of the monomer concentration to that of the initiator. The relative sizes of the blocks can thus be easily fine-tuned very precisely to date the best control of these parameters in block copolymers is achieved using anionic polymerization. The nature of each block, on the other hand, is controlled by the selection of the monomer for instance, styrene would provide a relatively stiff (hard) block while isoprene would provide a soft one. This is a consequence of the very low Tg of polyisoprene compared to that of polystyrene, which in simplistic terms reflects the relative conformational stiffness of the polymer chain. 

As biological systems have always been an inspiration for scientists, intracellular compartments (such as lysosomes or mitochondria) also have their artificial equivalents in polymer vesicles, called polymersomes. Polymersomes are spherical compartments with a bi- or monolayer membrane, generated by self-assembly of di- or triamphiphilic block copolymers in diluted aqueous conditions. To favor the formation of structures such as polymersomes, it is necessary to have a hydrophilic fraction of the copolymer mass of 25-40%, and polymer concentration above the critical micellar concentration. Other parameters that affect the self-assembly process, and therefore the final architecture of the polymer supramolecular assemblies, are the molecular weight of the copolymer (Af ), block lengths, solubility, and glass transition temperature (Tg) [21,22], The relative mass or volume fraction of each block is a key parameter in the formation of a self-assembled structure with a certain membrane curvature, and ultimately, with a specific architecture. The of the copolymer (and thus the block lengths) dictates the membrane thickness and polymersome properties, such as membrane fluidity, stabihty, and permeabihty [21,74],... 

In this approach, connectivity indices were used as the principle descriptor of the topology of the repeat unit of a polymer. The connectivity indices of various polymers were first correlated directly with the experimental data for six different physical properties. The six properties were Van der Waals volume (Vw), molar volume (V), heat capacity (Cp), solubility parameter (5), glass transition temperature Tfj, and cohesive energies ( coh) for the 45 different polymers. Available data were used to establish the dependence of these properties on the topological indices. All the experimental data for these properties were trained simultaneously in the proposed neural network model in order to develop an overall cause-effect relationship for all six properties. 

Figure 25 ANN model (5-8-6) training and testing results for van der Waals volume, molar volume, heat capacity, solubility parameter, and glass transition temperature of 45 different polymers.

In a fundamental sense, the miscibility, adhesion, interfacial energies, and morphology developed are all thermodynamically interrelated in a complex way to the interaction forces between the polymers. Miscibility of a polymer blend containing two polymers depends on the mutual solubility of the polymeric components. The blend is termed compatible when the solubility parameter of the two components are close to each other and show a single-phase transition temperature. However, most polymer pairs tend to be immiscible due to differences in their viscoelastic properties, surface-tensions, and intermolecular interactions. According to the terminology, the polymer pairs are incompatible and show separate glass transitions. For many purposes, miscibility in polymer blends is neither required nor de-... 

Table 9. Effect of organic substituents on the solubility parameter and the glass transition temperature of an organosiloxane polymer...

This statement can be proved very easily by considering four different types of general POP properties and their variability as a function of the side substituents on the polymer skeleton, i.e. glass transition temperature (Tg), morphology, solvent solubility and limiting oxygen index (LOI). The values of these parameters are reported in Tables 5-8. 

PS has a high index of refraction (1.592) and hence has excellent transparency to visible light. PS is a brittle polymer with a glass transition temperature rgof 100 C, a heat deflection temperature of 90 C, and a solubility parameter of 9.1 H. 

The relative initial ratio of acrylonitrile to butadiene and degree of conversion of nitrile to amidoxime are directly related to the resultant film s solubility parameter and glass transition temperature. Ideally, the concentration of amidoxime functional groups would be maximized while the coating s solubility parameter is matched to the vapor to be detected and the glass transition temperature is kept below room temperature. In practice, the conversion limitations are set by the reaction conditions of limited polymer solubility, reaction temperature and time. Three terpolymers of varying butadiene, acrylonitrile and amidoxime compositions were prepared as indicated in Table 1. 

The infrared spectra of the butadiene-acrylonitrile copolymer and butadiene-acrylonitrile-acrylamidoxime terpolymers are presented in Figure 2. The amidoxime specific bands appear at 3480 and 3380 cm-l (NH2 stretching) and at 1660 cm"l (C =N stretching) (1 2 ). The glass transition temperatures and solubility parameters of the corresponding polymers are also presented in Table 1. As the aerylamidoxime content increases from 3 to 7 to 45 mole percent, the... 

Kambour et al. performed extensive studies on the mechanisms of plasticization [18-25]. The correlation observed between the critical strain to craze and the extent of the glass-transition temperature (Tg) depression speaks strongly in favor of a mechanism of easier chain motion and hence easier void formation. In various studies on polycarbonate [19,24], polyphenylene oxide [20], polysulfone [21], polystyrene [22], and polyetherimide [25], Kambour and coauthors showed that the absorption of solvent and accompanying reduction in the polymer s glass-transition temperature could be correlated with a propensity for stress cracking. The experiments, performed over a wide range of polymer-solvent systems, allowed Kambour to observe that the critical strain to craze or crack was least in those systems where the polymer and the solvent had similar solubility values. The Hildebrand solubility parameter S [26] is defined as... 

Figure 2 The transport of a multifunctional hydroxyl dye to various dye-acceptor polymers during thermal transfer printing. P is the effective permeability coejficient Tg is the glass transition temperature of the polymer and bp are solubility parameters of dye and polymer, respectively Vj ,cr and are infrared absorptions estimating the dye-polymer specific interaction...

Many properties of pure polymers (and of polymer solutions) can be estimated with group contributions (GC). Examples of properties for which (GC) methods have been developed are the density, the solubility parameter, the melting and glass transition temperatures, as well as the surface tension. Phase equilibria for polymer solutions and blends can also be estimated with GC methods, as we discuss in Section 16.4 and 16.5. Here we review the GC principle, and in the following sections we discuss estimation methods for the density and the solubility parameter. These two properties are relevant for many thermodynamic models used for polymers, e.g., the Hansen and Flory-Hug-gins models discussed in Section 16.3 and the free-volume activity coefficient models discussed in Section 16.4. 

The solubility parameter concept has been used to correlate many physical phenomena. Miscibility of solvents with polymers, diffusion of solvents within polymers, effects of intermolecular forces on the glass transition temperature and interfacial interactions within copolymer materials would be included, just to mention a few examples. In many cases, meaningful interpretation of results was facilitated with the use of the solubility parameter. 

On the other hand, many important properties of materials are intensive properties. The values of intensive properties are essentially independent of the amount of material present, provided of course that this amount is not zero. An intensive property can usually be expressed in terms of the quotient of a pair of extensive properties. For example, the density equals the molecular weight per repeat unit divided by the molar volume. The solubility parameter equals the square root of the cohesive energy density (defined as the cohesive energy divided by the molar volume). As shown in Chapter 1, the glass transition temperature (an intensive property) can often be estimated in terms of the molar glass transition function divided by the molecular weight of a repeat unit of the polymer. 

The cohesive forces holding its different components together. The relevant components for the glass transition in amorphous polymers are chain segments. The cohesive forces can be quantified in terms of the cohesive energy density or the solubility parameter. 

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