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Interaction parameters

The first two terms result from the configurational entropy of mixing and are always negative. For AG to be negative, the value of must be small. The theoiy assumes that the parameter %i does not depend on concentration but this has not been experimentally confirmed. [Pg.124]

The critical value of that is sufficient for the compatibility of a polymer with a laige molecular mass with a plasticizer, is 0.5. A good plasticizer or solvent has a low value. Xi is a popular practical compatibihty criterion. Comprehensive compilations of its values ve beenpubhshed.  [Pg.125]

The theory of solutions assumes that molecules are spherical. For long-chain polymer molecules, consisting of segments, the number of modes of arrangement in a solution lattice differs from those of spherical molecules. This results in deviations from the ideal entropy of mixing. The polymer-plasticizer interaction differs qualitatively because of the presence of segments coimected into chains. [Pg.125]

Some novel statistical theories of solutions of polymers may also use the parameter. But they also use other interaction parameters discussed below. A number of interaction parameters can be used to account for the Flory-Huggins parameter s dependence on concentratiorr, size and shape of plasticizer molecules, isothermic compressibility and ejqransion of materials, etc. However experimental difficulties in estimating these parameters hmit the application of these theories. The Flory-Huggins parameter is the simplest nttmerical criterion of compatibility. Methods of estimating the Flory-Huggins parameters are similar to the methods of testing for compatibility. The experimental methods are presented in Section 6.3. [Pg.125]


The data base contains provisions for a simple augmentation by up to eight additional compounds or substitution of other compounds for those included. Binary interaction parameters necessary for calculation of fugacities in liquid mixtures are presently available for 180 pairs. [Pg.5]

UNIQUAC interaction parameters were not determined, but were assumed to be zero for this system. Quantities in parentheses refer to adiabatic flash. [Pg.123]

Appendix C-7 gives interaction parameters for noncondensable components with condensable components. (These are also included in Appendix C-5). Binary data sources are given. [Pg.144]

INTERACTION PARAMETERS FOR LIQUIO-PHASE MIXTURES COMPONENT NAMES... [Pg.183]

Vector (length 20) of stream composition (I = 1,N). Contribution from temperature dependence of UNIQUAC binary interaction parameters, here taken as 0. [Pg.296]

TAUS calculates temperature dependent UNIQUAC binary interaction parameters, use in subroutine GAMMA and ENTH. [Pg.313]

Pure component parameters for 92 components, and as many binary interaction parameters as have been established, are cited in Appendix C. These parameters can be loaded from formated cards, or other input file containing card images, by subroutine PARIN. [Pg.340]

The addition of components to this set of 92, the change of a few parameter values for existing components, or the inclusion of additional UNIQUAC binary interaction parameters, as they may become available, is best accomplished by adding or changing cards in the input deck containing the parameters. The formats of these cards are discussed in the subroutine PARIN description. Where many parameters, especially the binary association and solvation parameters are to be changed for an existing... [Pg.340]

PARIN first loads all pure component data by reading two records per component. The total number of components, M, in the library or data deck must be known beforehand. Next the associ-ation/solvation parameters are input for M components. Finally all the established UNIQUAC binary interaction parameters (or noncondensable-condensable interaction parameters) are read. [Pg.341]

Set of cards for UNIQUAC binary interaction parameters up to M(M-l)/2 cards) component indices I and J... [Pg.342]

IFIABSIE).GT.l.E-19) GO TO 900 9 INITIALLY ZERO UNIQUAC BINARY INTERACTION PARAMETERS... [Pg.343]

U(J,I) FORMAT(2I5, 2F10.2) giving all known interaction parameters. [Pg.345]

In polymer solutions and blends, it becomes of interest to understand how the surface tension depends on the molecular weight (or number of repeat units, IV) of the macromolecule and on the polymer-solvent interactions through the interaction parameter, x- In terms of a Hory lattice model, x is given by the polymer and solvent interactions through... [Pg.69]

Of particular interest has been the study of the polymer configurations at the solid-liquid interface. Beginning with lattice theories, early models of polymer adsorption captured most of the features of adsorption such as the loop, train, and tail structures and the influence of the surface interaction parameter (see Refs. 57, 58, 62 for reviews of older theories). These lattice models have been expanded on in recent years using modem computational methods [63,64] and have allowed the calculation of equilibrium partitioning between a poly-... [Pg.399]

While the phase rule requires tliree components for an unsymmetrical tricritical point, theory can reduce this requirement to two components with a continuous variation of the interaction parameters. Lindli et al (1984) calculated a phase diagram from the van der Waals equation for binary mixtures and found (in accord with figure A2.5.13 that a tricritical point occurred at sufficiently large values of the parameter (a measure of the difference between the two components). [Pg.659]

In polymer solutions or blends, one of the most important thennodynamic parameters that can be calculated from the (neutron) scattering data is the enthalpic interaction parameter x between the components. Based on the Flory-Huggins theory [4T, 42], the scattering intensity from a polymer in a solution can be expressed as... [Pg.1416]

First determine what parameters will be used for describing bond lengths and angles. Then determine torsional, inversion, and nonbonded interaction parameters. [Pg.241]

OPES (Optimized Potentials for Liquid Simulations) is based on a force field developed by the research group of Bill Jorgensen now at Yale University and previously at Purdue University. Like AMBER, the OPLS force field is designed for calculations on proteins and nucleic acids. It introduces nonbonded interaction parameters that have been carefully developed from extensive Monte Carlo liquid simulations of small molecules. These nonbonded interactions have been added to the bonding interactions of AMBERto produce anew force field that is expected to be better than AMBER at describing simulations where the solvent is explic-... [Pg.191]


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Interactive parameters

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