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Computer simulations polymers

Fig. 12.36 Capillary viscosity data and Sabia equation fit. [Reprinted by permission from H. Mavridis and R. N. Shroff, Multilayer Extrusion Experiments and Computer Simulation, Polym. Eng. Sci., 34, 559 (1994).]... Fig. 12.36 Capillary viscosity data and Sabia equation fit. [Reprinted by permission from H. Mavridis and R. N. Shroff, Multilayer Extrusion Experiments and Computer Simulation, Polym. Eng. Sci., 34, 559 (1994).]...
Gus kova, O.A., Pavlov, A.S., Khalatur, P.G. Complexes based on rigid-chain polyelectrolytes computer simulation. Polym. Sci. Ser. A 48(7), 763-770 (2006) Narambuena, C.F., Leiva, E.P.M., Chavez-Paez, M., Perez, E. Effect of chain stiffness on the morphology of polyelectrolyte complexes. A Monte Carlo simulation study. Polymer 51, 3293-3302 (2010)... [Pg.295]

In this section we look briefly at the problem of including quantum mechanical effects in computer simulations. We shall only examine tire simplest technique, which exploits an isomorphism between a quantum system of atoms and a classical system of ring polymers, each of which represents a path integral of the kind discussed in [193]. For more details on work in this area, see [22, 194] and particularly [195, 196, 197]. [Pg.2272]

Kremer K 1996 Computer simulation methods for polymer physics Monte Carlo and Molecular Dynamics of Condensed Matter Systems vol 49, ed K Binder and G Ciccotti (Bologna Italian Physical Society) pp 669-723... [Pg.2280]

Muller M, Wittmer J P and Cates M E 1996 Topological effects in ring polymers a computer simulation study Phys. Rev. E 53 5063... [Pg.2384]

Otlier expressions for tire diffusion coefficient are based on tire concept of free volume [57], i.e. tire amount of volume in tire sample tliat is not occupied by tire polymer molecules. Computer simulations have also been used to quantify tire mobility of small molecules in polymers [58]. In a first approach, tire partition functions of tire ground... [Pg.2536]

The complexity of polymeric systems make tire development of an analytical model to predict tlieir stmctural and dynamical properties difficult. Therefore, numerical computer simulations of polymers are widely used to bridge tire gap between tire tlieoretical concepts and the experimental results. Computer simulations can also help tire prediction of material properties and provide detailed insights into tire behaviour of polymer systems. A simulation is based on two elements a more or less detailed model of tire polymer and a related force field which allows tire calculation of tire energy and tire motion of tire system using molecular mechanisms, molecular dynamics, or Monte Carlo teclmiques 1631. [Pg.2537]

An area of great interest in the polymer chemistry field is structure-activity relationships. In the simplest form, these can be qualitative descriptions, such as the observation that branched polymers are more biodegradable than straight-chain polymers. Computational simulations are more often directed toward the quantitative prediction of properties, such as the tensile strength of the bulk material. [Pg.308]

Computational Modeling of Polymers J. Bicerano, Ed., Dekker, new York (1992). Computer Simulation of Polymers E. A. Coulbourne, Ed., Longman-Harlow, London (1992). [Pg.316]

Computer Simulation of Polymers R. J. Roe, Ed., Prentice Hall, New York (1991). [Pg.316]

Due to the complexity of macromolecular materials computer simulations become increasingly important in polymer science or, better, in what is now called soft matter physics. There are several reviews available which deal with a great variety of problems and techniques [1-7]. It is the purpose of the present introduction to give a very brief overview of the different approaches, mainly for dense systems, and a few apphcations. To do so we will confine ourselves to techniques describing polymers on a molecular level. By molecular level we mean both the microscopic and the mesoscopic level of description. In the case of the microscopic description (all)... [Pg.481]

Another important characteristic aspect of systems near the glass transition is the time-temperature superposition principle [23,34,45,46]. This simply means that suitably scaled data should all fall on one common curve independent of temperature, chain length, and time. Such generahzed functions which are, for example, known as generalized spin autocorrelation functions from spin glasses can also be defined from computer simulation of polymers. Typical quantities for instance are the autocorrelation function of the end-to-end distance or radius of gyration Rq of a polymer chain in a suitably normalized manner ... [Pg.504]


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