A Monte Carlo study of the glass transition in three-dimensional polymer melts

Wittkop, M.; Hölzl, Th.; Kreitmeier, Stefan; Göritz, D.

doi:10.1016/0022-3093(96)00141-x

Cited by 17 publications

(22 citation statements)

References 81 publications

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“…In order to introduce energy in the model two potentials are employed. First, a truncated Lennard-Jones potential calculated up to a distance of four lattice cells which represents intermolecular interactions: [24]…”

Section: Bond Fluctuation Modelmentioning

confidence: 99%

“…and a bond length potential representing interactions between monomeric groups and their preferred distances: [5,24] UðlÞ…”

Section: Bond Fluctuation Modelmentioning

confidence: 99%

“…[4][5][6][7][8][9][10][11] The bond fluctuation model (BFM) [5,[12][13][14] is a lattice model which has shown its utility to simulate the glass transition before. [5,[15][16][17][18][19][20][21][22] In spite of the presence of a lattice, the model allows a great variety of molecular chain configurations, which is one of the main hazards of lattice models. In a previous work we have shown the ability of BFM to reproduce the main features of the glass transition and physical aging processes in polymer systems in response to different thermal histories, provided the balance between inter-and intra-molecular potentials is adequate.…”

Section: Introductionmentioning

confidence: 99%

“…This problem is particularly difficult in the models where the volume of the lattice remains constant. [24][25][26] Glass transition has been observed by means of some of these definitions of ''free volume'' in BFM [23,24] but all of them take into account the empty cells without minding about the real probability of an empty cell to be occupied by a monomer.…”

Section: Introductionmentioning

confidence: 99%

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A Definition of Dynamically Accessible Volume for Thermal Systems

Molina‐Mateo

Dueñas

Ribelles

2005

Macro Theory & Simulations

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Summary: The glass transition and physical aging processes of a polymeric material have been simulated using the bond fluctuation model. Two potentials that represent intra‐ and inter‐molecular interactions have been employed. Simulations of different thermal histories that include cooling from equilibrium have been performed. The evolution of the system and the structure attained at low temperature are analyzed as a function of the assumed weight of inter‐ and intra‐molecular potentials in the total energy of the system. A new way of characterizing the free volume of the system and its evolution with the temperature or time is proposed. It is based on the concept of dynamically accessible volume but modified in the sense of considering the probability of an empty site to be accessed according to a Metropolis criterion. The results obtained show that the thermal redefinition of the dynamically accessible volume, TDAV, offers a better representation of the real mobility of the polymeric systems. The use of information on the structure of the system coming from the pair‐correlation function and the molecular mobility in the glassy state characterized by the time evolution of TDAV allows to reach the conclusion that a combination of inter‐ and intra‐molecular potentials produces the vitrification of the polymer system on cooling.

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Section: Bond Fluctuation Modelmentioning

confidence: 99%

“…and a bond length potential representing interactions between monomeric groups and their preferred distances: [5,24] UðlÞ…”

Section: Bond Fluctuation Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A Definition of Dynamically Accessible Volume for Thermal Systems

Molina‐Mateo

Dueñas

Ribelles

2005

Macro Theory & Simulations

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“…Other commonly used methods for T g prediction are: ab initio quantum mechanical calculations [21,22], Monte Carlo [23,24], and molecular dynamics simulations [25][26][27][28][29] and semi-empirical or empirical methods based on group contribution methods, often using the QSPR approach through neural network computation [30][31][32][33][34][35][36][37][38][39][40][41][42][43][44]. While some of these methods yield good results by predicting glass transition temperatures with errors as good as 3-10 K, most predictive accuracies are on the order of 20-100K.…”

Section: Polymer Flexibility and T Gmentioning

confidence: 99%

Glass transition temperature prediction of polymers through the mass-per-flexible-bond principle

Schut

Bolikal

Khan

et al. 2007

Polymer

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A semi-empirical method based on the mass-per-flexible-bond (M/f) principle was used to quantitatively explain the large range of glass transition temperatures (T g ) observed in a library of 132 L-tyrosine derived homo, co-and terpolymers containing different functional groups. Polymer class specific behavior was observed in T g vs. M/f plots, and explained in terms of different densities, steric hindrances and intermolecular interactions of chemically distinct polymers. The method was found to be useful in the prediction of polymer T g . The predictive accuracy was found to range from 6.4 to 3.7 K, depending on polymer class. This level of accuracy compares favorably with (more complicated) methods used in the literature. The proposed method can also be used for structure prediction of polymers to match a target T g value, by keeping the thermal behavior of a terpolymer constant while independently choosing its chemistry. Both applications of the method are likely to have broad applications in polymer and (bio)material science.

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