Computational evidence for anomalous diffusion of small molecules in amorphous polymers

Müller‐Plathe, Florian; Rogers, Stephen C.; Gunsteren, Wilfred F. van

doi:10.1016/0009-2614(92)80112-o

Cited by 157 publications

(102 citation statements)

References 20 publications

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“…The diffusion coefficient for model A is 24.09 lom6 cm2/s and 25.25 cm2/s for model B. Both diffusion coefficients are close to the value found by Muller-Plathe et al [2] (30.1 loe6 cm2/s) this is due to the fact we are using the same forcefield. Most importantly the diffusion coefficients differences between systems A and B are not significant.…”

supporting

confidence: 88%

“…The functional forms of the energy terms and their associated parameters is called a forcefield. In the present study, we are making use of the commercially available CHARMm forcefield [ 11, as well as forcefield parameters taken from Muller-Plathe et al [2] Molecular mechanics and molecular dynamics. Molecular mechanics is the procedure by which one locates local minima of energy.…”

Section: Methodsmentioning

confidence: 99%

“…The polymer used in this study was poly(isobutylene), or PIB, this polymer is enssentially an non cross-linked butyl rubber. The (full-atom) forcefield parameters were taken from Muller-Plathe et al [2] The Lorenz-Berthelot mixing rules were used for nonbond interactions between different atomic species, and all studies were performed at 300K.…”

Section: Butyl Rubbermentioning

confidence: 99%

“…We studied the diffusion of helium (He) through each of the polymer models, using the Lennard-Jones parameters given by Muller-Plathe et al [2] for He. In the case of Sample A, a polymer configuration with a density of exactly 0.91 &m3 was taken from the end of the second-stage runs.…”

mentioning

confidence: 99%

See 3 more Smart Citations

Massively parallel simulations of diffusion in dense polymeric structures

Faulon

Hobbs

Ford

et al. 1997

Proceedings of the 1997 ACM/IEEE Conference on Supercomputing (CDROM) - Supercomputing '97

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supporting

confidence: 88%

Section: Methodsmentioning

confidence: 99%

Section: Butyl Rubbermentioning

confidence: 99%

mentioning

confidence: 99%

See 2 more Smart Citations

Massively parallel simulations of diffusion in dense polymeric structures

Faulon

Hobbs

Ford

et al. 1997

Proceedings of the 1997 ACM/IEEE Conference on Supercomputing (CDROM) - Supercomputing '97

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“…2,3 For a complex system, however, an anomalous diffusion process with a sub-linear relation of ∆r(t) 2 ∼ D α t α is often observed at the intermediate time regime, where D α is a fractional diffusion coefficient. [2][3][4][5][6] If α > 1, e.g. a ballistic diffusion at a short-time regime, it is referred a Electronic mail: ccchiu2@mail.ncku.edu.tw.…”

Section: Introductionmentioning

confidence: 99%

Generic parameters of trajectory-extending kinetic Monte Carlo for calculating diffusion coefficients

Tien

Chiu

2018

AIP Advances

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One of the challenging applications of molecular dynamics (MD) simulations is to determine the dynamic properties such as the diffusion coefficient of the molecule of interest, particularly slow dynamic systems such as hydrogels and polymer melts. Recently, Neyertz et al. proposed a trajectory- extending kinetic Monte Carlo (TEKMC) algorithm combining both MD and kinetic Monte Carlo to probe the penetrant diffusion within the glassy polymer systems (S. Neyertz and D. Brown, Macromolecules 43, 9210, 2010). Yet, the original TEKMC relies on the manual adjustments of the key parameters of the sampling interval τ and the discretizing grid size rgrid, which limits its applicability to systems with unknown kinetic properties. Here, we reviewed the theoretical background of kinetic Monte Carlo to establish the generic criteria for selecting TEKMC parameters. Also, we modified and expanded the TEKMC algorithm for bulk fluid systems. The modified TEKMC algorithm were applied to systems with various kinetic properties, including Lennard Jones liquid, bulk water, Li+ liquid electrolyte, and Li+ polymer electrolyte. The diffusion coefficients obtained from the modified TEKMC and the generic parameter selections were promising and robust compared with the conventional MD results. With the proposed TEKMC approach, one can extend the MD trajectories to unambiguously characterize the diffusion behavior in the long-time diffusive regime.

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Transport Properties

Koros¹,

Madden²

2004

Encyclopedia of Polymer Science and Technology

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This article covers the transport properties of gases, low activity vapors, and intermediate‐sized penetrants through rubbery, semicrystalline, and glassy polymers. The article emphasizes polymer transport properties under conditions of low to intermediate penetrant concentration where extraordinary differences can exist between the diffusivities of penetrants having relatively small differences in molecular size or shape. Nonideal transport effects, such as plasticization, clustering, and non‐Fickian transport, are covered. Particular attention is given to the nonequilibrium nature of glassy polymers and the resulting effects on penetrant transport. The recent development of positron annihilation lifetime spectroscopy (PALS) and molecular modeling of diffusion are described. Transport through porous polymers and reptation of macromolecules within a macromolecular matrix are not covered in this article.

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Computational evidence for anomalous diffusion of small molecules in amorphous polymers

Cited by 157 publications

References 20 publications

Massively parallel simulations of diffusion in dense polymeric structures

Massively parallel simulations of diffusion in dense polymeric structures

Generic parameters of trajectory-extending kinetic Monte Carlo for calculating diffusion coefficients

Transport Properties

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