Lattice mean-field method for stationary polymer diffusion

被引:8
|
作者
Scheinhardt-Engels, SM [1 ]
Leermakers, FAM [1 ]
Fleer, GJ [1 ]
机构
[1] Univ Wageningen & Res Ctr, Lab Phys Chem & Colloid Sci, NL-6703 HB Wageningen, Netherlands
来源
PHYSICAL REVIEW E | 2003年 / 68卷 / 01期
关键词
D O I
10.1103/PhysRevE.68.011802
中图分类号
O35 [流体力学]; O53 [等离子体物理学];
学科分类号
070204 ; 080103 ; 080704 ;
摘要
We present a method to study mean-field stationary diffusion (MFSD) in polymer systems. When gradients in chemical potentials vanish, our method reduces to the Scheutjens-Fleer self-consistent field (SF-SCF) method for inhomogeneous polymer systems in equilibrium. To illustrate the concept of our MFSD method, we studied stationary diffusion between two different bulk mixtures, containing, for simplicity, noninteracting homopolymers. Four alternatives for the diffusion equation are implemented. These alternatives are based on two different theories for polymer diffusion (the slow- and fast-mode theories) and on two different ways to evaluate the driving forces for diffusion, one of which is in the spirit of the SF-SCF method. The diffusion profiles are primarily determined by the diffusion theory and they are less sensitive to the evaluation of the driving forces. The numerical stationary state results are in excellent agreement with analytical results, in spite of a minor inconsistency at the system boundaries in the numerical method. Our extension of the equilibrium SF method might be useful for the study of fluxes, steady state profiles and chain conformations in membranes (e.g., during drug delivery), and for many other systems for which simulation techniques are too time consuming.
引用
收藏
页数:15
相关论文
共 50 条
  • [1] The current method for stationary mean-field games on networks
    Gomes, Diogo A.
    Marcon, Diego
    Al Saleh, Fatimah
    2019 IEEE 58TH CONFERENCE ON DECISION AND CONTROL (CDC), 2019, : 305 - 310
  • [2] A mean-field lattice model for the diffusion-controlled aggregation
    Sakaguchi, H
    JOURNAL OF THE PHYSICAL SOCIETY OF JAPAN, 1999, 68 (01) : 61 - 63
  • [3] Mean-field lattice trees
    Christian Borgs
    Jennifer Chayes
    Remco van der Hofstad
    Gordon Slade
    Annals of Combinatorics, 1999, 3 (2-4) : 205 - 221
  • [4] Stationary focusing mean-field games
    Cirant, Marco
    COMMUNICATIONS IN PARTIAL DIFFERENTIAL EQUATIONS, 2016, 41 (08) : 1324 - 1346
  • [5] On the pressure in mean-field lattice models
    Oversteegen, SM
    Barneveld, PA
    Leermakers, FAM
    Lyklema, J
    LANGMUIR, 1999, 15 (25) : 8609 - 8617
  • [6] Reinforcement Learning in Stationary Mean-field Games
    Subramanian, Jayakumar
    Mahajan, Aditya
    AAMAS '19: PROCEEDINGS OF THE 18TH INTERNATIONAL CONFERENCE ON AUTONOMOUS AGENTS AND MULTIAGENT SYSTEMS, 2019, : 251 - 259
  • [7] Stationary mean-field games with logistic effects
    Gomes, Diogo Aguiar
    Ribeiro, Ricardo de Lima
    PARTIAL DIFFERENTIAL EQUATIONS AND APPLICATIONS, 2021, 2 (01):
  • [8] Stationary fully nonlinear mean-field games
    Andrade, Pedra D. S.
    Pimentel, Edgard A.
    JOURNAL D ANALYSE MATHEMATIQUE, 2021, 145 (01): : 335 - 356
  • [9] Stationary fully nonlinear mean-field games
    Pêdra D. S. Andrade
    Edgard A. Pimentel
    Journal d'Analyse Mathématique, 2021, 145 : 335 - 356
  • [10] Amplitude death with mean-field diffusion
    Sharma, Amit
    Shrimali, Manish Dev
    PHYSICAL REVIEW E, 2012, 85 (05):