INS10-1017
Computational Framework for Analyzing Electrostatic and Electrokinetic Properties of Polyelectrolyte Solutions in Brush-Grafted Microchannels
Topic
S10. AI-assisted Design and Simulation of Polymers
When and Where
Sep 30, 2026
15:25 - 15:50
Room 109
Session Chairs
YongJoo Kim
Presenter(s)
Myung-Suk Chun (KIST & UST)
Co-Author(s)
Abstract
Brush-grafted narrow channels have the advantage of a tunable response to external stimuli, allowing us to use them in various applications, such as sensing, actuators, and current rectification [1,2]. On the basis of the continuum mechanics approach, we developed a computational model for long-range electrostatic and electrokinetic interactions of Newtonian simple fluids as well as polyelectrolyte solutions in brush-grafted microchannels. In this model framework, the Poisson-Nernst-Planck equations are explicitly solved for the electrostatic field incorporated with the Alexander-de Gennes model for polyelectrolyte brush-layer. Here, the Brinkman hydrodynamic friction is addressed inside, and each ion concentration can be estimated by multi-species ion balance. A rheological model of Bird-Carreau type [3] is applied in the Cauchy equation to describe the exemplar solution of anionic polyacrylic acid (PAA).
This talk presents the discriminating results regarding the quantitative effects of grafting properties in terms of grafting density, counter-ion condensation, and Kuhn length predicted by employing coarse-grained mesoscale simulations. The electrostatic potential increases with grafting density, whereas the surface potential decreases with increasing Kuhn length clearly unlike in the bulk. It is emphasized that the flow velocity decreases with either higher grafting density owing to enhanced PAA chain friction or larger Kuhn length according to higher flow retardation due to chain stiffness. The corresponding viscosity profile inside the channel is also examined with variations of pH and concentration of PAA dispersion. Furthermore, this study is expected to promote the design platform by machine learning approaches.
[1] S. Das, M. Banik, G. Chen, S. Sinha, R. Mukherjee, Soft Matter 11, 8550 (2015).
[2] J.O. Zoppe, N.C. Ataman, P. Mocny, J. Wang, J. Moraes, H.-A. Klok, Chem. Rev. 117, 1105 (2017).
[3] K. Yoon, H.W. Jung, M.-S. Chun, Rheol. Acta 56, 915 (2017).
This talk presents the discriminating results regarding the quantitative effects of grafting properties in terms of grafting density, counter-ion condensation, and Kuhn length predicted by employing coarse-grained mesoscale simulations. The electrostatic potential increases with grafting density, whereas the surface potential decreases with increasing Kuhn length clearly unlike in the bulk. It is emphasized that the flow velocity decreases with either higher grafting density owing to enhanced PAA chain friction or larger Kuhn length according to higher flow retardation due to chain stiffness. The corresponding viscosity profile inside the channel is also examined with variations of pH and concentration of PAA dispersion. Furthermore, this study is expected to promote the design platform by machine learning approaches.
[1] S. Das, M. Banik, G. Chen, S. Sinha, R. Mukherjee, Soft Matter 11, 8550 (2015).
[2] J.O. Zoppe, N.C. Ataman, P. Mocny, J. Wang, J. Moraes, H.-A. Klok, Chem. Rev. 117, 1105 (2017).
[3] K. Yoon, H.W. Jung, M.-S. Chun, Rheol. Acta 56, 915 (2017).
