Development and Application of a Coarse-Grained Model for PNIPAM by Iterative Boltzmann Inversion and Its Combination with Lattice Boltzmann Hydrodynamics

Abstract

The polymer (PNIPAM) is studied using a novel combination of multiscale modeling methodologies. We develop an iterative Boltzmann inversion potential of concentrated PNIPAM solutions and combine it with Lattice Boltzmann as a Navier Stokes equation solver for the solvent. We study in detail the inuence of the methodology on statics and dynamics of the system. The combination is successful and signicantly simpler and faster than other mapping techniques for polymer solution while keeping the correct hydrodynamics. The model can semiquantitatively describe the correct phase behavior and polymer dynamics.

Machine-Learning Enabled New Insights into the Coil-to-Globule Transition of Thermosensitive Polymers Using a Coarse-Grained Model

“…As shown in Figure 3d, the dihedral angles in our CG models are highly correlated for long times, which suggests that the tacticity of PNIPAM chains is retained, similar to that of AA models and experiments. 34 To the best of our knowledge, this is the first temperature-independent CG model of PNIPAM, a thermosensitive polymer, that can maintain its tacticity. This can be attributed to the presence of dihedral angles and stiffer angle force constants for C2M− C2M−C2M and C2M−C2M−AMP beads in the PNIPAM backbone.…”

“…49 Recently, Botan et al used an autocorrelation function (ACF) of a dihedral angle (ACF = ⟨cos(Θ(t) − Θ(t + dτ))⟩, with Θ being the dihedral angle at time t to demonstrate that, for an AA model of PNIPAM chain, the tacticity is retained. 34 Moreover, they also show that retaining such tacticity in a CG model is a very challenging task. To evaluate the ability of the newly developed PNIPAM CG model in retaining its tacticity and to further explain the differences observed in the LCST of PNIPAM, we used the ACF defined by Botan et al The tacticity of the backbone dihedral angle (AMP−C2M−C2M− AMP) (see Figure 1b) for the three CG PNIPAM chains, P1, P2, and P3 at two temperatures, 290 and 320 K was determined.…”

“…34 Additionally, (iv) the CG MD simulations utilized the implicit water model. 34 Hence, none of these models can capture the polymer−water and polymer−polymer interactions accurately. 19 Here, we present a novel computational framework that integrates CG MD simulations and data-driven machinelearning methods to gain insights into conformations of polymers in solution.…”

Large-scale simulation of biomembranes incorporating realistic kinetics into coarse-grained models

“…But this approach fails when multiple timescales are present and can therefore not improve our ability to predict mechanisms, as it preserves the relative order between timescales. An alternative is to use a simplified coarse-grained explicit solvent 26,27 , or to use the lattice Boltzmann method to couple particle motions to a grid-based numerical solution of fluid dynamics 28 . Both approaches limit the accessible time-and lengthscales, due to additional computations necessary for the fluid response.…”

Large-scale simulation of biomembranes: bringing realistic kinetics to coarse-grained models

“…An alternative is to replace all-atom solvent by a simplified coarse-grained explicit solvent [9,10,41,42], or to use the lattice Boltzmann method to couple particle motions to a grid-based numerical solution of fluid dynamics [43,44]. Both approaches limit the accessible time-and length-scales, due to additional computations necessary for the fluid response.…”