Characterization of Morphology Evolution in a Polymer–Clay Nanocomposite Using Multiscale Simulations

Molecular simulations provide an effective route for investigating morphology evolution and the structure-property relationship in polymer-clay nanocomposites (PCNCs) incorporating layered silicates like montmorillonite (MMT), an important class of materials that show a significant enhancement over the constituent polymer for several properties. However, long relaxation times and large system size requirements limit their application to systems of practical interest. In this work, we developed a coarse-grained (CG) model of organically modified MMT (oMMT) compatible with the MARTINI force field, a chemically specific interaction model with high transferability. The dispersive and polar components of cleavage energy, basal spacing, and mechanical properties of MMT with tetramethylammonium (TMA) as intergallery ions were used to obtain a rational estimate for clay particle MARTINI bead types in accordance with the polarity of the functional group. The CG model provided accurate concurrent estimates for the structural, thermodynamic, and dynamical properties of polyethylene (PE) in a PE/TMA-MMT PCNC, with less than a 4% deviation from all atom (AA) simulations. The slow clay-induced redistribution of the polyethylene-polyethylene glycol block copolymer (PE-<i>b</i>-PEG) in the PCNCs was investigated using the developed CG model, with conformational changes occurring over a microsecond time scale. The preferential interaction coefficient and cluster analysis of individual blocks of PE-<i>b</i>-PEG were used to study the effect of clay arrangement (exfoliated vs tactoid) on copolymer reorientation and assembly at the clay surface. We find that the oMMT coated with PE-<i>b</i>-PEG acts as a neutral surface (small difference in polymer-polymer and polymer-oMMT + PE-<i>b</i>-PEG enthalpic interactions), and the primary influence of the nanofiller is a result of confinement and steric effect of the clay sheets on the PE chains. Finally, several different PCNC morphologies obtained from long CG simulations were backmapped to AA resolution for the accurate calculation of mechanical and physical properties. This work offers a computationally efficient multiscale simulation framework for the accurate determination of the morphology and mechanical performance of PCNCs, enabling a rational material design.

Authors

Institutions

Publication Details

Journal
Journal of Chemical Theory and Computation
Published
2025-08-12
DOI
https://doi.org/10.1021/acs.jctc.5c01004
Primary Topic
Polymer Nanocomposites and Properties
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Characterization of Morphology Evolution in a Polymer–Clay Nanocomposite Using Multiscale Simulations

Gaurav Goel, Parvez Khan, Ankit Patidar
1 links
Journal of Chemical Theory and Computation
Polymer Nanocomposites and Properties
article

Characterization of Morphology Evolution in a Polymer–Clay Nanocomposite Using Multiscale Simulations

Gaurav Goel, Parvez Khan, Ankit Patidar
article en

Abstract

Molecular simulations provide an effective route for investigating morphology evolution and the structure-property relationship in polymer-clay nanocomposites (PCNCs) incorporating layered silicates like montmorillonite (MMT), an important class of materials that show a significant enhancement over the constituent polymer for several properties. However, long relaxation times and large system size requirements limit their application to systems of practical interest. In this work, we developed a coarse-grained (CG) model of organically modified MMT (oMMT) compatible with the MARTINI force field, a chemically specific interaction model with high transferability. The dispersive and polar components of cleavage energy, basal spacing, and mechanical properties of MMT with tetramethylammonium (TMA) as intergallery ions were used to obtain a rational estimate for clay particle MARTINI bead types in accordance with the polarity of the functional group. The CG model provided accurate concurrent estimates for the structural, thermodynamic, and dynamical properties of polyethylene (PE) in a PE/TMA-MMT PCNC, with less than a 4% deviation from all atom (AA) simulations. The slow clay-induced redistribution of the polyethylene-polyethylene glycol block copolymer (PE-<i>b</i>-PEG) in the PCNCs was investigated using the developed CG model, with conformational changes occurring over a microsecond time scale. The preferential interaction coefficient and cluster analysis of individual blocks of PE-<i>b</i>-PEG were used to study the effect of clay arrangement (exfoliated vs tactoid) on copolymer reorientation and assembly at the clay surface. We find that the oMMT coated with PE-<i>b</i>-PEG acts as a neutral surface (small difference in polymer-polymer and polymer-oMMT + PE-<i>b</i>-PEG enthalpic interactions), and the primary influence of the nanofiller is a result of confinement and steric effect of the clay sheets on the PE chains. Finally, several different PCNC morphologies obtained from long CG simulations were backmapped to AA resolution for the accurate calculation of mechanical and physical properties. This work offers a computationally efficient multiscale simulation framework for the accurate determination of the morphology and mechanical performance of PCNCs, enabling a rational material design.

Journal of Chemical Theory and ComputationVol. 21(16)
Aligarh Muslim University (IN), Indian Institute of Technology Delhi (IN)
Openalex Percentile: Top 83%
Polymer Nanocomposites and Properties
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.