Skip to main content

Many-body potential for simulating the self-assembly of polymer-grafted nanoparticles in a polymer matrix

Publication ,  Journal Article
Zhou, Y; Bore, SL; Tao, AR; Paesani, F; Arya, G
Published in: npj Computational Materials
December 1, 2023

Many-body interactions between polymer-grafted nanoparticles (NPs) play a key role in promoting their assembly into low-dimensional structures within polymer melts, even when the particles are spherical and isotropically grafted. However, capturing such interactions in simulations of NP assembly is very challenging because explicit modeling of the polymer grafts and melt chains is highly computationally expensive, even using coarse-grained models. Here, we develop a many-body potential for describing the effective interactions between spherical polymer-grafted NPs in a polymer matrix through a machine-learning approach. The approach involves using permutationally invariant polynomials to fit two- and three-body interactions derived from the potential of mean force calculations. The potential developed here reduces the computational cost by several orders of magnitude, thereby, allowing us to explore assembly behavior over large length and time scales. We show that the potential not only reproduces previously known assembled phases such as 1D strings and 2D hexagonal sheets, which generally cannot be achieved using isotropic two-body potentials, but can also help discover interesting phases such as networks, clusters, and gels. We demonstrate how each of these assembly morphologies intrinsically arises from a competition between two- and three-body interactions. Our approach for deriving many-body effective potentials can be readily extended to other colloidal systems, enabling researchers to make accurate predictions of their behavior and dissect the role of individual interaction energy terms of the overall potential in the observed behavior.

Duke Scholars

Altmetric Attention Stats
Dimensions Citation Stats

Published In

npj Computational Materials

DOI

EISSN

2057-3960

Publication Date

December 1, 2023

Volume

9

Issue

1

Related Subject Headings

  • 5104 Condensed matter physics
  • 4016 Materials engineering
  • 3407 Theoretical and computational chemistry
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Zhou, Y., Bore, S. L., Tao, A. R., Paesani, F., & Arya, G. (2023). Many-body potential for simulating the self-assembly of polymer-grafted nanoparticles in a polymer matrix. Npj Computational Materials, 9(1). https://doi.org/10.1038/s41524-023-01166-6
Zhou, Y., S. L. Bore, A. R. Tao, F. Paesani, and G. Arya. “Many-body potential for simulating the self-assembly of polymer-grafted nanoparticles in a polymer matrix.” Npj Computational Materials 9, no. 1 (December 1, 2023). https://doi.org/10.1038/s41524-023-01166-6.
Zhou Y, Bore SL, Tao AR, Paesani F, Arya G. Many-body potential for simulating the self-assembly of polymer-grafted nanoparticles in a polymer matrix. npj Computational Materials. 2023 Dec 1;9(1).
Zhou, Y., et al. “Many-body potential for simulating the self-assembly of polymer-grafted nanoparticles in a polymer matrix.” Npj Computational Materials, vol. 9, no. 1, Dec. 2023. Scopus, doi:10.1038/s41524-023-01166-6.
Zhou Y, Bore SL, Tao AR, Paesani F, Arya G. Many-body potential for simulating the self-assembly of polymer-grafted nanoparticles in a polymer matrix. npj Computational Materials. 2023 Dec 1;9(1).

Published In

npj Computational Materials

DOI

EISSN

2057-3960

Publication Date

December 1, 2023

Volume

9

Issue

1

Related Subject Headings

  • 5104 Condensed matter physics
  • 4016 Materials engineering
  • 3407 Theoretical and computational chemistry