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Computational prediction of the molecular configuration of three-dimensional network polymers

Nature Materials volume 20, pages 1422–1430 (2021)Cite this article

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Abstract

The three-dimensional arrangement of natural and synthetic network materials determines their application range. Control over the real-time incorporation of each building block and functional group is desired to regulate the macroscopic properties of the material from the molecular level onwards. Here we report an approach combining kinetic Monte Carlo and molecular dynamics simulations that chemically and physically predicts the interactions between building blocks in time and in space for the entire formation process of three-dimensional networks. This framework takes into account variations in inter- and intramolecular chemical reactivity, diffusivity, segmental compositions, branch/network point locations and defects. From the kinetic and three-dimensional structural information gathered, we construct structure–property relationships based on molecular descriptors such as pore size or dangling chain distribution and differentiate ideal from non-ideal structural elements. We validate such relationships by synthesizing organosilica, epoxy–amine and Diels–Alder networks with tailored properties and functions, further demonstrating the broad applicability of the platform.

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Fig. 1: Network materials in decreasing order of their 3D structural configuration.
Fig. 2: Concepts of the framework exemplified for organosilica synthesis using TEOS; matrix-based kMC and MD simulations are interconnected to visualize the incorporation, building block by building block, of each FG at any t.
Fig. 3: Framework application for organosilica network synthesis with TEOS.
Fig. 4: Structure–property relationships for two network chemistries other than the organosilica case.
Fig. 5: Relevance of non-idealities for 3D Diels–Alder-based network structures (chemistry 3).

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Data availability

Source data are provided with this paper. The remaining data that support the findings of this study are included within the manuscript and its supplementary files and available from the corresponding authors upon request.

Code availability

The software used to access the molecular configuration of 3D network polymers in this paper is freely accessible via https://lammps.sandia.gov. Representative input and processing scripts are available at https://github.com/ldkeer/NatMater_dekeer_2021.

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Acknowledgements

L.D.K. acknowledges the research foundation Flanders (FWO; 1S37517N). P.H.M.V.S. and L.D. acknowledge FWO through a postdoctoral fellowship (12C4319N and 12ZR520N). D.R.D acknowledges FWO through G.0H52.16N and Flemish Government and Flanders Innovation & Entrepreneurship (Vlaio) through the Moonshot project P2C (HBC.2019.0114). The computational resources (Stevin Supercomputer Infrastructure) and services used in this work were provided by the Flemish Supercomputer Center, funded by Ghent University, FWO and the Flemish Government, department Economics, Science and Innovation (EWI). The work at Stanford University was supported by the US Department of Energy, Office of Basic Energy Sciences, under contract no. DE-FG02-07ER46391. C.B.-K. acknowledges an Australian Research Council Laureate Fellowship enabling his photochemical research programme as well as the Queensland University of Technology for key support. H.F. acknowledges Australian Research Council funding through a Discovery Early Career Researcher Award (DE200101096). We thank E. Loccufier for discussion regarding the interpretation of the experimental data for the membrane filtration. We thank J. Pelloth for carefully conducting initial kinetic experiments on the Diels–Alder chemistry.

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Authors and Affiliations

  1. Laboratory for Chemical Technology (LCT), Ghent University, Ghent, Belgium

    Lies De Keer, Paul H. M. Van Steenberge, Marie-Françoise Reyniers & Dagmar R. D’hooge

  2. Department of Materials Science and Engineering, Stanford University, Stanford, CA, USA

    Karsu I. Kilic & Reinhold H. Dauskardt

  3. Centre for Textile Science and Engineering (CTSE), Ghent University, Ghent, Belgium

    Lode Daelemans, Karen De Clerck & Dagmar R. D’hooge

  4. Centre for Materials Science, School of Chemistry and Physics, Queensland University of Technology (QUT), Brisbane, Queensland, Australia

    Daniel Kodura, Hendrik Frisch & Christopher Barner-Kowollik

  5. Institute of Nanotechnology (INT), Karlsruhe Institute of Technology (KIT), Eggenstein-Leopoldshafen, Germany

    Christopher Barner-Kowollik

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Contributions

L.D.K, P.H.M.V.S and D.R.D. contributed to the development of matrix-based kMC simulations for network synthesis. L.D.K, P.H.M.V.S., M.-F.R. and D.R.D. focused on the determination of the scale-dependent model parameters of the kMC simulations and contributed to the construction of the associated structure–property relationships. D.R.D. developed the overall framework of the connection of kMC and MD simulations. K.I.K. and R.H.D. contributed to part of the MD simulations and interpretation, as well as the construction of the structure–property relationship for the organosilica case. L.D. and K.D.C. contributed to the experimental part concerning the epoxy–amine curing and the construction of the related structure–property relationship. D.K., H.F. and C.B.-K. conceptualized and conducted the experimental part concerning the Diels–Alder chemistry and the construction of the related structure–property relationships. All authors approved the manuscript and made revisions during its preparation.

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Correspondence to Reinhold H. Dauskardt or Dagmar R. D’hooge.

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Peer review information Nature Materials thanks Simon Harrisson, Philippe Zinck and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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De Keer, L., Kilic, K.I., Van Steenberge, P.H.M. et al. Computational prediction of the molecular configuration of three-dimensional network polymers. Nat. Mater. 20, 1422–1430 (2021). https://doi.org/10.1038/s41563-021-01040-0

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