Dissipative particle dynamics simulations of end-cross-linked nanogels

ABSTRACT

Nanogels, due to their unique properties, have potential for promising applications in several fields. There is a growing interest in understanding which are the mechanisms controlling their properties, as those depend not only on composition but also on internal structure. In this work, dissipative particle dynamics simulations were applied to simulate the formation of nanogels from monodisperse end-functionalised polymer chains, with the cross-linking reaction modelled using a distance-based algorithm, including a reversible intermediate step. Nanogel properties are studied by calculating their swelling transition curves and structure properties, such as network defects and entanglement state. Various chain lengths, reaction schemes, nanogel in silico synthesis methods and solvent ratios are compared and discussed, showing how these factors influence the nanogel swelling behaviour and structure. Our results show that, in order to be compared with experiments, nanogel simulations should carefully consider processing parameters.

KEYWORDS:

• Nanogels
• swelling
• entanglement
• dissipative particle dynamics
• Network formation

Acknowledgments

The authors wish to thank Dr Dirk J. Dijkstra and Dr Piet J. Driest for the fruitful discussions and ideas, and Prof. Martin Kröger for kindly providing the Z1 code for primitive path analysis. This project has received funding from the European Union's Horizon 2020-Research and Innovation Framework Programme under the Marie Skłodowska-Curie Grant Agreement no. 642890 (http://thelink-project.eu/) and it was partially supported by the Portuguese Foundation for Science and Technology (FCT) in the framework of the Strategic Funding UIDB/04650/2020-2023, by the FCT grant SFRH/BD/128666/2017. The authors acknowledge FCT and the National Advanced Computing Network (RNCA) for providing HPC resources from cluster Bob at Minho Advanced Computing Center (MACC). Such resources have contributed to the research results reported within this paper. URL: https://www.fccn.pt/computacao/rnca and https://macc.fccn.pt

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This project has received funding from the European Union's Horizon 2020-Research and Innovation Framework Programme under the Marie Skłodowska-Curie Actions grant agreement no. 642890 (http://thelink-project.eu/) and it was partially supported by the Portuguese Foundation for Science and Technology (FCT) in the framework of the Strategic Funding UIDB/04650/2020-2023,SFRH/BD/128666/2017, by the FCT.