Molecular dynamics based descriptors for predicting supramolecular gelation

Ruben Van Lommel, Jianyu Zhao, Wim De Borggraeve, Frank De Proft, Mercedes Alonso Giner

Research output: Contribution to journalArticlepeer-review

22 Citations (Scopus)
137 Downloads (Pure)

Abstract

Whilst the field of supramolecular gels is rapidly moving towards complex materials and applications, their design is still an effortful and laborious trial-and-error process. Herein, we introduce four new descriptors that can be derived from all-atom molecular dynamics simulations and which are able to predict supramolecular gelation in both water and organic solvents. Their predictive ability was demonstrated via two separate machine learning techniques, a decision tree and an artificial neural network, with a dataset composed of urea-based gelators. Owing to the physical relevance of these descriptors to the supramolecular gelation process, their use could be conceptualized to other classes of supramolecular gelators and hence steer their design.
Original languageEnglish
Pages (from-to)4226-4238
Number of pages13
JournalChemical Science
Volume11
Issue number16
DOIs
Publication statusPublished - 28 Apr 2020

Bibliographical note

Funding Information:
The Strategic Research Program funding of the VUB is thanked for nancial support. F. D. P. also acknowledges the Francqui foundation for a position as “Francqui research professor”. R. V. L. thanks FWO for the PhD fellowship received (1185219N) and Jos L. Teunissen for valuable discussions. M. A. thanks the FWO for a postdoctoral fellowship (12F4416N) and the VUB for nancial support.

Funding Information:
Tier2 computational resources and services were provided by the Shared ICT Services Centre Funded by the Vrije Universiteit Brussel, the Flemish Supercomputer Center (VSC) and FWO. The Strategic Research Program funding of the VUB is thanked for financial support. F. D. P. also acknowledges the Francqui foundation for a position as “Francqui research professor”. R. V. L. thanks FWO for the PhD fellowship received (1185219N) and Jos L. Teunissen for valuable discussions. M. A. thanks the FWO for a postdoctoral fellowship (12F4416N) and the VUB for financial support.

Publisher Copyright:
© The Royal Society of Chemistry 2020.

Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.

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