Materials Map

Discover the materials research landscape. Find experts, partners, networks.

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The Materials Map is an open tool for improving networking and interdisciplinary exchange within materials research. It enables cross-database search for cooperation and network partners and discovering of the research landscape.

The dashboard provides detailed information about the selected scientist, e.g. publications. The dashboard can be filtered and shows the relationship to co-authors in different diagrams. In addition, a link is provided to find contact information.

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The Materials Map is still under development. In its current state, it is only based on one single data source and, thus, incomplete and contains duplicates. We are working on incorporating new open data sources like ORCID to improve the quality and the timeliness of our data. We will update Materials Map as soon as possible and kindly ask for your patience.

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in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (3/3 displayed)

  • 2023Multi-angle evaluation of kinetic Monte-Carlo simulations as a tool to evaluate the distributed monomer composition in gradient copolymer synthesis2citations
  • 2022Identifying optimal synthesis protocols via the in silico characterization of (a)symmetric block and gradient copolymers with linear and branched chainscitations
  • 2022A unified kinetic Monte Carlo approach to evaluate (a)symmetric block and gradient copolymers with linear and branched chains illustrated for poly(2-oxazoline)s16citations

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Van Steenberge, Paul
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Dhooge, Dagmar R.
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Hoogenboom, Richard
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Sedlacek, Ondrej
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Dhooge, Dagmar
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2023
2022

Co-Authors (by relevance)

  • Van Steenberge, Paul
  • Dhooge, Dagmar R.
  • Marien, Yoshi
  • Hoogenboom, Richard
  • Sedlacek, Ondrej
  • Dhooge, Dagmar
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article

A unified kinetic Monte Carlo approach to evaluate (a)symmetric block and gradient copolymers with linear and branched chains illustrated for poly(2-oxazoline)s

  • Van Steenberge, Paul
  • Sedlacek, Ondrej
  • Dhooge, Dagmar R.
  • Marien, Yoshi
  • Hoogenboom, Richard
  • Conka, Robert
Abstract

The synthesis of well-defined gradient, block-gradient and di-block copolymers with both asymmetric and symmetric compositions considering hydrophilic and hydrophobic monomer units is relevant for application fields, such as drug/gene delivery and (bio)compatibilization. The evaluation of the synthesis success and the resulting polymer structure remains however challenging, as ideally every chain needs to be considered, which is experimentally almost impossible. Matrix-based kinetic Monte Carlo (kMC) simulations provide a solution to this challenge, as they allow to visualize the monomer sequences of individual chains with reliable parameter tuning based on experimental data on average compositions and size exclusion chromatography. Here, such matrix-based kMC simulations are applied to visualize monomer sequences in polymers prepared by living cationic ring-opening polymerization (CROP) of 2-methyl-2-oxazoline (MeOx) and 2-phenyl-2-oxazoline (PhOx), uniquely differentiating between linear and branched chains. For the branched chains, a novel modeling protocol is presented allowing to evaluate their structural (here compositional) organization in a similar manner as linear chains by comparing arm pairs. This delivers an average compositional deviation for these branched species (SDBr) that in combination with the conventional deviation for linear chains (SDLin) and proper weighing with the mass fractions allows to obtain the overall SD. It is highlighted that di-block copolymer synthesis recipes most closely resemble the ideal target structure, benefiting from a semi-batch procedure. Such recipes allow to minimize the contribution of chain transfer to monomer and enable a more fluent transition of linear side products with bad composition in branched chains that by further growth can compensate for the compositional deviation. It is also demonstrated that reaching of the targeted structure is less trivial for a more symmetric composition and that (well-chosen) threshold SD values can be defined allowing to qualify synthesized copolymers as bad, good and excellent, at least for the guide of the eye. A sufficiently low dispersity is necessary to obtain a sufficiently high product quality, but as such is not a sufficient condition to evaluate the structural variation, highlighting the strength of the kMC framework for the identification of optimal synthesis protocols.

Topics
  • impedance spectroscopy
  • microstructure
  • simulation
  • laser emission spectroscopy
  • strength
  • copolymer
  • block copolymer
  • exclusion chromatography
  • gradient copolymer
  • weighing