| People | Locations | Statistics |
|---|---|---|
| Naji, M. |
| |
| Motta, Antonella |
| |
| Aletan, Dirar |
| |
| Mohamed, Tarek |
| |
| Ertürk, Emre |
| |
| Taccardi, Nicola |
| |
| Kononenko, Denys |
| |
| Petrov, R. H. | Madrid |
|
| Alshaaer, Mazen | Brussels |
|
| Bih, L. |
| |
| Casati, R. |
| |
| Muller, Hermance |
| |
| Kočí, Jan | Prague |
|
| Šuljagić, Marija |
| |
| Kalteremidou, Kalliopi-Artemi | Brussels |
|
| Azam, Siraj |
| |
| Ospanova, Alyiya |
| |
| Blanpain, Bart |
| |
| Ali, M. A. |
| |
| Popa, V. |
| |
| Rančić, M. |
| |
| Ollier, Nadège |
| |
| Azevedo, Nuno Monteiro |
| |
| Landes, Michael |
| |
| Rignanese, Gian-Marco |
|
Van Steenberge, Paul
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (21/21 displayed)
- 2024Impact of rubber content on average properties and distributions of high impact polystyrene by means of multiphase coupled matrix-based Monte Carlo
- 2024Surfactant-free peroxidase-mediated enzymatic polymerization of a biorenewable butyrolactone monomer via a green approach : synthesis of sustainable biobased latexescitations
- 2024Combining ternary phase diagrams and multiphase coupled matrix-based Monte Carlo to model phase dependent compositional and molar mass variations in high impact polystyrene synthesiscitations
- 2024Exploring the influence of polybutadiene content on high-impact polystyrene properties : a multiphase coupled matrix-based Monte Carlo approach
- 2023Surfactant-Free Peroxidase-Mediated Enzymatic Polymerization of a Biorenewable Butyrolactone Monomer via a Green Approach: Synthesis of Sustainable Biobased Latexes
- 2023Multi-angle evaluation of kinetic Monte-Carlo simulations as a tool to evaluate the distributed monomer composition in gradient copolymer synthesiscitations
- 2023Bayesian tuned kinetic Monte Carlo modeling of polystyrene pyrolysis : unraveling the pathways to its monomer, dimers, and trimers formationcitations
- 2023Bayesian tuned kinetic Monte Carlo modeling of polystyrene pyrolysis : unraveling the pathways to its monomer, dimers, and trimers formationcitations
- 2023Playing with process conditions to increase the industrial sustainability of poly(lactic acid)-based materialscitations
- 2023Comparing thermal degradation for fused filament fabrication (FFF) with chain or step-growth polymers
- 2022Identifying optimal synthesis protocols via the in silico characterization of (a)symmetric block and gradient copolymers with linear and branched chains
- 2022A unified kinetic Monte Carlo approach to evaluate (a)symmetric block and gradient copolymers with linear and branched chains illustrated for poly(2-oxazoline)scitations
- 2020Connecting polymer synthesis and chemical recycling on a chain-by-chain basis : a unified matrix-based kinetic Monte Carlo strategycitations
- 2020Progress in reaction mechanisms and reactor technologies for thermochemical recycling of poly(methyl methacrylate)citations
- 2019The relevance of multi‐injection and temperature profiles to design multi‐phase reactive processing of polyolefinscitations
- 2017How penultimate monomer unit effects and initiator choice influence ICAR ATRP of n-butyl acrylate and methyl methacrylatecitations
- 2015Model-based visualization and understanding of monomer sequence formation in the synthesis of gradient copoly(2-oxazoline)s on the basis of 2-methyl-2-oxazoline and 2-phenyl-2-oxazolinecitations
- 2015Model-based design of the polymer microstructure : bridging the gap between polymer chemistry and engineering
- 2015Model-based design of the polymer microstructure: bridging the gap between polymer chemistry and engineeringcitations
- 2014Fed-batch control and visualization of monomer sequences of individual ICAR ATRP gradient copolymer chainscitations
- 2012Linear gradient quality of ATRP copolymerscitations
Places of action
| Organizations | Location | People |
|---|
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
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.