Modeling oil paint network formation

Authors

  • Jorien Duivenvoorden University of Amsterdam

DOI:

https://doi.org/10.25609/sure.v1.1035

Abstract

Polymerized oil paint is a strongly cross-linked network and analysis of the molecular topology is practically impossible. Insight in the structure is crucial to explain several degradation processes. In this study an advanced model, based on kinetic Monte Carlo and graph theory, is developed that simulates the formation of an oil paint network and provides the desired structural information. The basic assumption is that the reactivity of the monomers depends on their ability to form cross-links. The addition of three novel routines makes the model approach a real chemical system more accurately. Furthermore, an experimental validation of the model is discussed.

Author Biography

Jorien Duivenvoorden, University of Amsterdam

Van ‘t Hoff Institute for Molecular Science

References

Van den Berg, J., Van den Berg, K., Boon, J.

Determination of the degree of hydrolysis of oil paint

samples using a two-step derivatisation method and

on-column GC/MS. Progress in Organic Coatings, 41

, 143-155.

Geldof, M. Finding the suspect of the discolouration

of the floor.

http://slaapkamergeheimen.vangoghmuseum.nl/catego

ry/collaboration/?lang=en

Hamzehlou, S., Reyes, Y., Leiza, J.R. A new insight

into the formation of polymer networks: a kinetic

monte carlo simulation of the cross-linking

polymerization of s/dvb. Macromolecules, 46 (2013),

-9073

Soucek, M. D., Khattab, T., Wu, J. Review of

autoxidation and driers. Progress in Organic

Coatings, 73 (2012), 435-454.

Van Gorkum, R., Bouwman, E. The oxidative drying

of alkyd paint catalysed by metal

complexes. Coordination Chemistry Reviews, 249

(2005), 1709-1728.

Mastan, E., Zhu, S. Method of moments: A versatile

tool for deterministic modeling of polymerization

kinetics. European Polymer Journal, 68 (2015), 139-

Kryven, I., Iedema, P. D. Transition into the gel

regime for free radical crosslinking polymerisation in

a batch reactor. Polymer, 55 (2014), 3475-3489.

Kryven, I., Iedema, P. D. Topology evolution in

polymer modification. Macromolecular Theory and

Simulations, 23 (2014), 7-14.

Rapaport, D. C. The art of molecular dynamics

simulation. Cambridge University Press, Cambridge,

UK, 2004.

Gillespie, D.T. A general method for numerically

simulating the stochastic time evolution of coupled

chemical reactions. Journal of computational physics,

(1976), 403-434

Dušek, K.; Gordon, M.; Ross-Murphy, S.B. Graphlike

state of matter 10. Cyclization and concentration of

elastically active network chains in polymer networks.

Macromolecules, 11 (1978), 236-245.

White, B. Math 51 lecture notes: How Google ranks

web pages.

http://web.stanford.edu/class/math51/PageRank.pdf

Chakraborty, J., Kumar, J., Singh, M., Mahoney, A.

W., Ramkrishna, D. Inverse Problems in Population

Balances. Determination of Aggregation Kernel by

Weighted Residuals. Industrial & Engineering

Chemistry Research (2015)

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Published

2015-11-20

How to Cite

Duivenvoorden, J. (2015). Modeling oil paint network formation. Student Undergraduate Research E-Journal!, 1. https://doi.org/10.25609/sure.v1.1035

Issue

Section

Economics & Social Sciences