Population balance approach for predicting polymer particles morphology

Simone Rusconi (1) , Denys Dutykh (2, 3, 4) , Arghir Zarnescu (1, 5, 6) , Dmitri Sokolovski (6) , Elena Akhmatskaya (6, 1)

1 BCAM - Basque Center for Applied Mathematics
2 LAMA - Laboratoire de Mathématiques
3 INSMI-CNRS - Institut National des Sciences Mathématiques et de leurs Interactions - CNRS Mathématiques
4 USMB [Université de Savoie] [Université de Chambéry] - Université Savoie Mont Blanc
5 IMAR - "Simion Stoilow" Institute of Mathematics
6 Ikerbasque - Basque Foundation for Science

Polymer particles morphology can be defined as a pattern of phase-separated domains comprising a multi-phase polymer particle [1]. Properties of a polymer particle strongly depend on its morphology, and thus the control of particle morphology is a key factor for success in producing high-quality polymers materials, such as coatings, adhesives and additives [2]. Currently, an accurate prediction of particles morphology is still a challenge due to its complexity. Several modelling approaches, describing the dynamics of the morphology of a single particle, have been suggested in the last few years [3, 4, 5]. However, the single-particle approaches only provide a partial view of realistic systems, containing millions of particles. Furthermore, such models are computationally demanding even with the use of High-Performance Computers.

Domaines: Mécanique des fluides [physics.class-ph]; Dynamique des Fluides [physics.flu-dyn]; Physique Numérique [physics.comp-ph]; Chimie-Physique [physics.chem-ph]; Physique Classique [physics.class-ph]; Analyse numérique [math.NA]; Analyse numérique [cs.NA]

Simone Rusconi, Denys Dutykh, Arghir Zarnescu, Dmitri Sokolovski, Elena Akhmatskaya. Population balance approach for predicting polymer particles morphology. The 11th Conference on Dynamical Systems Applied to Biology and Natural Sciences (DSABNS), Feb 2020, Trento, Italy. ⟨hal-02518323⟩