Shear-induced ordering in systems with competing interactions: A machine learning study

J. Pȩkalski, W. Rządkowski, A. Z. Panagiotopoulos

Research output: Contribution to journalArticle

Abstract

When short-range attractions are combined with long-range repulsions in colloidal particle systems, complex microphases can emerge. Here, we study a system of isotropic particles, which can form lamellar structures or a disordered fluid phase when temperature is varied. We show that, at equilibrium, the lamellar structure crystallizes, while out of equilibrium, the system forms a variety of structures at different shear rates and temperatures above melting. The shear-induced ordering is analyzed by means of principal component analysis and artificial neural networks, which are applied to data of reduced dimensionality. Our results reveal the possibility of inducing ordering by shear, potentially providing a feasible route to the fabrication of ordered lamellar structures from isotropic particles.

Original languageEnglish (US)
Pages (from-to)204905
Number of pages1
JournalThe Journal of chemical physics
Volume152
Issue number20
DOIs
StatePublished - May 29 2020

All Science Journal Classification (ASJC) codes

  • Physics and Astronomy(all)
  • Physical and Theoretical Chemistry

Fingerprint Dive into the research topics of 'Shear-induced ordering in systems with competing interactions: A machine learning study'. Together they form a unique fingerprint.

  • Cite this