English

Mapping self-avoiding walk on obstacle-ridden lattice onto chelation of heavy metal ions: Monte Carlo study

Soft Condensed Matter 2024-12-10 v1 Disordered Systems and Neural Networks

Abstract

Self-avoiding walk (SAW) represents linear polymer chain on a large scale, neglecting its chemical details and emphasizing the role of its conformational statistics. The role of the latter is important in formation of agglomerates and complexes involving polymers and organic or inorganic particles, such as polymer-stabilized colloidal suspensions, microemulsions, or micellar solutions. When such particles can be adsorbed on a polymer of considerably larger dimensions than themselves, this setup may represent chelation of heavy metal ions by polymeric chelants. We consider the SAW of the length NN on a cubic lattice ridden by randomly distributed obstacles of the concentration pp interpreted as ions. The SAW monomers can bind to the obstacles with variable binding energy ε\varepsilon mimicking formation of the chelation bond. Pruned-enriched Rosenbluth method (PERM) Monte Carlo (MC) algorithm is applied to simulate system behaviour. We focus on several relevant properties related to the chelation efficiency and strength, as functions of the variables set {p,N,ε}\{p,N,\varepsilon\}. The results are interpreted in terms of conformational freedom, excluded volume effects and loop formation for the SAW, and the tendencies being predicted are in agreement with some experimental data.

Keywords

Cite

@article{arxiv.2409.10974,
  title  = {Mapping self-avoiding walk on obstacle-ridden lattice onto chelation of heavy metal ions: Monte Carlo study},
  author = {V. Blavatska and Ja. Ilnytskyi and E. Lähderanta},
  journal= {arXiv preprint arXiv:2409.10974},
  year   = {2024}
}