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

TL;DR

This study models the chelation of heavy metal ions by polymers using self-avoiding walks on a lattice with obstacles, employing Monte Carlo simulations to analyze how binding and obstacle concentration affect chelation efficiency.

Contribution

It introduces a novel mapping of self-avoiding walks with obstacles onto chelation processes and applies advanced Monte Carlo methods to study their properties.

Findings

Chelation efficiency depends on obstacle concentration, chain length, and binding energy.

Conformational freedom and loop formation influence chelation strength.

Predictions align with some experimental data on polymer-metal interactions.

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 $N$ on a cubic lattice ridden by randomly distributed obstacles of the concentration $p$ interpreted as ions. The SAW monomers can bind to the obstacles with variable binding energy $\varepsilon$ 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 $\{p,N,\varepsilon\}$. 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.