Persistence length of semi-flexible polymer chains on Euclidean lattices

Ivan Živić, Sunčica Elezović-Hadžić and Dušanka Marčetić

Physica A: Statistical Mechanics and its Applications, 2022, vol. 607, issue C

Abstract: We have studied the persistence length behavior of semi-flexible linear polymers, represented by self-avoiding random walks (SAWs) on the square (d=2) and simple cubic (d=3) lattice. By employing the PERM Monte Carlo algorithm we have generated SAWs, changing the chain stiffness (characterized by the parameter s, related to each bend of a SAW). We have examined two quantities that measure persistence length of N-step SAWs: (1) ℓN, which is defined as an average length of straight parts of polymer chains, and (2) λN, defined as the mean projection of the end-to-end distance vector on the SAW’s first step. For each particular s, we have found that ℓN is a linear function of 1/N in both dimensions, d=2 and d=3, while λN is a linear function of 1/NΦeff, where Φeff≈0.3 in d=2 and Φeff≈0.82 in d=3. Sequences of ℓN and λN have been extrapolated in the range of very long chains, and we have established that, for each examined s, they converge to s dependent constants ℓp=ℓN→∞ and λp=λN→∞. We analyze dependence of ℓp and λp on the polymer stiffness s, and make a comparison between our findings and former results for studied quantities.

Keywords: Polymers; Self-avoiding walks; Persistence length; Chain stiffness; Monte Carlo (search for similar items in EconPapers)
Date: 2022
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0378437122007804
Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:607:y:2022:i:c:s0378437122007804

DOI: 10.1016/j.physa.2022.128222

Access Statistics for this article

Physica A: Statistical Mechanics and its Applications is currently edited by K. A. Dawson, J. O. Indekeu, H.E. Stanley and C. Tsallis

More articles in Physica A: Statistical Mechanics and its Applications from Elsevier
Bibliographic data for series maintained by Catherine Liu ().