Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 176

The DOI matches its Crossref record.

Short range correlation between elements of a long polymer in a good solvent

Open access
des Cloizeaux, J.·1980·Journal de Physique

Abstract

Correlation properties of a long polymer in a good solvent are studied with the help of renormalization techniques. The probability distribution of the vector r joining, in a space of dimension d, the end points of a polymer segment made of N links, is a function Ps,N(r), where s is an index referring to various situations. Case s = 0 : the segment coincides with the polymer itself. Case s = 1 : the segment is at one extremity of an infinite polymer. Case s = 2 : the segment is located in the central part of an infinite polymer. It is shown that the probability distributions obey scaling laws of the form Ps,N(r) = N-νd fs (r/N ν), that, for small x, fs(x) ∝ x θs and that the indices θ0, θ1, θ 2 are given by the renormalization of simple vertices. The second order expansions of these indices with respect to ε = 4 — d have been calculated. The results are : Estimations of these indices for d = 3 give θ0 = 0.273, θ1 = 0.46, θ 2 = 0.71. These results show that the probability of contact of the end points of a segment made of N links, belonging to the central part of an infinite polymer is proportional to N-ν(d+θ2 )≃ N-2.18. This conclusion agrees with the fact, predicted by the author, that for N>> 1, the dominant terms of the energy E of a polymer made of N monomers, are of the form E = aN + b, in a good solvent.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1051/jphys:01980004103022300

Cites

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cited by

See all 176

Metadata

Authors
des Cloizeaux, J.
Venue
Journal de Physique
Publisher
EDP Sciences
Published
1980
Volume
41
Issue
3
Pages
223-238
ISSN
0302-0738 (ISSN-L)
OpenAlex
W2146345439
Cited by
176
References
0
FWCI
3.10
Type
journal article
Language
en
Open access
green

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Short range correlation between elements of a long polymer in a good solvent. https://app.cochat.ai/papers/10.1051/jphys:01980004103022300
The paper
des Cloizeaux, J. (1980). Short range correlation between elements of a long polymer in a good solvent. Journal de Physique. https://doi.org/10.1051/jphys%3A01980004103022300

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.