Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 597

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Archetypal energy landscapes

Wales, David J., Miller, Mark A., Walsh, Tiffany R.·1998·Nature

Abstract

Energy landscapes hold the key to understanding a wide range of molecular phenomena. The problem of how a denatured protein re-folds to its active state (Levinthal's parado) has been addressed in terms of the underlying energy landscape, as has the widely used ‘strong’ and ‘fragile’ classification of liquids,. Here we show how three archetypal energy landscapes for clusters of atoms or molecules can be characterized in terms of the disconnectivity graphs of their energy minima—that is, in terms of the pathways that connect minima at different threshold energies. First we consider a cluster of 38 Lennard–Jones particles, whose energy landscape is a ‘double funnel’ on which relaxation to the global minimum is diverted into a set of competing structures. Then we characterize the energy landscape associated with the annealing of C60 cages to buckministerfullerene, and show that it provides experimentally accessible clues to the relaxation pathway. Finally we show a very different landscape morphology, that of a model water cluster (H2O)20, and show how it exhibits features expected for a ‘strong’ liquid. These three examples do not exhaust the possibilities, and might constitute substructures of still more complex landscapes.

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 · 10.1038/29487

Cites

1 of 1 references verified0 citation errors · 0 not checkable

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

Cites

Show all 1 references

Cited by

See all 597

Metadata

Authors
Wales, D. J., Miller, M. A., & Walsh, T. R.
Venue
Nature
Published
1998-08
Volume
394
Issue
6695
Pages
758-760
ISSN
  • 0028-0836 (ISSN-L)
  • 1476-4687
OpenAlex
W1566214213
Cited by
597
References
1
FWCI
14.54
Type
journal article
Language
en
Open access
closed

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: Archetypal energy landscapes. https://app.cochat.ai/papers/10.1038/29487
The paper
Wales, D. J., Miller, M. A., & Walsh, T. R. (1998). Archetypal energy landscapes. Nature. https://doi.org/10.1038/29487

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.