The DOI matches its Crossref record; 43 of the 43 references it cites were found in a registry or an index.
Theoretical study of Cu–Au nanoalloy clusters using a genetic algorithm
Abstract
A study has been made of the structures and stabilities of copper and gold clusters and copper–gold nanoalloy clusters, with up to 56 atoms, modeled by the many-body Gupta potential. For pure copper clusters, the lowest energy structures are found to be based on icosahedral packing, while pure gold clusters tend to form less symmetrical (often amorphous) structures. In a number of cases, the replacement of a single gold atom by copper is found to be sufficient to convert the structure to that of the more symmetrical copper cluster. The lowest energy clusters are generally more difficult to find for the bimetallic clusters than for the pure metallic clusters, due to the presence of homotops (related by permuting Cu and Au atoms), as well as geometrical isomers. The structures of the lowest energy bimetallic clusters exhibit primarily icosahedral packing, with (CuAu)M and (CuAu3)M clusters tending to form layered structures and (Cu3Au)M clusters showing greater Cu–Au mixing.
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.
Integrity signals
Registry
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.
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
Genetic algorithms in search, optimization, and machine learning
(1989) · Choice Reviews Online · doi:10.5860/choice.27-0936 · Cited by 49,010
Holland, J. H. (1992) · The MIT Press eBooks · doi:10.7551/mitpress/1090.001.0001 · Cited by 47,002
Introduction to Solid State Physics
Kittel, C., & Fan, H. Y. (1957) · American Journal of Physics · doi:10.1119/1.1934457 · Cited by 22,240
Goldberg, D. E. (1989) · Medical Entomology and Zoology · Cited by 10,109
Selected values of the thermodynamic properties of binary alloys
Hultgren, R., Desai, P. D., Hawkins, D. T., Gleiser, M., & Kelley, K. K. (1973) · CERN Document Server (European Organization for Nuclear Research) · Cited by 3,316
Electronic Shell Structure and Abundances of Sodium Clusters
Knight, W. D., Clemenger, K., de Heer, W. A., Saunders, W. A., Chou, M. Y., & Cohen, M. L. (1984) · Physical Review Letters · doi:10.1103/physrevlett.52.2141 · Cited by 2,407
Tight-binding potentials for transition metals and alloys
Cleri, F., & Rosato, V. (1993) · Physical Review B · doi:10.1103/physrevb.48.22 · Cited by 1,940
Molecular Geometry Optimization with a Genetic Algorithm
Deaven, D. M., & Ho, K. M. (1995) · Physical Review Letters · doi:10.1103/physrevlett.75.288 · Cited by 1,136
The Crystal Chemistry and Physics of Metals and Alloys
Pearson, W. B., & Weaire, D. L. (1973) · Physics Today · doi:10.1063/1.3128023 · Cited by 1,100
Rosato, V., Guillope, M., & Legrand, B. (1989) · Philosophical Magazine A · doi:10.1080/01418618908205062 · Cited by 1,062
Cited by
Nanoalloys: From Theory to Applications of Alloy Clusters and Nanoparticles
Ferrando, R., Jellinek, J., & Johnston, R. L. (2008) · Chemical Reviews · doi:10.1021/cr040090g · Cited by 3,690
Self-citationStructural properties of nanoclusters: Energetic, thermodynamic, and kinetic effects
Baletto, F., & Ferrando, R. (2005) · Reviews of Modern Physics · doi:10.1103/revmodphys.77.371 · Cited by 1,811
Surface Energy of Nanostructural Materials with Negative Curvature and Related Size Effects
Ouyang, G., Wang, C. X., & Yang, G. W. (2009) · Chemical Reviews · doi:10.1021/cr900055f · Cited by 274
Alexandrova, A. N., Boldyrev, A. I., Fu, Y.-J., Yang, X., Wang, X.-B., & Wang, L.-S. (2004) · The Journal of Chemical Physics · doi:10.1063/1.1783276 · Cited by 271
Metadata
- Authors
- Darby, S., Mortimer-Jones, T. V., Johnston, R. L., & Roberts, C.
- Venue
- The Journal of Chemical Physics
- Publisher
- AIP Publishing
- Published
- 2002-01-22
- Volume
- 116
- Issue
- 4
- Pages
- 1536-1550
- ISSN
- 0021-9606 (ISSN-L)
- 1089-7690
- OpenAlex
- W2030929351
- Cited by
- 379
- References
- 43
- FWCI
- 12.09
- 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: Theoretical study of Cu–Au nanoalloy clusters using a genetic algorithm. https://app.cochat.ai/papers/10.1063/1.1429658
- The paper
- Darby, S., Mortimer-Jones, T. V., Johnston, R. L., & Roberts, C. (2002). Theoretical study of Cu–Au nanoalloy clusters using a genetic algorithm. The Journal of Chemical Physics. https://doi.org/10.1063/1.1429658
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.
