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Finding low energy conformations of atomic clusters using evolution strategies

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Evolutionary Programming VII (EP 1998)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1447))

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Abstract

We demonstrate the use of evolution strategies in the search for low energy conformations of atomic clusters. Our results indicate that the search process can be performed efficiently without having to relax the cluster structure as is done in genetic algorithm approaches. The evolution strategy is tested on small clusters of silicon atoms.

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References

  1. Z. Bačić and R. Miller, “Molecular clusters: structure and dynamics of weakly bound systems”, J. Phys. Chem. 100, 12945–12959, 1996

    Google Scholar 

  2. Cluster Ions, C. Ng. T. Baer and I. Powis (Eds.), John Wiley & Son, New York, 1993 and references therein

    Google Scholar 

  3. M. Jarrold, “Drift tube studies of atomic clusters”, J. Phys. Chem. 99, 11–21, 1995

    Google Scholar 

  4. M. Born and J. Oppenheimer, “Zur quantentheorie der molekeln”, Ann. d. Phys. 84, 457–484, 1927

    Google Scholar 

  5. M. Hoare, “Structure and dynamics of simple microclusters”, Adv. Chem. Phys. 40, 49–135, 1979

    Google Scholar 

  6. L. Wille and J. Vennik, “Computational complexity of the ground-state determination of atomic clusters”, J. Phys. A 18, L419–L422, 1985

    Google Scholar 

  7. B. Hartke, “Global geometry optimization of clusters using genetic algorithms”, J. Phys. Chem. 97, 9973–9976, 1993

    Google Scholar 

  8. Y. Zeiri, “Prediction of the lowest energy structure of clusters using a genetic algorithm”, Phys. Rev. E 51, R2769–R2772, 1995

    Google Scholar 

  9. R. Judson, M. Colvin, J. Meza, A. Huffer and D. Gutierrez, “Do intelligent configuration search techniques outperform random search for large molecules?”, Int. J. Quant. Chem. 44, 277–290, 1992

    Google Scholar 

  10. P. Tuffery, C. Etchebest, S. Hazout and R. Lavery, “A critical comparison of search algorithms applied to the optimization of protein side conformations”, J. Comput. Chem 14, 790–798, 1993

    Google Scholar 

  11. W. Pullan, “Energy minimization of mixed argon-xenon microclusters using a genetic algorithm”, J. Comput. Chem. 18, 1096–1111, 1997

    Google Scholar 

  12. T. Bäck and F. Hoffmeister, “Basic aspects evolution strategies”, Statistics & Computing 4, 51–63, 1994

    Google Scholar 

  13. W. Brown, R. Freeman, K. Raghavachari and M. Schluter, “Covalent group IV atomic clusters”, Science 235, 860–865, 1987

    Google Scholar 

  14. J. Chelikowsky, J. Phillips, M. Kamal and M. Strauss, “Surface and thermodynamic interatomic force fields for silicon clusters and bulk phases”, Phys. Rev. Lett. 62, 292–295, 1989

    Google Scholar 

  15. XMol, version 1.3.1, Network Computing Services, Inc., Minneapolis MN, 1993

    Google Scholar 

  16. B. Hartke, “Global geometry optimization of clusters guided by N-dependent model potentials”, Chem. Phys. Lett. 258, 144–148, 1996

    Google Scholar 

  17. B. Bolding and H. Andersen, “Interatomic potential for silicon clusters, crystals and surfaces”, Phys. Rev. B 41, 10568–10585, 1990

    Google Scholar 

  18. D. Deaven and K. Ho, “Molecular geometry optimization with a genetic algorithm”, Phy. Rev. Lett. 75, 288–291, 1995

    Google Scholar 

  19. F. Stillinger and T. Weber, “Computer simulation of local order in condensed phases of silicon”, Phys. Rev. B 31, 5262–5271, 1985

    Google Scholar 

  20. X. Gong, “Empirical potential studies on the structural properties of small silicon clusters”, Phys. Rev. B 47, 2329, 1993

    Google Scholar 

  21. R. Judson, E. Jaeger, A. Treasurywala and M. Peterson, “Conformational searching methods for small molecules. II. genetic algorithm approach”, J. Comput. Chem 14, 1407–1414, 1993

    Google Scholar 

  22. D. McGarrah and R. Judson, “Analysis of the genetic algorithm method of molecular conformation determination”, J. Comput. Chem. 14, 1385–1395, 1993

    Google Scholar 

  23. R. Jones and O. Gunnarsson, “The density functional formalism, its applications and prospects”, Rev. Mod. Phy. 61, 689–746, 1989

    Google Scholar 

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V. W. Porto N. Saravanan D. Waagen A. E. Eiben

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© 1998 Springer-Verlag Berlin Heidelberg

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Greenwood, G.W., Liu, YP. (1998). Finding low energy conformations of atomic clusters using evolution strategies. In: Porto, V.W., Saravanan, N., Waagen, D., Eiben, A.E. (eds) Evolutionary Programming VII. EP 1998. Lecture Notes in Computer Science, vol 1447. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0040801

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  • DOI: https://doi.org/10.1007/BFb0040801

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  • Print ISBN: 978-3-540-64891-8

  • Online ISBN: 978-3-540-68515-9

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