Abstract
A new parametrization of the small-size silicon cluster is proposed in this paper to improve the quality of predicted energy value by potential energy function in force-field modeling. ASBO-based concept has applied to evolve the parameters under different circumstances and cluster structure. The performance of new parameters is compared with the other well-established parameters in stillinger–weber energy function and its variants. Under known and unknown environment, effects of higher dimension in energy predicting capability are also analyzed. A significant improvement is observed in predicting the small cluster energy value with a proposed solution compared to values obtained with existing parameters. PSO with dynamic weight (DWPSO) is also applied to analyze the comparative capability of ASBO in solution exploration and convergence characteristics, and there is a remarkable improvement observed with ASBO-based solution.
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References
Srivastava, D., Atluri, S.N.: Computational nanotechnology: a current perspective. CMES 3(5), 531–538 (2002)
MacLennan, B.J.: Morphogenesis as a model for nano communication. Elsevier Nano Commun. Netw. 1, 199–208 (2010)
Stillinger, W.: Computer simulation of local order in condensed phase of silicon. Phys. Rev. 31(8) (1985)
Gong, X.G., Zheng, Q.Q., He, Y.-Z.: Structural properties of silicon clusters: an empirical potential study. J. Phys. Condens. Matter 7 (1995)
Globus, A., Menon, M., Ricks, E., Srivastava, D.: Evolving molecular force field parameters for Si and Ge. NSTI Nanotechnol. Conf. Trade Show (2003)
Vink, R., Barkema, W.M.: Fitting the Stillinger-Weber potential to amorphous silicon. Elsevier J. Non-Cryst. Solids 282(2–3), 248–255 (2001)
Pizzagalli, L.: A new parametrization of the Stillinger–Weber potential for an improved description of defects and plasticity of silicon. J. Phys. Condens. Matter 25(5) (2013)
Mostaghim, S.: Molecular force field parametrization using multi-objective evolutionary algorithms. IEEE, CEC. 1 (2004)
Slepoy, A., Peters, M.D., Thompson, A.P.: Searching for globally optimal functional forms for interatomic potentials using genetic programming with parallel tempering. J. Comput. Chem. 28(15), 2465–2471 (2007)
Larsson, H.R., Hartke, B.: Fitting reactive force fields using genetic algorithms. Comput. Method Mater. Sci. 13(1) (2013)
Pukrittayakamee, A., Malshe, M.: Simultaneous fitting of a potential energy surface and its corresponding force filed using feed forward neural network. J. Chem. Phys. 130, 134101 (2009)
Hiura, H., Miyazaki, T., Kanayama, T.: Phys. Rev. Lett. 86, 1733 (2001)
Katircioglu, S., Erkoc, S.: Physica E 9, 314 (2001)
Baturin, V.S.: Structural and electronic properties of small silicon clusters. J. Phys. Conf. Series 510 (2014)
Singh, M.K.: A new optimization method based on adaptive social behavior: ASBO. Springer AISC 174, 823–831 (2012)
Clerc, M., Kennedy, J.: The particle swarm-explosion, stability, and convergence in a multidimensional complex space. IEEE Trans. Evol. Comput. 6(1) (2002)
Acknowledgments
This research has completed in Manuro Tech Research Pvt. Ltd., Bangalore, India. The Authors express their thanks to Mrs. Reeta Kumari (Director) for her valuable suggestion to accomplish this research.
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Gondakar, S.N., Vasan, S.T., Singh, M.K. (2016). Computational Intelligence-Based Parametrization on Force-Field Modeling for Silicon Cluster Using ASBO. In: Satapathy, S., Raju, K., Mandal, J., Bhateja, V. (eds) Proceedings of the Second International Conference on Computer and Communication Technologies. Advances in Intelligent Systems and Computing, vol 380. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2523-2_8
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DOI: https://doi.org/10.1007/978-81-322-2523-2_8
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