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Abstract:

The characterisation and prediction of the structures of metal silicon clusters is important for nanotechnology research because these clusters can be used as building blocks for nanodevices, integrated circuits and solar cells. Several authors have postulated that there is a transition between exo and endo absorption of Cu in Sin clusters and showed that, for n larger than 9, it is possible to find endohedral clusters. Unfortunately, no global searches have confirmed this observation, which is based on local optimisations of plausible structures. Here, we use parallel genetic algorithms (GAs), as implemented in our modified genetic algorithms (MGAC) software, directly coupled with density functional theory energy calculations to show that the global search of CuSin cluster structures does not find endohedral clusters for n8 but finds them for n10. © 2011 Taylor & Francis.

Registro:

Documento: Artículo
Título:Transition from exo to endo Cu absorption in CuSin clusters: A genetic algorithms density functional theory study
Autor:Oña, O.B.; Ferraro, M.B.; Facelli, J.C.
Filiación:Departamento de Física, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires, Argentina
Department of Biomedical Informatics, University of Utah, 155 South 1452 East, Salt Lake City, UT, United States
Center for High Performance Computing, University of Utah, 155 South 1452 East, Salt Lake City, UT, United States
Palabras clave:copper-silicon clusters; genetic algorithms; global optimisation; Density functional theory; Genetic algorithms; Global optimization; Structural optimization; Density functional theory studies; Endohedral clusters; Energy calculation; Global optimisation; Modified genetic algorithms; Nanotechnology research; Parallel genetic algorithms; Silicon clusters; Clustering algorithms
Año:2011
Volumen:37
Número:8
Página de inicio:678
Página de fin:688
DOI: http://dx.doi.org/10.1080/08927020903583830
Título revista:Molecular Simulation
Título revista abreviado:Mol Simul
ISSN:08927022
CODEN:MOSIE
Registro:https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_08927022_v37_n8_p678_Ona

Referencias:

  • Elkind, J.L., Alford, J.M., Weiss, F.D., Laaksonen, R.T., Smalley, R.E., FT-ICR probes of silicon cluster chemistry: The special behavior of Si (1987) J. Chem. Phys., 87, pp. 2397-2399
  • Shvartsburg, A.A., Jarrold, M.F., Liu, B., Lu, Z.-Y., Wang, C.-Z., Ho, K.-M., Dissociation energies of silicon clusters: A depth gauge for the global minimum on the potential energy surface (1998) Physical Review Letters, 81 (21), pp. 4616-4619
  • Honea, E.C., Ogura, A., Murray, C.A., Raghavachari, K., Sprenger, W.O., Jarrold, M.F., Brown, W.L., Raman spectra of size- selected silicon clusters and comparison with calculated structures (1993) Nature (London), 366, pp. 42-44
  • Raghavachari, K., Rohlfing, C.M., Bonding and stabilities of small silicon clusters: A theoretical study of Si7-Si10 (1988) J. Chem. Phys., 89, pp. 2219-2234
  • Rohlfing, C.M., Raghavachari, K., Electronic structures and photoelectron spectra of Si and Si (1992) J. Chem. Phys., 96, pp. 2114-2117
  • Ho, K.-M., Shvartsburg, A.A., Pan, B., Lu, Z.-Y., Wang, C.-Z., Wacker, J.G., Fye, J.L., Jarrold, M.F., Structures of medium-sized silicon clusters (1998) Nature, 392 (6676), pp. 582-585. , DOI 10.1038/33369
  • Jarrold, M.F., Bower, J.E., Mobilities of silicon cluster ions: The reactivity of silicon sausages and spheres (1992) J. Chem. Phys., 96, pp. 9180-9190. , references therein
  • Ma, L., Zhao, J., Wang, J., Wang, B., Wang, G., Growth behavior and magnetic properties ofSinFe (n~2-14) clusters (2006) Phys. Rev. B, 73, pp. 125439-125447
  • Wang, J., Han, J.G., Geometries, stabilities, and electronic properties ofdifferent-sized ZrSin (n=1-16) clusters: A density- functional investigation (2005) J Chem. Phys., 123, pp. 064306-064321
  • Hiura, H., Miyazaki, T., Kanayama, T., Structural transformation in the formation ofH-induced (111) platelets in Si (2001) Phys. Rev. Lett., 86, pp. 1773-1776
  • Ohara, M., Koyasu, K., Nakajima, A., Kaya, K., Geometric and electronic structures of metal (M)-doped silicon cluster (M = Ti, Hf, Mo and W) (2003) Chemical Physics Letters, 371 (3-4), pp. 490-497. , DOI 10.1016/S0009-2614(03)00299-9, PII S0009261403002999
  • Jaeger, J.B., Jaeger, T.D., Duncan, M.A., Photodissociation of metal-silicon clusters: Encapsulated versus surface-bound metal (2006) Journal of Physical Chemistry A, 110 (30), pp. 9310-9314. , DOI 10.1021/jp0629947
  • Lu, J., Nagase, S., Structural and electronicproperties ofmetal- encapsulated silicon clusters in a large size range (2003) Phys. Rev. Lett., 90, pp. 115506-115509
  • Sen, P., Mitas, L., Density-functional investigation of metal- silicon cage clusters MSin (M~Sc, Ti, V, Cr, Mn, Fe, Co, Ni, Cu, Zn; N\\-8-16) (2008) Phys Rev. B, 77, pp. 195417-195424
  • Reveles, J.U., Kahnna, S.N., Electronic counting rules for the stability of metal-silicon clusters (2006) Phys. Rev. B, 74, pp. 035435-035440. , references therein
  • Guo, L., Zhao, G., Gu, Y., Liu, X., Zeng, Z., Density-functional investigation of metal-silicon cage clusters MSin (M~Sc, Ti, V, Cr, Mn, Fe, Co, Ni, Cu, Zn; N~8-16) (2008) Phys Rev. B, 77, pp. 195417-195424
  • Beck, S.M., Studies of silicon cluster-metal atom compound formation in a supersonic molecular beam (1987) J. Chem. Phys., 87, pp. 4233-4234
  • Beck, S.M., Mixed metal-silicon clusters formed by chemical reaction in a supersonic molecular beam: Implications for reactions at the metal/silicon interface (1989) J. Chem. Phys., 90, pp. 6306-6312
  • Andriotis, A.N., Mpourmpakis, G., Froudakis, G., Menon, M., Stabilization of Si-based cage clusters and nanotubes by encapsulation of transition metal atoms (2002) New J. Phys., 4, pp. 781-7814
  • Koyasu, K., Atobe, J., Akutsu, M., Mitsui, M., Nakajima, A., Electronic and geometric stabilities of clusters with transition metal encapsulated by silicon (2007) Journal of Physical Chemistry A, 111 (1), pp. 42-49. , DOI 10.1021/jp066757f
  • Xiao, C., Hagelberg, F., Lester Jr., W.A., Geometric, energetic, and bonding properties ofneutral and charged copper-doped silicon clusters (2002) Phys Rev. B, 66, pp. 075425-075447
  • Zdetsis, A.D., Bonding and structural characteristics of Zn-, Cu-, and Ni-encapsulated Si clusters: Density-functional theory calcu- lations (2007) Phys Rev. B, 75, pp. 08549-08558
  • Hossain, D., Pittman Jr., C.U., Gwaltney, S.R., Structures and stabilities of copper encapsulated within silicon nano-clusters: CuSin (n~9-15) (2008) Chem. Phys. Lett., 451, pp. 93-97
  • Hagelberg, F., Xiao, C., Lester Jr., W.A., Cagelike Si12 clusters with endohedral Cu, Mo, and W metal atom impurities (2003) Phy Rev. B, 67, pp. 035426-035434
  • Bazterra, V.E., Ferraro, M.B., Facelli, J.C., Modified genetic algorithm to model crystal structures. I. Benzene, naphthalene and anthracene (2002) Journal of Chemical Physics, 116 (14), pp. 5984-5991. , DOI 10.1063/1.1458547
  • Bazterra, V.E., Cuma, M., Ferraro, M.B., Facelli, J.C., A general framework to understand parallel performance in heterogeneous systems (2005) J. Parallel Distr. Comput., 65, pp. 48-57
  • Oña, O., Bazterra, V.E., Caputo, M.C., Ferraro, M.B., Facelli, J.C., Ab initio global optimization of the structures of Sin H. n~4-10, using parallel genetic algorithm (2005) Phys Rev. A, 72, pp. 053205-053212
  • Luque, G., Alba, E., Dorronsoro, B., Parallel genetic algorithms (2005) Parallel Metaheuristics: A New Class of Algorithms, pp. 105-125. , E. Alba, ed. Wiley Hoboken, NJ
  • Cantu-Paz, E., (2000) Efficient and Accurate Parallel Genetic Algorithms, Series: GeneticAlgorithms and Evolutionary Computation, 1. , Springer, Berlin
  • Johnston, R.L., Roberts, C., Genetic algorithms for the geometry optimization of clusters and nanoparticles (2003) Soft Computing Approaches in Chemistry, 120, pp. 161-204. , H.M. Cartwright and M. Sztandera, eds. Springer-Verlag, Heildberg
  • Oña, O., Bazterra, V.E., Caputo, M.C., Ferraro, M.B., Fuentealba, P., Facelli, J.C., Modified genetic algorithms to model atomic cluster structures: CuSi clusters (2004) J. Mol. Struct. (THEOCEHM), 681, pp. 149-155
  • Ballone, P., Andreoni, W., Clusters, M., Eckardt, W., (1999), p. 71. , ed. Wiley Chichester; Oña, O., Bazterra, V.E., Caputo, M.C., Ferraro, M.B., Facelli, J.C., Global optimization of atomic cluster structures using parallel genetic algorithms (2006) Mater. Res. Soc. Symp., 894, pp. 277-281
  • Parrinello, M., Andreoni, W., Computer Code CPMD V3.9, , http://www.cpmd.org/, Available at
  • Goedecker, S., Hutter, J., Teter, M., Separable dual-space Gaussianpseudopotentials (1996) Phys. Rev. B, 54, pp. 1703-1710
  • Perdew, J.P., Burke, K., Ernzerhof, M., Generalized gradient approximation made simple (1996) Physical Review Letters, 77 (18), pp. 3865-3868
  • Frisch, M.J., Trucks, G.W., Schlegel, H.B., Scuseria, G.E., Robb, M.A., Cheeseman, J.R., Montgomery Jr., J.A., Po Le, J.A., (2004) Gaussian 03, , Revision C.02, Gaussian Inc., Wallingford CT
  • Bazterra, V.E., Oña, O., Caputo, M.C., Ferraro, M.B., Fuentealba, P., Facelli, J.C., Modified genetic algorithms to model cluster structures in medium size silicon clusters (2004) Phys. Rev. A, 69, pp. 053202-053208
  • Gruene, P., Fielicke, A., Meijer, G., Janssens, E., Ngan, V.T., Nguyen, M.T., Lievens, P., Tuning the geometric structure by doping silicon clusters (2008) Chem. Phys. Chem., 9, pp. 703-706
  • King, R.B., Topological models ofthe chemical bonding in transition metal-silicon clusters (1991) Z Phys. D, 18, pp. 189-191
  • Kishi, R., Iwata, S., Nakajima, A., Kaya, K., Geometric and electronic structures of silicon-sodium binary clusters. I. Ionization energy of SinNam (1997) Journal of Chemical Physics, 107 (8), pp. 3056-3070
  • Xiao, C., Abraham, A., Quinn, R., Hagelberg, F., Lester Jr., W.A., Comparative study on the interaction of scandium and copper atoms with small silicon clusters (2002) Journal of Physical Chemistry A, 106 (46), pp. 11380-11393. , DOI 10.1021/jp021668y
  • Schafer, R., Schlecht, S., Woenckhaus, J., Becker, J.A., Polarizabilities of isolated semiconductor clusters (1996) Physical Review Letters, 76 (3), pp. 471-474
  • Wang, J., Yang, M., Wang, G., Zhan, J., Dipole polarizabilities of germanium clusters (2003) Chem. Phys. Lett., 367, pp. 448-454
  • Pouchan, C., Begué, D., Zhang, D., Between geometry, stability, and polarizability: Density functional theory studies of silicon clusters Sin (n=3-10) (2004) J Chem. Phys., 121, pp. 4628-4634
  • Jackson, K.A., Yang, M., Chaudhuri, I., Frauenheim, T., Shape, polarizability, and metallicity in silicon clusters (2005) Phys Rev. A, 71, pp. 033205-033210
  • Hiura, H., Miyazaki, T., Kanayama, T., Formation of metal- encapsulating Si cage clusters (2001) Phys. Rev. Lett., 86, pp. 1733-1736
  • Lightstone, J.M., Patterson, M.J., White, M.G., Reactivity of the M4S? (M~Mo W) cluster with CO and NH3 in the gas-phase: An experimental and DFT study (2005) Chem. Phys. Lett., 413, pp. 429-433

Citas:

---------- APA ----------
Oña, O.B., Ferraro, M.B. & Facelli, J.C. (2011) . Transition from exo to endo Cu absorption in CuSin clusters: A genetic algorithms density functional theory study. Molecular Simulation, 37(8), 678-688.
http://dx.doi.org/10.1080/08927020903583830
---------- CHICAGO ----------
Oña, O.B., Ferraro, M.B., Facelli, J.C. "Transition from exo to endo Cu absorption in CuSin clusters: A genetic algorithms density functional theory study" . Molecular Simulation 37, no. 8 (2011) : 678-688.
http://dx.doi.org/10.1080/08927020903583830
---------- MLA ----------
Oña, O.B., Ferraro, M.B., Facelli, J.C. "Transition from exo to endo Cu absorption in CuSin clusters: A genetic algorithms density functional theory study" . Molecular Simulation, vol. 37, no. 8, 2011, pp. 678-688.
http://dx.doi.org/10.1080/08927020903583830
---------- VANCOUVER ----------
Oña, O.B., Ferraro, M.B., Facelli, J.C. Transition from exo to endo Cu absorption in CuSin clusters: A genetic algorithms density functional theory study. Mol Simul. 2011;37(8):678-688.
http://dx.doi.org/10.1080/08927020903583830