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Coarse-grained kinetic scheme-based simulation framework for solution growth of ZnO nanowires

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Abstract

Kinetic Monte Carlo (KMC)-based stochastic model is used to understand the growth of zinc oxide nanowires from aqueous solution containing chemical precursors and capping agent. Through a hydrothermal growth mechanism, the average diameter of zinc oxide wires obtained is around 300 nm, whereas the length is order of several micrometers. Our Monte Carlo algorithm is based on the continuous-time Monte Carlo algorithm of Bortz, Kalos and Lebowitz (BKL) methodology. Both reactions and diffusion mechanisms assigning stochastic probabilities have been simulated. In algorithm, the ZnO atoms were treated as individual particles which diffuse in solution substrate and interact with other type of atoms. Once attached with growing nanowires, the diffusion rate of ZnO atom is considerably reduced. Since in a KMC algorithm each atom can be represented individually therefore, internal noise is automatically incorporated.

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References

  • Abhilash S, Hemant CW, Mats B, Joy deep DJ (2006) Zinc oxide nanowires in chemical bath on seeded substrates: role of hexamine. J Sol-Gel Sci Technol 39:49–56

    Article  Google Scholar 

  • Anthony SP, Lee JI, Kim JK (2007) Tuning optical band gap of vertically aligned ZnO nanowire arrays grown by homoepitaxial electrodeposition. Appl Phys Lett 90:103107

    Article  Google Scholar 

  • Battaile CC (1998) Atomic-scale kinetic Monte Carlo simulations of diamond chemical vapor deposition. PhD Thesis, University of Michigan, pp 147–170

  • Battaile CC, Srolovitz DJ (2002) Kinetic Monte Carlo simulation of chemical vapor deposition. Annu Rev Mater Res 32:297–319

    Article  CAS  Google Scholar 

  • Boercker JE, Schmidt JB, Aydil ES (2009) Transport limited growth of zinc oxide nanowires. Cryst Growth Des 9(6):2783–2789

    Article  CAS  Google Scholar 

  • Chang CP, Fan YZ, Chien JC, Stichtenoth D, Ronning C, Lu G (2006) High-performance ZnO nanowire field effect transistors. J Appl Phys Lett 89:133113–133115

    Article  Google Scholar 

  • Chen G (1998) Thermal conductivity and ballistic phonon transport in cross-plane direction of super lattices. Phys Rev B 57:14958–14973

    Article  CAS  Google Scholar 

  • Chen G, Borca T, Yang GR (2004) Encyclopedia of nanoscience and nanotechnology, vol 7. American Scientific Publishers, Stevenson Ranch, CA, pp 429–459

    Google Scholar 

  • Fischetti MV, Lai VM, Laux SE (1993) Monte Carlo study of electron transport in Si inversion layers. Phys Rev B 48:2244–2245

    Article  CAS  Google Scholar 

  • Grafoute M, Labaye Y, Calvayrac F, Grenèche JM (2005) Structure of grain boundaries in nanostructured powders: a Monte Carlo/EAM numerical investigation. J Eur Phys 45:419–424

    CAS  Google Scholar 

  • Greene L, Law M, Goldberger J, Kim F, Johnson J, Zhang Y, Yang P (2003) Low-temperature wafer-scale production of ZnO nanowire arrays. Angew Chem 42:3031–3034. doi:10.1002/anie.200351461

    Article  CAS  Google Scholar 

  • Howell RJ (1998) The Monte Carlo method in radiative heat transfer. J Heat Transf 120:547–560

    Article  CAS  Google Scholar 

  • Jacoboni C, Reggiani L (1983) The Monte Carlo method for the solution of charge transport in semiconductors with applications to covalent materials. Rev Mod Phys 55:645–705

    Article  CAS  Google Scholar 

  • Law M, Greene LE, Johnson JC, Saykally R, Yang P (2005) Nanowire dye-sensitized solar cells. Nat Mat 4:455–459

    Article  CAS  Google Scholar 

  • Lugli P, Bordone P, Reggiani L, Rieger M, Kocevar P, Goodnick MS (1989) Monte Carlo studies of non equilibrium phonon effects in polar semiconductors and quantum wells. Phys Rev B 39:7852–7865

    Article  Google Scholar 

  • Majumdar A (2004) Thermoelectricity in semiconductor nanostructures. Science 303:777–778

    Article  CAS  Google Scholar 

  • Ming Shan J, Ronggui Y, Gang C (2005) Monte Carlo simulation of thermoelectric properties in nanocomposites. In: 24th International conference on ICT, vol 19, pp 21–26

  • Rossnagel S, Ulman A (1996) Modeling of film deposition for microelectronic applications. Thin Films 22:290–291

    Article  Google Scholar 

  • Su WY, Huang JS, Lin CF (2008) Improving the property of ZnO nanorods using hydrogen peroxide solution. J Cryst Growth 310:2806–2809

    Article  CAS  Google Scholar 

  • Vayssieres L (2003) Growth of arrayed nanorods and nanowires of ZnO from aqueous solutions. Adv Mater 15:464–466

    Article  CAS  Google Scholar 

  • Vugt KVL, Ruhle S, Ravindran P, Gerritsen CH, Kuipers L, Vanmaekelbergh D (2006) Exciton polaritons confined in a ZnO nanowire cavity. Phys Rev Lett 97:147401

    Article  Google Scholar 

  • Wu JJ, Liu CS (2002) Low-temperature growth of well-aligned ZnO nanorods by chemical vapor deposition. Adv Mater 4:215–218. doi:10.1002/1521-4095(20020205)14:3

    Article  Google Scholar 

  • Zeyan W, Baibiao H, Xiaojing L, Xiaoyan Q, Xiaoyang Z, Jiyong W, Peng W, Shushan Y, Zhang Q, Yang X (2008) Photoluminescence studies from ZnO nanorod arrays synthesized by hydrothermal method with polyvinyl alcohol as surfactant. J Mater Lett 62:2637–2639

    Article  Google Scholar 

  • Zhang J, Sun L, Pan H, Liao C, Yang C (2002) ZnO nanowires fabricated by a convenient route. New J Chem 26:33–34

    Article  Google Scholar 

  • Zhang H, Du N, Wu J, Ma X, Yang D, Zhang X, Yang Z (2007) A novel low-temperature chemical solution route for straight and dendrite-like ZnO nanostructures. J Mater Sci Eng B 141:76–81

    Article  CAS  Google Scholar 

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Acknowledgment

This work was supported by National Science Foundation through NSF Grant no. 2103-1016.

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Authors and Affiliations

  1. Department of Electrical Engineering, University of South Florida, 4202 E Fowler Avenue, Tampa, FL, 33620-5350, USA

    Farah Alvi

  2. Department of Mechanical Engineering, University of South Florida, 4202 E Fowler Avenue, Tampa, FL, 33620, USA

    Rakesh K. Joshi & Ashok Kumar

  3. Daniel J. Epstein Department of Industrial and Systems Engineering, University of Southern California, Los Angeles, CA, USA

    Qiang Huang

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  1. Farah Alvi
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  2. Rakesh K. Joshi
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  3. Qiang Huang
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  4. Ashok Kumar
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Correspondence to Farah Alvi.

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Alvi, F., Joshi, R.K., Huang, Q. et al. Coarse-grained kinetic scheme-based simulation framework for solution growth of ZnO nanowires. J Nanopart Res 13, 2451–2459 (2011). https://doi.org/10.1007/s11051-010-0137-6

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  • DOI: https://doi.org/10.1007/s11051-010-0137-6

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