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Structure descriptor for surface passivation in the simulation of atomistic models

原子模型仿真中用于表面钝化的结构描述子

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Abstract

Surface passivation is an essential step for atomistic simulations. There can be many possible surface passivation results for a given device model, such as semiconductor devices that consist of Si, GaAs, or other materials because the bonding directions of the surface atoms may not be unique. Based on the structure analysis of the given model, a generation method with structure descriptor (SDG) is proposed for surface passivation. Compared with other existing solutions, the SDG method not only provides trimmer results, but also reduces the torsion angle energy of the model, which is preferred in the simulation of atomistic models. The efficiency of this method was validated through test results from several applications.

摘要

创新点

本文提出一种利用分析原子器件模型几何结构的方法辅助进行表面钝化的方法。相较于基于原子构型的表面钝化方法, 这种新方法的优点包括:

  1. 1、

    利用结构描述子可以对各种原子模型产生更齐整的表面钝化模型。

  2. 2、

    结构描述子可以从给定的原子模型进行结构分析后产生, 无需附加的模型材料信息。

  3. 3、

    提出的表面钝化方法易于拓展到其它拥有晶体结构的原子模型。

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References

  1. Kim D M, Khondker A N, Ahmed S S, et al. Theory of conduction in polysilicon: drift-diffusion approach in crystalline- amorphous-crystalline semiconductor systemPart I: small signal theory. IEEE Trans Electron Dev, 1984, 31: 480–493

    Article  Google Scholar 

  2. Khondker A N, Kim D M, Ahmed S S, et al. Theory of conduction in polysilicon: drift-diffusion approach in crystalline- amorphous-crystalline semiconductor systemPart II: general I-V theory. IEEE Trans Electron Dev, 1984, 31: 493–500

    Article  Google Scholar 

  3. Green M A. Intrinsic concentration, effective densities of states, and effective mass in silicon. J Appl Phys, 1990, 67: 2944–2954

    Article  Google Scholar 

  4. Vasileska D, Mamaluy D, Khan H R, et al. Semiconductor device modeling. J Comput Theor Nanosci, 2008, 5: 999–1030

    Article  Google Scholar 

  5. Martinez A, Kalna K, Sushko P V, et al. Impact of body-thickness-dependent band structure on scaling of double-gate MOSFETs: a DFT/NEGF study. IEEE Trans Nanotechnol, 2009, 8: 159–166

    Article  Google Scholar 

  6. Zhang L N, Zahid F, Zhu Y, et al. First principles simulations of nanoscale silicon devices with uniaxial strain. IEEE Trans Electron Dev, 2013, 60: 3527–3533

    Article  Google Scholar 

  7. Velichko O I, Shaman Y P, Kovaliova A P. Simulation of hydrogen diffusion and boron passivation in crystalline silicon. Modell Simul Mater Sci Eng, 2014, 22: 035003

    Article  Google Scholar 

  8. Vo T, Williamson A J, Galli G. First principles simulations of the structural and electronic properties of silicon nanowires. Phys Rev B, 2006, 74: 045116

    Article  Google Scholar 

  9. Yelundur V. Understanding and implementation of hydeogen passivation of deffects in string ribbon silicon for high-efficiency, manufacturable, silicon solar cells. Dissertation for the Doctoral Degree. Georgia: Georgia Institute of Technology, 2003

    Google Scholar 

  10. Taylor R D, Jewsbury P J, Essex J W. A review of protein-small molecule docking methods. J Comput-Aid Mol Des, 2002, 16: 151–166

    Article  Google Scholar 

  11. Yam C Y, Peng J, Chen Q, et al. A multi-scale modeling of junctionless field-effect transistors. Appl Phys Lett, 2013, 103: 062109

    Article  Google Scholar 

  12. Northrup J. Structure of Si(100)H: dependence on the H chemical potential. Phys Rev B, 1992, 44: 1419–1422

    Article  Google Scholar 

  13. Materials studio—visualization and statistics software. v4.3.0.0 Accelrys Software Inc., 2008

  14. HyperChem—molecular modeling system. v8.0. Hypercube Inc., 2007

  15. Zevenbergen I S, Martynov Y V, Rasmussen F B, et al. Magnetic resonance spectroscopy of hydrogen-passivated double donors in silicon. Mater Sci Eng B, 1996, 36: 138–141

    Article  Google Scholar 

  16. Ma D D D, Lee C S, Au F C K, et al. Small-Diameter silicon nanowire surfaces. Science, 2003, 299: 1874–1877

    Article  Google Scholar 

  17. Hansen U, Vogl P. Hydrogen passivation of silicon surfaces: a classical molecular-dynamics study. Phys Rev B, 1998, 57: 295–304

    Article  Google Scholar 

  18. Daras P, Zarpalas D, Axenopoulos A, et al. Three-dimensional shape-structure comparison method for protein classi- fication. Trans Comput Biol Bioinf, 2006, 3: 193–207

    Article  Google Scholar 

  19. Rappe A K, Casewit C J, Colwell K S, et al. UFF, a full periodic table force field for molecular mechanics and molecular dynamics simulations. J Amer Chem Soc, 1992, 114: 10024–10035

    Article  Google Scholar 

  20. Cornell W D, Cieplak P, Bayly C I, et al. A second generation force field for the simulation of proteins, nucleic acids, and organic molecules. J Amer Chem Soc, 1995, 117: 5179–5197

    Article  Google Scholar 

  21. van Duin A C T, Strachan A, Stewman S, et al. ReaxFFSiO reactive force field for silicon and silicon oxide systems. J Phys Chem A, 2003, 107: 3803–3811

    Article  Google Scholar 

  22. Postma H, Teepen T, Yao Z, et al. Carbon nanotube single-electron transistors at room temperature. Science, 2001, 293: 75–79

    Article  Google Scholar 

  23. Furuhashi M. Chiral vector determination of carbon nanotubes by observation of interference patterns near the end cap. Phys Rev Lett, 2008, 101: 185503

    Article  Google Scholar 

  24. Franklin A D, Luisier M, Han S J, et al. Sub-10nm carbon nanotube transistor. Nano Lett, 2012, 12: 758–762

    Article  Google Scholar 

  25. Peng L M, Zhang Z Y, Wang S, et al. Carbon based nanoelectronics: materials and devices (in Chinese). Sci Sin Tech, 2014, 44: 1071–1086

    Google Scholar 

  26. Wang W C, Lee G, Huang M, et al. First-principles study of GaAs(001)-β2(2 × 4) surface oxidation and passivation with H, Cl, S, F, and GaO. J Appl Phys, 2010, 107: 103720

    Article  Google Scholar 

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Correspondence to Li Cao.

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Cao, L., Koo, S., Sun, J. et al. Structure descriptor for surface passivation in the simulation of atomistic models. Sci. China Inf. Sci. 60, 032103 (2017). https://doi.org/10.1007/s11432-014-0876-4

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  • DOI: https://doi.org/10.1007/s11432-014-0876-4

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