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Theoretical Characterization of a Nanocrystal Layer for Nonvolatile Memory Applications

Published online by Cambridge University Press:  01 February 2011

Yann Leroy ,
Dumitru Armeanu  and
Anne-Sophie Cordan
Yann Leroy
Affiliation:
yann.leroy@ensps.u-strasbg.fr, InESS (UMR 7163, CNRS-UdS), Strasbourg, France
Dumitru Armeanu
Affiliation:
dumitru.armeanu@ensps.u-strasbg.fr, InESS (UMR 7163, CNRS-UdS), Strasbourg, France
Anne-Sophie Cordan
Affiliation:
anne-sophie.cordan@ensps.u-strasbg.fr, InESS (UMR 7163, CNRS-UdS), Strasbourg, France
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Abstract

On the road to miniaturization, nanocrystal layers are promising as floating gate in nonvolatile flash memories. Although much experimental work has been devoted to the study of these new memory devices, only few theoretical models exist to help the experimentalists to understand the physical phenomena encountered and explain the behavior of the device.

We have developed a model based on the geometrical and physical properties of the elementary structure of a nanocrystal flash memory, i.e. one nanocrystal embedded in an oxide between the channel and the gate electrodes. To obtain a fine analysis of the observed phenomena, several specific hypotheses have been taken into account. Concerning the channel, the contribution of the subbands is explicitly included. In the case of an electrode with a quasi-continuum of energy levels, we replace the continuum by equivalent sets of 2D subbands in order to be able to isolate the energy range that really contributes to the charging/discharging of the nanocrystal. The properties of the materials (bulk band structure, dielectric permittivity, …) can be easily set as well as the geometrical specifications of the elementary structure (nanocrystal radius, tunnel and control oxyde thicknesses, …).

The behavior of a layer of nanocrystals is described according to a statistical approach starting from single nanocrystal results. This method allows us to take into account the fluctuations of geometrical parameters. Thus we are able to simulate various types of materials for the nanocrystals (Si, Ge, …), the oxide layer (SiO2, HfO2, …) and the electrodes, for both a single nanocrystal and layers of nanocrystals.

Keywords

memorysimulationnanostructure
Type
Research Article
Information
MRS Online Proceedings Library (OPL) , Volume 1250: Symposium G – Materials and Physics for Nonvolatile Memories II , 2010 , 1250-G01-04
Copyright
Copyright © Materials Research Society 2010

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References

[1] Molas, G. Salvo, B. D. Mariolle, D. Ghibaudo, G. Toffoli, A. Buffet, N. and Deleonibus, S. Sol. Stat. Elec. 47, 1645–1649 (2003).Google Scholar
[2] Decossas, S. Mazen, F. Baron, T. Bremond, G. and Souifi, A. Nanotechnology 14, 1272–1278 (2003).10.1088/0957-4484/14/12/008Google Scholar
[3] Bonafos, C. Carrada, M. Cherkashin, N. Coffin, H. Chassaing, D. Assayag, G. B. Claverie, A. Müller, T., Heinig, K. H. Perego, M. Fanciulli, M. Dimitrakis, P. and Normand, P. J. Appl. Phys. 95(10), 5696–5702 (2004).10.1063/1.1695594Google Scholar
[4] Shalchian, M. Grisolia, J. Assayag, G. B. Coffin, H. Atarodi, S. M. and Claverie, A. Appl. Phys. Lett. 86, 163111 (2005).Google Scholar
[5] Compagnoni, C. M. Gusmeroli, R. Ielmini, D. Spinelli, A. S. and Lacaita, A. L. J. Nanosci. Nanotechnol. 7(1), 193–205 (2007).Google Scholar
[6] Iannaccone, G. and Coli, P. Appl. Phys. Lett. 78(14), 2046–2048 (2001).10.1063/1.1361097Google Scholar
[7] Thean, A. and Leburton, J. P. IEEE Electron Dev. Lett. 22(3), 148–150 (2001); J. S. de Sousa, A. V. Thean, J. P. Leburton, and V. N. Freire, J. Appl. Phys. 92(10), 6182–6187 (2002).10.1109/55.910625Google Scholar
[8] Prada, M. and Harrison, P. New Journal of Physics 6(1), 30 (2004).10.1088/1367-2630/6/1/030Google Scholar
[9] Compagnoni, C. M. Ielmini, D. Spinelli, A. S. and Lacaita, A. L. IEEE Trans. Elect. Dev. 52(4), 569–576 (2005).Google Scholar
[10] Leriche, B. Leroy, Y. and Cordan, A. S. J. Appl. Phys. 100(7), 074316–1/6 (2006).Google Scholar
[11] Leroy, Y. Leriche, B. and Cordan, A. S. Modeling transport in silicon nanocrystal structure, in Proceedings of the COMSOL Multiphysics Conference 2005, pp. 129–134, Paris, November 2005.Google Scholar
[12] Leroy, Y. Armeanu, D. and Cordan, A. S. (to be published).Google Scholar
[13] Dubois, M. Latil, S. Scifo, L. Grévin, B., and Rubio, A. J. Chem. Phys. 125(3), 034708 (2006).Google Scholar
[14] AB, Comsol, Comsol Multiphysics Reference Manual, version 3.5, 2008.Google Scholar
[15] Simmons, J. G. Image force in Metal-Oxide-Metal tunnel junctions, in Tunneling phenomena in solids, edited by Burstein, E. and Lundqvist, S. chapter 10, pp. 135–148, Plenum Press, 1969.Google Scholar
[16] Norris, W. T. IEE Proc. Sci. Meas. Technol. 142(2), 142–150 (1995).Google Scholar
[17] Leroy, Y. and Cordan, A. S. Microelectron. Eng. 85(12), 2354–2357 (2008).Google Scholar
[18] Cordan, A. S. Leroy, Y. and Leriche, B. Sol. Stat. Elec. 50(2), 205–208 (2006).Google Scholar