Publication :


Title:

Numerical simulations for quantitative analysis of electrostatic interaction between atomic force microscopy probe and an embedded electrode within a thin dielectric: meshing optimization, sensitivity to potential distribution and impact of cantilever contribution

Authors: M. Azib, F. Baudoin, N. Binaud, C. Villeneuve-faure, F. Bugarin, S. Segonds and G. Teyssedre
Year: février 2018
Journal: Journal of Physics D - Applied Physics.
Volume: in press,

DOI: 10.1088/1361-6463/aab286
Référencé Scopus

Abstract:
Recent experimental results demonstrated that Electrostatic Force Distance Curve (EFDC) can be used for space charge probing in thin dielectric layers. A main advantage of the method is claimed to be its sensitivity to charge localization, which, however, needs to be substantiated by numerical simulations. In this paper, we have developed a model which permits to compute EFDC accurately by using the most sophisticated and accurate geometry for the Atomic Force Microscopy (AFM) probe. To avoid simplifications and in order to reproduce experimental conditions, EFDC has been simulated for a system constituted of a polarized electrode embedded in a thin dielectric layer (SiNx). The individual contributions of forces on the tip and on the cantilever have been analysed separately to account for possible artefacts. The EFDC sensitivity to potential distribution is studied through change in electrodes shape, namely the width and the depth. Finally, the numerical results have been compared with experimental data.

Bibtex citation :
@article{Azib2018,
Author={Azib, M. and Baudoin, F. and Binaud, N. and Villeneuve-faure, C. and Bugarin, F. and Segonds, S. and Teyssedre, G.},
Title={Numerical simulations for quantitative analysis of electrostatic interaction between atomic force microscopy probe and an embedded electrode within a thin dielectric: meshing optimization, sensitivity to potential distribution and impact of cantilever contribution},
Journal={Journal of Physics D - Applied Physics},
Month={february},
Volume={in press},
Number={},
Pages={},
Year={2018}}


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