Issue |
EPJ Photovolt.
Volume 10, 2019
|
|
---|---|---|
Article Number | 3 | |
Number of page(s) | 6 | |
Section | Bulk Silicon | |
DOI | https://doi.org/10.1051/epjpv/2019002 | |
Published online | 06 June 2019 |
https://doi.org/10.1051/epjpv/2019002
Regular Article
KPFM surface photovoltage measurement and numerical simulation
1
IPVF, Institut Photovoltaïque d'Île-de-France, 30 route Départementale 128, 91120 Palaiseau, France
2
GeePs, UMR CNRS 8507, Centralesupélec, Université Paris-Sud, Université Paris-Saclay, Sorbonne Université, 11 rue Joliot Curie, Plateau de Moulon, 91192 Gif sur Yvette, France
3
ISC-Konstanz e.V., Rudolf-Diesel-Straße 15, 78467 Konstanz, Germany
4
EDF R&D, 30 Route Départementale 128, 91120 Palaiseau, France
* e-mail: clement.marchat@ipvf.fr
Received:
13
November
2018
Received in final form:
26
March
2019
Accepted:
29
April
2019
Published online: 6 June 2019
A method for the analysis of Kelvin probe force microscopy (KPFM) characterization of semiconductor devices is presented. It enables evaluation of the influence of defective surface layers. The model is validated by analysing experimental KPFM measurements on crystalline silicon samples of contact potential difference (VCPD) in the dark and under illumination, and hence the surface photovoltage (SPV). It is shown that the model phenomenologically explains the observed KPFM measurements. It reproduces the magnitude of SPV characterization as a function of incident light power in terms of a defect density assuming Gaussian defect distribution in the semiconductor bandgap. This allows an estimation of defect densities in surface layers of semiconductors and therefore increased exploitation of KPFM data.
Key words: KPFM / SPV / surface defects / modeling and band bending
© C. Marchat et al., published by EDP Sciences, 2019
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.