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September 2011 Spatial modeling of the 3D morphology of hybrid polymer-ZnO solar cells, based on electron tomography data
O. Stenzel, V. Schmidt, H. Hassfeld, R. Thiedmann, L. J. A. Koster, S. D. Oosterhout, S. S. van Bavel, M. M. Wienk, J. Loos, R. A. J. Janssen
Ann. Appl. Stat. 5(3): 1920-1947 (September 2011). DOI: 10.1214/11-AOAS468

Abstract

A spatial stochastic model is developed which describes the 3D nanomorphology of composite materials, being blends of two different (organic and inorganic) solid phases. Such materials are used, for example, in photoactive layers of hybrid polymer zinc oxide solar cells. The model is based on ideas from stochastic geometry and spatial statistics. Its parameters are fitted to image data gained by electron tomography (ET), where adaptive thresholding and stochastic segmentation have been used to represent morphological features of the considered ET data by unions of overlapping spheres. Their midpoints are modeled by a stack of 2D point processes with a suitably chosen correlation structure, whereas a moving-average procedure is used to add the radii of spheres. The model is validated by comparing physically relevant characteristics of real and simulated data, like the efficiency of exciton quenching, which is important for the generation of charges and their transport toward the electrodes.

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O. Stenzel. V. Schmidt. H. Hassfeld. R. Thiedmann. L. J. A. Koster. S. D. Oosterhout. S. S. van Bavel. M. M. Wienk. J. Loos. R. A. J. Janssen. "Spatial modeling of the 3D morphology of hybrid polymer-ZnO solar cells, based on electron tomography data." Ann. Appl. Stat. 5 (3) 1920 - 1947, September 2011. https://doi.org/10.1214/11-AOAS468

Information

Published: September 2011
First available in Project Euclid: 13 October 2011

zbMATH: 1228.62165
MathSciNet: MR2884927
Digital Object Identifier: 10.1214/11-AOAS468

Keywords: adaptive thresholding , exciton quenching , marked point process , model fitting , model validation , Parameter estimation , polymer solar cells , segmentation , simulation , spatial statistics , Stochastic geometry

Rights: Copyright © 2011 Institute of Mathematical Statistics

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Vol.5 • No. 3 • September 2011
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