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The current density-voltage characteristic (JV) is a critical tool for understanding the behaviour of solar cells. In this article, we present an overview of the key aspects of JV analysis and introduce a user-friendly flowchart that facilitates the swift identification of the most probable limiting process in a solar cell, based mainly on the outcomes of light-intensity-dependent JV measurements. The flowchart was developed through extensive drift-diffusion simulations and a rigorous review of the literature, with a specific focus on perovskite and organic solar cells. Moreover, the flowchart proposes supplementary experiments that can be conducted to obtain a more precise prediction of the primary performance losses. It therefore serves as an optimal starting point to analyse performance losses of solar cells., Comment: 50 pages (14 manuscript, 36 supporting information), 37 figures (5 main, 32 supporting information)

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., Comment: Published in at http://dx.doi.org/10.1214/11-AOAS468 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org)