Spatial modeling of the 3D morphology of hybrid polymer-ZnO solar cells, based on electron tomography data

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

Hyperbranched Quasi-1D TiO2 Nanostructure for Hybrid Organic-Inorganic Solar Cells

The performance of hybrid solar cells is strongly affected by the device morphology. In this work we demonstrate a Poly(3-hexylthiophene-2,5-diyl)/TiO2 hybrid solar cell where the TiO2 photoanode comprises an array of tree-like hyperbranched quasi-1D nanostructures self-assembled from the gas phase. This advanced architecture enables us to increase the power conversion efficiency to over 1%, doubling the efficiency with respect to state of the art devices employing standard mesoporous titania photoanodes. This improvement is attributed to several peculiar features of this array of nanostructures: high interfacial area; increased optical density thanks to the enhanced light scattering; and enhanced crystallization of Poly(3-hexylthiophene-2,5-diyl) inside the quasi-1D nanostructure

Strukturelle Analyse des Porenraumes von Gasdiffusionslagen in Brennstoffzellen mittels geometrischer 3 D Graphen

Kurzfassung Eine wichtige Komponente von Polymer-Elektrolyt-Membran-Brennstoffzellen (PEMFC) ist die Gasdiffusionslage (GDL). Sie ist, unter anderem, für die Versorgung der Elektrode mit Reaktionsgasen sowie den Abtransport des entstehenden Wassers verantwortlich. Um einen optimalen Wirkungsgrad der Brennstoffzelle erzielen zu können und eine vorzeitige Alterung zu verhindern, ist eine konstante und gleichmäßige Versorgung der Elektrode mit Reaktionsgasen erforderlich. Dazu muss vor allem sichergestellt werden, dass das bei der Reaktion entstehende Wasser abtransportiert wird, um den Gastransport nicht zu behindern. Um diese Stofftransportprozesse, die im Porenraum der GDL stattfinden, besser verstehen zu können, untersuchen wir in der vorliegenden Arbeit die Struktur des Porenraumes basierend auf einer Graphen-Darstellung. Diese Darstellung des Porenraumes gewinnen wir aus 3-D Synchrotron-Daten mit Hilfe einer Skelettierung. In der vorliegenden Arbeit werden wir damit die Porenräume von zwei verschiedenen Typen von GDL (Papier-Typ und Vlies-Typ) strukturell untersuchen und deren Unterschiede quantitativ beschreiben.</jats:p

Random geometric graphs for modelling the pore space of fibre-based materials

A stochastic network model is developed which describes the 3D morphology of the pore space in fibre-based materials. It has the form of a random geometric graph, where the vertex set is modelled by random point processes and the edges are put using tools from graph theory and Markov chain Monte Carlo simulation. The model parameters are fitted to real image data gained by X-ray synchrotron tomography. In particular, they are specified in such a way that the distributions of vertex degrees and edge lengths, respectively, coincide to a large extent for real and simulated data. Furthermore, the network model is used to introduce a morphology-based notion of pores and their sizes. The model is validated by considering physical characteristics which are relevant for transport processes in the pore space, like geometric tortuosity, i.e., the distribution of shortest path lengths through the material relative to its thickness