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Informatics 2017, 4(3), 25; doi:10.3390/informatics4030025

Visual Analysis of Stochastic Trajectory Ensembles in Organic Solar Cell Design

1
Department of Science and Technology, Linköping University, 60174 Norrköping, Sweden
2
Department of Physics, Chemistry and Biology, Linköping University, 58183 Linköping, Sweden
3
Institute for Media Informatics, Ulm University, 89081 Ulm, Germany
*
Author to whom correspondence should be addressed.
Academic Editors: Gunther H. Weber and Achim Ebert
Received: 31 May 2017 / Revised: 24 July 2017 / Accepted: 26 July 2017 / Published: 1 August 2017
(This article belongs to the Special Issue Scalable Interactive Visualization)
View Full-Text   |   Download PDF [26005 KB, uploaded 1 August 2017]   |  

Abstract

We present a visualization system for analyzing stochastic particle trajectory ensembles, resulting from Kinetic Monte-Carlo simulations on charge transport in organic solar cells. The system supports the analysis of such trajectories in relation to complex material morphologies. It supports the inspection of individual trajectories or the entire ensemble on different levels of abstraction. Characteristic measures quantify the efficiency of the charge transport. Hence, our system led to better understanding of ensemble trajectories by: (i) Capturing individual trajectory behavior and providing an ensemble overview; (ii) Enabling exploration through linked interaction between 3D representations and plots of characteristics measures; (iii) Discovering potential traps in the material morphology; (iv) Studying preferential paths. The visualization system became a central part of the research process. As such, it continuously develops further along with the development of new hypothesis and questions from the application. Findings derived from the first visualizations, e.g., new efficiency measures, became new features of the system. Most of these features arose from discussions combining the data-perspective view from visualization with the physical background knowledge of the underlying processes. While our system has been built for a specific application, the concepts translate to data sets for other stochastic particle simulations. View Full-Text
Keywords: stochastic trajectory ensemble visualization; organic solar cell design; charge transport stochastic trajectory ensemble visualization; organic solar cell design; charge transport
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MDPI and ACS Style

Kottravel, S.; Volpi, R.; Linares, M.; Ropinski, T.; Hotz, I. Visual Analysis of Stochastic Trajectory Ensembles in Organic Solar Cell Design. Informatics 2017, 4, 25.

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