Visual Analysis of Charge Flow Networks for Complex Morphologies

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dc.contributor.authorKottravel, Sathishen_US
dc.contributor.authorFalk, Martinen_US
dc.contributor.authorBin Masood, Talhaen_US
dc.contributor.authorlinares, mathieuen_US
dc.contributor.authorHotz, Ingriden_US
dc.contributor.editorGleicher, Michael and Viola, Ivan and Leitte, Heikeen_US
dc.date.accessioned2019-06-02T18:28:29Z
dc.date.available2019-06-02T18:28:29Z
dc.date.issued2019
dc.description.abstractIn the field of organic electronics, understanding complex material morphologies and their role in efficient charge transport in solar cells is extremely important. Related processes are studied using the Ising model and Kinetic Monte Carlo simulations resulting in large ensembles of stochastic trajectories. Naive visualization of these trajectories, individually or as a whole, does not lead to new knowledge discovery through exploration. In this paper, we present novel visualization and exploration methods to analyze this complex dynamic data, which provide succinct and meaningful abstractions leading to scientific insights. We propose a morphology abstraction yielding a network composed of material pockets and the interfaces, which serves as backbone for the visualization of the charge diffusion. The trajectory network is created using a novel way of implicitly attracting the trajectories to the skeleton of the morphology relying on a relaxation process. Each individual trajectory is then represented as a connected sequence of nodes in the skeleton. The final network summarizes all of these sequences in a single aggregated network. We apply our method to three different morphologies and demonstrate its suitability for exploring this kind of data.en_US
dc.description.number3
dc.description.sectionheadersSpatial Data Applications
dc.description.seriesinformationComputer Graphics Forum
dc.description.volume38
dc.identifier.doi10.1111/cgf.13704
dc.identifier.issn1467-8659
dc.identifier.pages479-489
dc.identifier.urihttps://doi.org/10.1111/cgf.13704
dc.identifier.urihttps://diglib.eg.org:443/handle/10.1111/cgf13704
dc.publisherThe Eurographics Association and John Wiley & Sons Ltd.en_US
dc.subjectHuman
dc.subjectcentered computing
dc.subjectScientific visualization
dc.subjectComputing methodologies
dc.subjectDiscrete
dc.subjectevent simulation
dc.subjectApplied computing
dc.subjectPhysical sciences and engineering
dc.titleVisual Analysis of Charge Flow Networks for Complex Morphologiesen_US
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