Charge-flow network for interactive exploration of data from organic solar cell simulations
Figure: Overview of our charge flow network pipeline. Given the raw data, the pipeline generates the network abstraction and network visualization.
In 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. Naïve visualization of these trajectories, individually or as a whole is not sufficient to understand the data. We developed novel visualization and exploration methods to analyze this complex dynamic data, which provide succinct and meaningful abstractions leading to scientific insights. Thereby a morphology abstraction yields a network composed of material pockets and interfaces, which serves as backbone for the visualization of the charge diffusion. Each individual trajectory can then be represented as a sequence of nodes in the skeleton. The final network thus summarizes all sequences in a single aggregated network.
Reference: Visual Analysis of Charge Flow Network for Complex Morphologies. S Kottravel, M.Falk, T Bin Masood, M. Linares and I. Hotz. Computer Graphics Forum (EuroVis’19). 2019