Charles HansenVolume RenderingRay Tracing Graphics |
Valerio PascucciTopological MethodsData Streaming Big Data |
Chris JohnsonScalar, Vector, andTensor Field Visualization, Uncertainty Visualization |
Mike KirbyUncertainty Visualization |
Ross WhitakerTopological MethodsUncertainty Visualization |
Data Science: What Is It and How Is It Taught?, H. De Sterck, C.R. Johnson. In SIAM News, SIAM, July, 2015. |
Visualization C.R. Johnson, K. Potter. In The Princeton Companion to Applied Mathematics, Edited by Nicholas J. Higham, Princeton Unicersity Press, pp. 843-846. September, 2015. ISBN: 9780691150390 |
Morse-Smale Analysis of Ion Diffusion for DFT Battery Materials Simulations, A. Gyulassy, A. Knoll, K. C. Lau, Bei Wang, P. T. Bremer, M. E. Papka, L. A. Curtiss, V. Pascucci. Topology-Based Methods in Visualization (TopoInVis), 2015. Ab initio molecular dynamics (AIMD) simulations are increasingly useful in modeling, optimizing and synthesizing materials in energy sciences. In solving Schrodinger's equation, they generate the electronic structure of the simulated atoms as a scalar field. However, methods for analyzing these volume data are not yet common in molecular visualization. The Morse-Smale complex is a proven, versatile tool for topological analysis of scalar fields. In this paper, we apply the discrete Morse-Smale complex to analysis of first-principles battery materials simulations. We consider a carbon nanosphere structure used in battery materials research, and employ Morse-Smale decomposition to determine the possible lithium ion diffusion paths within that structure. Our approach is novel in that it uses the wavefunction itself as opposed distance fields, and that we analyze the 1-skeleton of the Morse-Smale complex to reconstruct our diffusion paths. Furthermore, it is the first application where specific motifs in the graph structure of the complete 1-skeleton define features, namely carbon rings with specific valence. We compare our analysis of DFT data with that of a distance field approximation, and discuss implications on larger classical molecular dynamics simulations. |
Topological and Statistical Methods for Complex Data, Subtitled “Tackling Large-Scale, High-Dimensional, and Multivariate Data Spaces,” J. Bennett, F. Vivodtzev, V. Pascucci (Eds.). Mathematics and Visualization, 2015. ISBN: 978-3-662-44899-1 This book contains papers presented at the Workshop on the Analysis of Large-scale, |