Morse-Smale Analysis of Ion Diffusion in Ab Initio Battery Materials Simulations

Gyulassy, Attila; Knoll, Aaron; Lau, Kah Chun; Wang, Bei; Bremer, Peer-Timo; Papka, Michael; Curtiss, Larry A; Pascucci, Valerio

doi:10.1007/978-3-319-44684-4_8

Morse-Smale Analysis of Ion Diffusion in Ab Initio Battery Materials Simulations

Journal Article · Sat Jun 03 04:00:00 EDT 2017 · Topological Methods in Data Analysis and Visualization IV. TopoInVis 2015. Mathematics and Visualization

DOI:https://doi.org/10.1007/978-3-319-44684-4_8· OSTI ID:1370671

Gyulassy, Attila ^[1]; Knoll, Aaron ^[1]; Lau, Kah Chun ^[2]; Wang, Bei ^[1]; Bremer, Peer-Timo ^[3]; Papka, Michael ^[2]; Curtiss, Larry A ^[2]; Pascucci, Valerio ^[1]

Univ. of Utah, Salt Lake City, UT (United States)
Argonne National Lab. (ANL), Argonne, IL (United States)
Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

Ab initio molecular dynamics (AIMD) simulations are increasingly useful in modeling, optimizing and synthesizing materials in energy sciences. In solving Schrödinger’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.

Research Organization:: Energy Frontier Research Centers (EFRC) (United States). Center for Electrical Energy Storage (CEES)

Sponsoring Organization:: USDOE SC Office of Basic Energy Sciences (SC-22)

DOE Contract Number:: AC02-06CH11357

OSTI ID:: 1370671

Journal Information:: Topological Methods in Data Analysis and Visualization IV. TopoInVis 2015. Mathematics and Visualization, Journal Name: Topological Methods in Data Analysis and Visualization IV. TopoInVis 2015. Mathematics and Visualization

Publisher:: Springer, Cham; Carr H., Garth C., Weinkauf T. (eds)

Country of Publication:: United States

Language:: English

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