Nanovol: A Volumetric Visualization and Analysis Framework for Chemical Materials Science

Aaron Knoll
Seminar

Modern materials and energy research is increasingly driven by computational chemistry. Ab initio computations produce atom geometry and scalar fields from which the wavefunction, or electron density clouds, can be directly visualized. Larger-scale phenomena are computed using classical molecular dynamics, consisting of atom geometry alone. Visualizing molecules as ball and stick is problematic for models with thousands of atoms or more. The biomolecular community has conventionally used abstractions such as molecular surfaces and ribbons to portray surface and structure, but these representations bear no direct relationship to electronic structure. In Nanovol, we propose a wholly volumetric means of visualizing and modeling material structures at Angstrom to micron scales, using either volume data computed in first-principles calculations or modeled from radial density distributions in bulk. We employ a physically-driven uncertainty classification technique for both volume rendering and analysis, allowing for estimation of material interfaces and boundaries while taking electron structure into account. Finally, we discuss problems with volumetric representation of molecular data, and how topological analyses may provide solutions.