Feature-preserving Adaptive Mesh Generation for Molecular Modeling

نویسندگان

  • ZEYUN YU
  • MICHAEL HOLST
  • ANDREW MCCAMMON
چکیده

In this article we describe a mesh generation toolchain for molecular modeling. We take as inputs the centers and radii of all atoms of a molecule and the toolchain outputs both surface (triangular) and volumetric (tetrahedral) meshes. Experiments on a number of molecules are demonstrated, showing that our toolchain possesses a number of desirable properties: feature-preservation, local adaptivity, high quality (in various metrics), and smoothness (for surface meshes). Our tool is also applicable to other types of inputs such as scalar 3D volumes and triangular surface meshes with low quality, and hence can be used for generation/improvment of meshes in a broad range of applications.

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تاریخ انتشار 2007