TopoMS: Comprehensive topological exploration for molecular and condensed‐matter systems

We introduce TopoMS, a computational tool enabling detailed topological analysis of molecular and condensed‐matter systems, including the computation of atomic volumes and charges through the quantum theory of atoms in molecules, as well as the complete molecular graph. With roots in techniques from...

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Veröffentlicht in:Journal of computational chemistry 2018-06, Vol.39 (16), p.936-952
Hauptverfasser: Bhatia, Harsh, Gyulassy, Attila G., Lordi, Vincenzo, Pask, John E., Pascucci, Valerio, Bremer, Peer‐Timo
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Sprache:eng
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Zusammenfassung:We introduce TopoMS, a computational tool enabling detailed topological analysis of molecular and condensed‐matter systems, including the computation of atomic volumes and charges through the quantum theory of atoms in molecules, as well as the complete molecular graph. With roots in techniques from computational topology, and using a shared‐memory parallel approach, TopoMS provides scalable, numerically robust, and topologically consistent analysis. TopoMS can be used as a command‐line tool or with a GUI (graphical user interface), where the latter also enables an interactive exploration of the molecular graph. This paper presents algorithmic details of TopoMS and compares it with state‐of‐the‐art tools: Bader charge analysis v1.0 (Arnaldsson et al., 01/11/17) and molecular graph extraction using Critic2 (Otero‐de‐la‐Roza et al., Comput. Phys. Commun. 2014, 185, 1007). TopoMS not only combines the functionality of these individual codes but also demonstrates up to 4× performance gain on a standard laptop, faster convergence to fine‐grid solution, robustness against lattice bias, and topological consistency. TopoMS is released publicly under BSD License. © 2018 Wiley Periodicals, Inc. The QTAIM volumes corresponding to the atoms in a C2H4 molecule is extracted using TopoMS. The presented software, TopoMS, enables comprehensive topological analysis by also producing the complete molecular graph through numerically robust and scalable algorithms.
ISSN:0192-8651
1096-987X
DOI:10.1002/jcc.25181