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Persistent Homology to Quantify the Quality of Surface‐Supported Covalent Networks
Author(s) -
Gutierrez Abraham,
Buchet Mickaël,
Clair Sylvain
Publication year - 2019
Publication title -
chemphyschem
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.016
H-Index - 140
eISSN - 1439-7641
pISSN - 1439-4235
DOI - 10.1002/cphc.201900257
Subject(s) - covalent bond , homogeneity (statistics) , atomic force microscopy , computation , homology (biology) , persistent homology , materials science , computer science , spanning tree , biological system , nanotechnology , chemistry , algorithm , mathematics , machine learning , biology , combinatorics , biochemistry , amino acid , organic chemistry
Covalent networks formed by on‐surface synthesis usually suffer from the presence of a large number of defects. We report on a methodology to characterize such two‐dimensional networks from their experimental images obtained by scanning probe microscopy. The computation is based on a persistent homology approach and provides a quantitative score indicative of the network homogeneity. We compare our scoring method with results previously obtained using minimal spanning tree analyses and we apply it to some molecular systems appearing in the existing literature.