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Quantifying nanoparticle dispersion by using the area disorder of Delaunay triangulation
Author(s) -
Bray David J.,
Gilmour Steven G.,
Guild Felicity J.,
Taylor Ambrose C.
Publication year - 2012
Publication title -
journal of the royal statistical society: series c (applied statistics)
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.205
H-Index - 72
eISSN - 1467-9876
pISSN - 0035-9254
DOI - 10.1111/j.1467-9876.2011.01009.x
Subject(s) - delaunay triangulation , dispersion (optics) , measure (data warehouse) , computer science , point (geometry) , categorization , homogeneous , artificial intelligence , materials science , statistical physics , mathematics , data mining , algorithm , optics , geometry , physics
Summary. Characterizing the quality of dispersion of nanocomposites presents a challenging statistical problem for which no direct method has been fully adopted. A high precision, statistically well‐grounded measure is required which is suitable for dealing with a single small non‐homogeneous particle pattern obtained from the material. Our approach uses the Delaunay network of particles to measure the area disorder AD Del , which can be further used to categorize a material sample into well or poorly dispersed. AD Del ‐analysis is applied to several micrographs of nanoparticle‐modified materials and found to classify the type of dispersion reliably. Selected spatial point processes are employed to estimate expected imprecision in observed measurements.