ANANE-FENIN, Kwame; AKINLABI, Esther Tililabi; PERRY, Nicolas

doi:10.1088/2053-1591/ab1106

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ANANE-FENIN, Kwame
University of the Witwatersrand [Johannesburg] [WITS]

AKINLABI, Esther Tililabi
University of the Witwatersrand [Johannesburg] [WITS]

PERRY, Nicolas

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Materials Research Express. 2019-04-03, vol. 6, n° 7, p. 075310

IOP Publishing Ltd

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This study was prompted by the inadequacy of most dispersion quantification techniques to addressissues pertaining to scalability, implementation complexity, accuracy/error, uncertainty factors and versatility. Therefore, a method for quantifying dispersion based on gap statistics was developed. Adispersion quantity (D) was formulated from a Gap factor ( G 0 ) , Particle spacing dispersity (PSD 1 ) and Particle size dispersity (PSD 2 ) factors. The summation of the factors resulted in the dispersionparameter (D p ) which must be equal to one for an ideal or uniformly distributed condition. The stateof dispersion increases as D→100%. The concept was tested with simulated models having uniform dispersion, random dispersion, small aggregate, three large aggregate and one large aggregate were successfully quantified to show 99.34%, 82.42%, 34.17%, 8.95% and 3.65% respectively. For validation of concept, the state of dispersion when samples with (scenario 1) and without (scenario 4) silane treatment were quantified as 32,02% and 7.72% respectively. The concepts were then validated using real microscopy images. This approach is robust, versatile and easy to implement.< Réduire

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Polymers and Plastics

image segmentation

nanoparticles

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Quantification of nanoparticle dispersion within polymer matrix using gap statistics

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