Quantification of nanoparticle dispersion within polymer matrix using gap statistics. (5th April 2019)

• Record Type: Journal Article
• Authors: Anane-Fenin, K; Akinlabi, E T; Perry, N
• Is Part Of: Materials research express. Volume 6:Number 7(2019)
• Publication Date: 2019-04-05
• Subjects: agglomeration -- dispersion -- gap statistics -- image segmentation -- nanoparticles; Materials science -- Research -- Periodicals; Materials science -- Periodicals; 620.11
• DOI: 10.1088/2053-1591/ab1106
• Languages: English
• ISSNs: 2053-1591

Abstract

Abstract: This study was prompted by the inadequacy of most dispersion quantification techniques to address issues pertaining to scalability, implementation complexity, accuracy/error, uncertainty factors and versatility. Therefore, a method for quantifying dispersion based on gap statistics was developed. A dispersion 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 dispersion parameter ( D p ) which must be equal to one for an ideal or uniformly distributed condition. The state of 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.