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 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.
Original language | English |
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Article number | 075310 |
Journal | Materials Research Express |
Volume | 6 |
Issue number | 7 |
DOIs | |
Publication status | Published - 5 Apr 2019 |
Keywords
- agglomeration
- dispersion
- gap statistics
- image segmentation
- nanoparticles
ASJC Scopus subject areas
- Electronic, Optical and Magnetic Materials
- Biomaterials
- Surfaces, Coatings and Films
- Polymers and Plastics
- Metals and Alloys