2D-3D conversion method for assessment of multiple characteristics of particle shape and size

Abstract

Accurate assessment of three-dimensional (3D) particle characteristics, such as particle shape and size distribution, is a basic requirement in various fields. In practice, however, two-dimensional (2D) characteristics are often measured instead of 3D, due to limitations of cost, speed, and so on. A conversion method which simultaneously estimates multiple 3D characteristics from measurable multiple 2D counterparts is here proposed. Briefly, the method consists of the following steps: numerical creation of 3D particle models; computation of 3D and 2D parameter distributions of the model particles to establish a conversion database; and determination of the optimal combination of the 3D particle models to fit the measured 2D parameter distributions, using the genetic algorithm. The proposed method was validated by numerical examination using ellipsoidal particles with three grades of surface roughness. The method is novel in two respects: (i) versatility, as it is applicable to various types of particles, and (ii) convenience, as multiple parameters can be estimated at once; and it has the potential to be a fundamental technique in various fields dealing with particles, whether organic or inorganic, natural or artificial.