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Particle shape characterization from 2D images

机译:二维图像的颗粒形状表征

摘要

Three-dimensional (3D) shapes of particles are characterized from a two-dimensional (2D) image of the particles that is obtained using TEM. The 3D shape characterization method includes the steps of obtaining a 2D image of a batch of nanoparticles, determining 2D shapes of the nanoparticles from the 2D image, and deriving six distributions, each of which corresponds to a 2D shape and a 3D shape associated with the 2D shape. The first size distribution is derived from the nanoparticles having the 2D triangle shape. The second and third size distributions are derived from the nanoparticles having the 2D tetragon shape. The fourth, fifth and sixth size distributions are derived from the nanoparticles having the 2D round shape. Based on these six size distributions, three size distributions, each of which corresponds to one of three 3D shape classes, are estimated. The size distributions corresponding to the 3D shape classes provide a better log-normal distribution than the size distributions corresponding to the 2D shapes.
机译:颗粒的三维(3D)形状由使用TEM获得的颗粒的二维(2D)图像表征。 3D形状表征方法包括以下步骤:获得一批纳米颗粒的2D图像;从2D图像确定纳米颗粒的2D形状;以及推导六个分布,每个分布对应于2D形状和与3D形状相关的3D形状2D形状。第一尺寸分布源自具有2D三角形形状的纳米颗粒。第二和第三尺寸分布源自具有2D四边形形状的纳米颗粒。第四,第五和第六尺寸分布源自具有二维圆形的纳米颗粒。基于这六个尺寸分布,估计三个尺寸分布,每个尺寸分布对应于三个3D形状类别之一。对应于3D形状类别的尺寸分布比对应于2D形状的尺寸分布提供更好的对数正态分布。

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