Efficient and precise: Particle size and shape measurement with Dynamic Image Analysis

2012 ◽  
pp. 711-713
Author(s):  
Jörg Westermann
Keyword(s):  
Particle Size ◽  
Image Analysis ◽  
Shape Measurement ◽  
Dynamic Image ◽  
Size And Shape ◽  
Dynamic Image Analysis ◽  
Particle Size And Shape

scholarly journals An Experimental Study on the Particle Size and Shape Distribution of Coal Drill Cuttings by Dynamic Image Analysis

Geofluids ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Zhigang Zhang ◽  
Xiangyun Lan ◽  
Guangcai Wen ◽  
Qingming Long ◽  
Xuelin Yang
Keyword(s):  
Particle Size ◽  
Image Analysis ◽  
Particle Size Distribution ◽  
Size Distribution ◽  
Logarithmic Scale ◽  
Shape Distribution ◽  
Dynamic Image ◽  
Size And Shape ◽  
Dynamic Image Analysis ◽  
Particle Size And Shape

Particle size and shape distribution can be measured in great detail by dynamic image analysis (DIA). The narrow dispersion of repeated experiment results indicates that the particle size distribution can be obtained with high reliability. Particle size distribution can be better fitted to Rosin-Rammler equation than Gaudin-Schuhmann distribution and the lognormal distribution. The spread parameter ( m ) and the location parameters ( d 0 ) of the Rosin-Rammler equation can be calculated precisely. We analyzed the similarities and differences between the different particle shape distributions. The distributions of form factor and circularity are right-skewed distributions, while the distributions of ellipse ratio, irregularity, and aspect ratio obey a normal distribution. By studying the relation between particle size and shape, we find a linear relationship between the ellipse ratio and the Legendre ellipse diameter on the logarithmic scale.

Particle Size and Shape of Polytetrafluoroethylene (PTFE) powders using Static and Dynamic Image Analysis

2012 ◽  
Vol 18 (S2) ◽  
pp. 1244-1245 ◽  
Author(s):  
P. Bajaj ◽  
O. Guise
Keyword(s):  
Particle Size ◽  
Image Analysis ◽  
Dynamic Image ◽  
Size And Shape ◽  
Dynamic Image Analysis ◽  
Particle Size And Shape

Extended abstract of a paper presented at Microscopy and Microanalysis 2012 in Phoenix, Arizona, USA, July 29 – August 2, 2012.

Effect of Electron Microscope Magnification on the Determination of Particle Size and Shape by Image Analysis

2007 ◽  
Vol 121-123 ◽  
pp. 893-896
Author(s):  
Zheng Min Li
Keyword(s):  
Particle Size ◽  
Image Analysis ◽  
Standard Sample ◽  
Standard Specimen ◽  
Particle Diameter ◽  
Value Change ◽  
Size And Shape ◽  
Transmission Electron ◽  
Particle Size And Shape

To investigate the effect of magnification (M) on determination of particle size and shape by transmission electron microscopy (TEM) and image analysis. The calibration curve and its simulative equation of TEM magnification are obtained by measurement of a grating replica standard specimen at different magnifications. Based on the analysis of TEM images at a series of magnifications for a 350nm-sphere standard sample, It has been found that the two errors of its size measurement, caused by one pixel change of the pixel number per particle diameter (Np) and by one gray value change during thresholding, is smaller, and the shape of ‘circle’ particles are close to the standard one, while Np is larger than 35. It can be seen that the suitable TEM magnification is in inverse proportion to particle size and it can be calculated by given equation.

scholarly journals A NEW APPROACH FOR PARTICLE SIZE CHARACTERIZATION OF SOIL BASED ON DYNAMIC IMAGE ANALYSIS (DIA)

2019 ◽  
Vol 34 (4) ◽  
pp. 89-95
Author(s):  
Saman Tabrizi-Zarringhabaei ◽  
◽  
Reza Goli Ejlali ◽  
Mikaeil Yousefzadeh Fard ◽  
Sayyedjavad Sayyedfattahi ◽  
...  
Keyword(s):  
Particle Size ◽  
Image Analysis ◽  
New Approach ◽  
Dynamic Image ◽  
Size Characterization ◽  
Dynamic Image Analysis ◽  
Particle Size Characterization

Dextran-induced modifications of calcium carbonate particles precipitated during carbonatation

2019 ◽  
pp. 382-391
Author(s):  
Karin Abraham ◽  
Liza Splett ◽  
Eckhard Flöter
Keyword(s):  
Particle Size ◽  
Image Analysis ◽  
Calcium Carbonate ◽  
Filter Cake ◽  
Particle Size Analysis ◽  
Size Analysis ◽  
Shape Parameters ◽  
Size And Shape ◽  
Static Image ◽  
Particle Size And Shape

The effects of high and low molecular mass dextran (T2000 and T40) on the size and shape of particles precipitated during carbonatation and their correlation with filtration performances were key to this study. Varying contents of T2000 and T40 dextran in sugar solutions corresponding to DS contents of thin juice were investigated. For particle size and shape analysis, static image analysis and laser particle size analysis were used. Both methods, static image analysis and laser diffraction, revealed that the presence of T2000 and T40 dextran leads to a higher amount of large-sized particles at the expense of small-sized particles, indicating pronounced agglomeration. The additional evaluation of shape parameters (circularity, roundness, solidity) obtained from static image analysis indicates that the agglomeration is oriented in the absence and in the presence of lower T40 dextran levels. Besides, non-oriented agglomeration, resulting in more round agglomerates with smoother surfaces, was found for samples loaded with T2000 dextran and high T40 dextran levels. Only the latter samples have shown to negatively affect the filtration performance. Thus, in the presence of T2000 dextran and high T40 dextran levels, the filtration was hampered. This appears to be mainly caused by a tighter packing of more round calcium carbonate agglomerates in the porous structure of the filter cake.

scholarly journals Image analysis framework with focus evaluation for in situ characterisation of particle size and shape attributes

2018 ◽  
Vol 191 ◽  
pp. 208-231 ◽  
Author(s):  
Javier Cardona ◽  
Carla Ferreira ◽  
John McGinty ◽  
Andrew Hamilton ◽  
Okpeafoh S. Agimelen ◽  
...  
Keyword(s):  
Particle Size ◽  
Image Analysis ◽  
Analysis Framework ◽  
Size And Shape ◽  
Particle Size And Shape

Size and Shape Analysis of Sedimentary Grains by Automated Dynamic Image Analysis

2006 ◽  
Vol 23 (5) ◽  
pp. 381-387 ◽  
Author(s):  
Daisy Tysmans ◽  
Philippe Claeys ◽  
Luc Deriemaeker ◽  
Dominique Maes ◽  
Robert Finsy ◽  
...  
Keyword(s):  
Image Analysis ◽  
Shape Analysis ◽  
Dynamic Image ◽  
Size And Shape ◽  
Dynamic Image Analysis
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