Fractal Characteristics of the Pore Network in Diatomites Using Mercury Porosimetry and Image Analysis

2015 ◽  
pp. 79-89
Author(s):  
Grażyna Stańczak ◽  
Marek Rembiś ◽  
Beata Figarska-Warchoł ◽  
Tomasz Toboła
Keyword(s):  
Image Analysis ◽  
Mercury Porosimetry ◽  
Pore Network ◽  
Fractal Characteristics

Microstructure characterization of mullite foam by image analysis, mercury porosimetry and X-ray computed microtomography

2018 ◽  
Vol 44 (11) ◽  
pp. 12315-12328 ◽  
Author(s):  
Eva Gregorová ◽  
Tereza Uhlířová ◽  
Willi Pabst ◽  
Petra Diblíková ◽  
Ivona Sedlářová
Keyword(s):  
Image Analysis ◽  
Mercury Porosimetry ◽  
Microstructure Characterization ◽  
X Ray ◽  
Computed Microtomography ◽  
X Ray Computed

scholarly journals Quantification of Random Pore Structures of Porous Adsorbents

1991 ◽  
Vol 8 (4) ◽  
pp. 196-216 ◽  
Author(s):  
R. Mann ◽  
H.N.S. Yousef
Keyword(s):  
Image Analysis ◽  
Gas Adsorption ◽  
Mercury Porosimetry ◽  
Stochastic Networks ◽  
Random Pattern ◽  
Sem Images ◽  
Pore Networks ◽  
Fractal Surfaces ◽  
Pore Structures ◽  
Particulate Form

The structure of pore spaces in typical catalyst particles could often be described as being “not so much fabricated as thrown together”. Thus whilst for certain materials, such as zeolites, the microstructures are well defined and have a precise geometry, most materials when used in typical particulate form are at least partly composed of chaotically configured pore spaces. These random pore structures can be important in determining an adsorbent's performance, so it is necessary to define them quantitatively. A heirarchy of approaches based upon developments from simple stochastic pore networks is described. A stochastic pore network is one in which simple pore segments form interconnecting networks within which pores can be either randomly or partly randomly distributed. Such stochastic networks can be characterised by mercury porosimetry and low-temperature gas adsorption. Interconnectivity and randomness affect the degree of hysteresis for both these techniques. For 3-D random pattern stochastic networks, it is possible to interpret sectioned SEM images using ‘random’ slices of particles subject to low melting point alloy visual porosimetry in order to arrive at measures of random pore structure. This ‘image analysis’ approach is being extended to 3-D image reconstruction of SEM sections using fractal surfaces in conjunction with randomly tortuous pores.

Researches on Fractal Features of Graphite Porous Materials

2012 ◽  
Vol 507 ◽  
pp. 25-29 ◽  
Author(s):  
Qi Liu ◽  
Ya Fei Hu ◽  
Qi Li Wang
Keyword(s):  
Fractal Dimension ◽  
Pore Formation ◽  
Inflection Point ◽  
Pore Diameter ◽  
Mercury Porosimetry ◽  
Microscopic Structure ◽  
Fractal Characteristics ◽  
The One ◽  
Main Factor

The mercury porosimetry experiment has tested three different kinds of porosity graphite and the microscopic structure of impregnation antimony materials, and has calculated the corresponding fractal dimension by using the Menger model. The results show that: the main pore diameter of the graphite materials is in the interval of , most of which can be filled by impregnation antimony, and graphite and impregnation antimony materials both have the fractal characteristics. Graphite materials also have the dual fractal characteristics. Its fractal inflection point aperture is about 1μm, and the fractal dimension (3.05 ~ 3.25) of the small pores (φ≤1μm) is less than the one (3.71 ~ 3.95) of the large pores (φ>1μm). The reason why existing the dual fractal characteristics is that the size of the pore formation mechanism is different. Impregnation occurs mainly in the range of large pores, characteristics of which is an important factor to influence the quality of impregnation materials. The material formula is the main factor to influence the large pores and an important guarantee to improve the quality of impregnation products.

Fractal characteristics of coal samples utilizing image analysis and gas adsorption

Fuel ◽  
2016 ◽  
Vol 182 ◽  
pp. 314-322 ◽  
Author(s):  
Xianfeng Liu ◽  
Baisheng Nie
Keyword(s):  
Image Analysis ◽  
Gas Adsorption ◽  
Fractal Characteristics

Pore network quantification of sandstones under experimental CO2 injection using image analysis

2015 ◽  
Vol 77 ◽  
pp. 97-110 ◽  
Author(s):  
Edgar Berrezueta ◽  
Luís González-Menéndez ◽  
Berta Ordóñez-Casado ◽  
Peter Olaya
Keyword(s):  
Image Analysis ◽  
Pore Network ◽  
Co2 Injection
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