Proper Characterisation of Pore Size Distribution in Cementitious Materials

2006 ◽  
pp. 479-485 ◽  
Author(s):  
J. Hu ◽  
Piet Stroeven
Keyword(s):  
Pore Size Distribution ◽  
Pore Size ◽  
Size Distribution ◽  
Cementitious Materials

scholarly journals Effect of High-Dispersible Graphene on the Strength and Durability of Cement Mortars

Materials ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 915
Author(s):  
Xiaoqiang Qi ◽  
Sulei Zhang ◽  
Tengteng Wang ◽  
Siyao Guo ◽  
Rui Ren
Keyword(s):  
Pore Size Distribution ◽  
Pore Size ◽  
Size Distribution ◽  
Cement Mortar ◽  
Chloride Ion ◽  
Cementitious Materials ◽  
Chloride Ion Penetration ◽  
Cement Mortars ◽  
Strength And Durability ◽  
Durability Performance

Graphene’s outstanding properties make it a potential material for reinforced cementitious composites. However, its shortcomings, such as easy agglomeration and poor dispersion, severely restrict its application in cementitious materials. In this paper, a highly dispersible graphene (TiO2-RGO) with better dispersibility compared with graphene oxide (GO) is obtained through improvement of the graphene preparation method. In this study, both GO and TiO2-RGO can improve the pore size distribution of cement mortars. According to the results of the mercury intrusion porosity (MIP) test, the porosity of cement mortar mixed with GO and TiO2-RGO was reduced by 26% and 40%, respectively, relative to ordinary cement mortar specimens. However, the TiO2-RGO cement mortars showed better pore size distribution and porosity than GO cement mortars. Comparative tests on the strength and durability of ordinary cement mortars, GO cement mortars, and TiO2-RGO cement mortars were conducted, and it was found that with the same amount of TiO2-RGO and GO, the TiO2-RGO cement mortars have nearly twice the strength of GO cement mortars. In addition, it has far higher durability, such as impermeability and chloride ion penetration resistance, than GO cement mortars. These results indicate that TiO2-RGO prepared by titanium dioxide (TiO2) intercalation can better improve the strength and durability performance of cement mortars compared to GO.

scholarly journals Ink-bottle Effect and Pore Size Distribution of Cementitious Materials Identified by Pressurization–Depressurization Cycling Mercury Intrusion Porosimetry

Materials ◽  
2019 ◽  
Vol 12 (9) ◽  
pp. 1454 ◽  
Author(s):  
Yong Zhang ◽  
Bin Yang ◽  
Zhengxian Yang ◽  
Guang Ye
Keyword(s):  
Pore Structure ◽  
Pore Size Distribution ◽  
Pore Size ◽  
Size Distribution ◽  
Mercury Intrusion Porosimetry ◽  
Cementitious Materials ◽  
Limestone Powder ◽  
Accurate Estimation ◽  
Mercury Intrusion ◽  
Pore Size Distributions

Capturing the long-term performance of concrete must be underpinned by a detailed understanding of the pore structure. Mercury intrusion porosimetry (MIP) is a widely used technique for pore structure characterization. However, it has been proven inappropriate to measure the pore size distribution of cementitious materials due to the ink-bottle effect. MIP with cyclic pressurization–depressurization can overcome the ink-bottle effect and enables a distinction between large (ink-bottle) pores and small (throat) pores. In this paper, pressurization–depressurization cycling mercury intrusion porosimetry (PDC-MIP) is adopted to characterize the pore structure in a range of cementitious pastes cured from 28 to 370 days. The results indicate that PDC-MIP provides a more accurate estimation of the pore size distribution in cementitious pastes than the standard MIP. Bimodal pore size distributions can be obtained by performing PDC-MIP measurements on cementitious pastes, regardless of the age. Water–binder ratio, fly ash and limestone powder have considerable influences on the formation of capillary pores ranging from 0.01 to 0.5 µm.

scholarly journals POROSIMETRY BY RANDOM NODE STRUCTURING IN VIRTUAL CONCRETE

2012 ◽  
Vol 31 (2) ◽  
pp. 79 ◽  
Author(s):  
Piet Stroeven ◽  
Nghi L.B. Le ◽  
Lambertus J Sluys ◽  
Huan He
Keyword(s):  
Pore Size Distribution ◽  
Pore Size ◽  
Size Distribution ◽  
Pore Space ◽  
Cementitious Materials ◽  
Discrete Element Modeling ◽  
Concurrent Algorithm ◽  
Random Node ◽  
Volume Measurements ◽  
3D Information

Two different porosimetry methods are presented in two successive papers. Inspiration for the development came from the rapidly-exploring random tree (RRT) approach used in robotics. The novel methods are applied to virtual cementitious materials produced by a modern concurrent algorithm-based discrete element modeling system, HADES. This would render possible realistically simulating all aspects of particulate matter that influence structure-sensitive features of the pore network structure in maturing concrete, namely size, shape and dispersion of the aggregate and cement particles. Pore space is a complex tortuous entity. Practical methods conventionally applied for assessment of pore size distribution may fail or present biased information. Among them, mercury intrusion porosimetry and 2D quantitative image analysis are popular. The mathematical morphology operator “opening” can be applied to sections and even provide 3D information on pore size distribution, provided isotropy is guaranteed. However, aggregate grain surfaces lead to anisotropy in porosity. The presented methods allow exploration of pore space in the virtual material, after which pore size distribution is derived from star volume measurements. In addition to size of pores their continuity is of crucial importance for durability estimation. Double-random multiple tree structuring (DRaMuTS), introduced earlier in IA&S (Stroeven et al., 2011b) and random node structuring (RaNoS) provide such information.

POROSIMETRY BY DOUBLE-RANDOM MULTIPLE TREE STRUCTURING IN VIRTUAL CONCRETE

2012 ◽  
Vol 31 (1) ◽  
pp. 55 ◽  
Author(s):  
Piet Stroeven ◽  
Nghi L.B. Le ◽  
Lambertus J Sluys ◽  
Huan He
Keyword(s):  
Pore Size Distribution ◽  
Pore Size ◽  
Size Distribution ◽  
Pore Space ◽  
Cementitious Materials ◽  
Discrete Element Modeling ◽  
Random Node ◽  
Volume Measurements ◽  
3D Information ◽  
Multiple Tree

Two different porosimetry methods are presented in two successive papers. Inspiration for the development came from the rapidly-exploring random tree (RRT) approach used in robotics. The novel methods are applied to virtual cementitious materials produced by a modern concurrent algorithm-based discrete element modeling system, HADES. This would render possible realistically simulating all aspects of particulate matter that influence structure-sensitive features of the pore network structure in maturing concrete, namely size, shape and dispersion of aggregate and cement particles. Pore space is a complex tortuous entity. Practical methods conventionally applied for assessment of pore size distribution may fail or present biased information. Among them, mercury intrusion porosimetry and 2D quantitative image analysis are popular. The mathematical morphology operator “opening” can be applied to sections and even provide 3D information on pore size distribution, provided isotropy is guaranteed. Unfortunately, aggregate grain surfaces lead to pore anisotropy. The presented methods allow exploration of pore space in the virtual material, after which pore size distribution is derived from star volume measurements.  In addition to size of pores their continuity is of crucial importance for durability estimation. Double-random multiple tree structuring (DRaMuTS), presented herein, and random node structuring (RaNoS) provide such information. The latter method will be introduced in a next issue of IA&S.

Proper Characterisation of Pore Size Distribution in Cementitious Materials

2006 ◽  
Vol 302-303 ◽  
pp. 479-485 ◽  
Author(s):  
J. Hu ◽  
Piet Stroeven
Keyword(s):  
Pore Size Distribution ◽  
Pore Size ◽  
Size Distribution ◽  
Mercury Intrusion Porosimetry ◽  
Structural Information ◽  
Cementitious Materials ◽  
Comparison Study ◽  
Cement Pastes ◽  
Mercury Intrusion ◽  
Mathematic Morphology

In this paper, a mathematic morphology measurement with the name of opening operation was applied to section images for the assessment of pore size distribution in cement pastes. This method is compared with other methods for characterising pore size distribution, including the experimental technique of mercury intrusion porosimetry, the conventional image analysis by area histogram and a direct approach by a simulation model. The comparison study reveals that the so-called opening distribution technique yields realistic structural information of pore size distribution in cement pastes. The proper characterisation of pore size distribution is of significant importance to permeability prediction of cementitious materials and thereby to durability studies of the materials.

pyGAPS: A Python-Based Framework for Adsorption Isotherm Processing and Material Characterisation

2019 ◽  
Author(s):  
Paul Iacomi ◽  
Philip L. Llewellyn
Keyword(s):  
Pore Size Distribution ◽  
Pore Size ◽  
Size Distribution ◽  
Surface Area ◽  
Isosteric Heat ◽  
Material Characterisation ◽  
Mixture Adsorption ◽  
Surface Energetics ◽  
Adsorption Processing ◽  
User Friendly

Material characterisation through adsorption is a widely-used laboratory technique. The isotherms obtained through volumetric or gravimetric experiments impart insight through their features but can also be analysed to determine material characteristics such as specific surface area, pore size distribution, surface energetics, or used for predicting mixture adsorption. The pyGAPS (python General Adsorption Processing Suite) framework was developed to address the need for high-throughput processing of such adsorption data, independent of the origin, while also being capable of presenting individual results in a user-friendly manner. It contains many common characterisation methods such as: BET and Langmuir surface area, t and α plots, pore size distribution calculations (BJH, Dollimore-Heal, Horvath-Kawazoe, DFT/NLDFT kernel fitting), isosteric heat calculations, IAST calculations, isotherm modelling and more, as well as the ability to import and store data from Excel, CSV, JSON and sqlite databases. In this work, a description of the capabilities of pyGAPS is presented. The code is then be used in two case studies: a routine characterisation of a UiO-66(Zr) sample and in the processing of an adsorption dataset of a commercial carbon (Takeda 5A) for applications in gas separation.

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