New Measuring Instrument for Pore Size Distribution by the Capillary Condensation/Nano-Perm Porometer

In order to provide the wetting processing and the design of thermal moisture comfort of fabric with micron-scaled pore size data, this paper reports on an experimental investigation on the pore size distribution of 6 kinds of fabrics with the method of seft-proposed weight-classification method. This paper focuses on the effect of fabric structure and component on the pore size distribution . Histograms reveal the relationship between various factors. For cotton fabric, the peak area of the histogram of 1/2 twill weave fabric (TWF) is wider and higher than that of plain weave fabric (PWF) due to fewer structure points and more loose structure. This leads to wicking rate increase. For the polyester fabric, the difference between the peak area shapes of the TWF and PWF is not obvious. This may arise from that smaller warp/weft density of both the samples inhibited by the change in inter-yarn gap leading to the similarity. For polyester-cotton fabric, with the increase in the ratio of hydrophilic cotton component, pore size range significantly expanded, showing more uniform wicking and capillary condensation.

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Studies on pore structure of adsorbents and catalysts II. Pore size distribution in synthetic chrysotile: the classical and corrected kelvin equation applied to nitrogen capillary condensation

Journal of Catalysis ◽

10.1016/0021-9517(75)90006-8 ◽

1975 ◽

Vol 36 (1) ◽

pp. 30-35 ◽

Cited By ~ 16

Author(s):

L DEWIT

Keyword(s):

Pore Structure ◽

Pore Size Distribution ◽

Pore Size ◽

Size Distribution ◽

Capillary Condensation ◽

Kelvin Equation

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A Novel Method for Analyzing Pore Size Distribution of Complex Geometry Shaped Porous Shale

Materials Science Forum ◽

10.4028/www.scientific.net/msf.1003.134 ◽

2020 ◽

Vol 1003 ◽

pp. 134-143

Author(s):

Yang Ming ◽

Lin Mian

Keyword(s):

Porous Media ◽

Pore Size Distribution ◽

Pore Size ◽

Size Distribution ◽

Complex Geometry ◽

Capillary Condensation ◽

Relative Pressure ◽

Differential Function ◽

Novel Method

This article proposes the differential BJH equation based on the principles of multilayer adsorption and capillary condensation, which was simplified by theoretical investigation and experiments. This work indicates that the differential function of isotherm and the differential function of pore size to relative pressure determine the pore size distribution of porous media. The differential BJH model can be used to explain the source of the false peak in pore size distribution and to calculate the pore size distribution of different shapes of pores in a porous media with a porous structure. It has an excellent application prospect in the characterization of complex pore structure represented by shale.

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A New Model for Capillary Condensation−Evaporation Hysteresis Based on a Random Corrugated Pore Structure Concept: Prediction of Intrinsic Pore Size Distribution. 2. Model Application

Industrial & Engineering Chemistry Research ◽

10.1021/ie000163w ◽

2000 ◽

Vol 39 (10) ◽

pp. 3764-3777 ◽

Cited By ~ 25

Author(s):

G. P. Androutsopoulos ◽

C. E. Salmas

Keyword(s):

Pore Structure ◽

Pore Size Distribution ◽

Pore Size ◽

Size Distribution ◽

Capillary Condensation ◽

Model Application ◽

New Model

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PORE SIZE DISTRIBUTION OF MICRO-MESOPOROUS ADSORBENTS DETERMINED BY MEANS OF THE MULTILAYERING AND CAPILLARY CONDENSATION THEORY

Adsorption Science and Technology ◽

10.1142/9789812793331_0040 ◽

2000 ◽

Author(s):

C. NGUYEN ◽

D. D. DO

Keyword(s):

Pore Size Distribution ◽

Pore Size ◽

Size Distribution ◽

Capillary Condensation

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

10.26434/chemrxiv.7970402.v1 ◽

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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