Why and how to tailor the vertical coordinate of pore size distribution to construct ORR-active carbon materials?

Nano Energy ◽  
2019 ◽  
Vol 58 ◽  
pp. 384-391 ◽  
Author(s):  
Yaling Zhao ◽  
Xiaoge Li ◽  
Xianbin Jia ◽  
Shuyan Gao
Keyword(s):  
Pore Size Distribution ◽  
Pore Size ◽  
Size Distribution ◽  
Active Carbon ◽  
Carbon Materials ◽  
Vertical Coordinate

scholarly journals Description of an Active Carbon Micropore Size Distribution Based on the Horvath—Kawazoe Equation Adapted to Benzene Adsorption Isotherms

1996 ◽  
Vol 14 (1) ◽  
pp. 59-67 ◽  
Author(s):  
A. Światkowski ◽  
B.J. Trznadel ◽  
S. Zietek
Keyword(s):  
Pore Size Distribution ◽  
Pore Size ◽  
Size Distribution ◽  
Active Carbon ◽  
Distribution Functions ◽  
Correction Factors ◽  
X Ray Scattering ◽  
Micropore Size ◽  
Carbon Micropore

The Horvath–Kawazoe equation has been used for the determination of the pore size distribution (PSD) of four fractions of active carbon separated by elutriation on the basis of their different degrees of activation. A comparison of the pore size distribution functions for argon and benzene as adsorbates has been undertaken. For both adsorbates, correction factors including the adsorption in mesopores have been evaluated. The influence of these corrections on the PSD functions has been discussed. Quantitative evaluations of the PSD functions for these two different adsorbates and a comparison with the results of small-angle X-ray scattering measurements leads to the conclusion that it is possible to use the benzene isotherm as well as those of other adsorbates.

scholarly journals Study on 3D Pore Characteristics of Carbon Materials in HTGR by Micro-CT and HPMI Methods

2019 ◽  
Vol 2019 ◽  
pp. 1-10
Author(s):  
Shengchao Ma ◽  
Zhenzhong Zhang ◽  
Kaiyue Shen ◽  
Xuedong He ◽  
Jun Li ◽  
...  
Keyword(s):  
Pore Size Distribution ◽  
Pore Size ◽  
Size Distribution ◽  
Carbon Materials ◽  
Gas Adsorption ◽  
Matrix Material ◽  
Structure Characteristic ◽  
Pore Characteristics ◽  
Corrosion Reaction ◽  
Special Points

Many tons of porous carbon materials (including BC and IG-110) are contained in HTGR, which are serving as structural material and fuel matrix material. These materials would absorb moisture and other impurities when exposed to the environment, and these impurities (especially moisture) absorbed in the carbon material must be removed before the reactor operation to prevent corrosion reaction at high temperature (more than 500°C). As the pore microscopic structure characteristic is the significant factor affecting the gas adsorption and flow in the porous materials, the detailed 3D pore structures of the carbon materials (BC and IG-110) in HTGR were studied by Micro-XCT and HPMI methods in this paper. These pore structure characteristics include pore geometry, pore size distribution, and pore throat connectivity. The test results show that the pore size distribution of BC material is wide, and the pore diameter is obviously larger than that of IG-110. Pore connections in BC show radial shape connections at some special points, and the pore connectivity in IG-110 is very complex and presents a huge complex 3D pore network.

Insensitivity in the pore size distribution of ultramicroporous carbon materials by CO2 adsorption

Carbon ◽  
2020 ◽  
Vol 168 ◽  
pp. 508-514
Author(s):  
V. Cornette ◽  
J. Villarroel-Rocha ◽  
K. Sapag ◽  
R. Delgado Mons ◽  
J.P. Toso ◽  
...  
Keyword(s):  
Pore Size Distribution ◽  
Pore Size ◽  
Size Distribution ◽  
Carbon Materials ◽  
Co2 Adsorption

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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