Simulations of Binary Mixture Adsorption of Carbon Dioxide and Methane in Carbon Nanotubes:  Temperature, Pressure, and Pore Size Effects

2007 ◽  
Vol 111 (32) ◽  
pp. 11912-11920 ◽  
Author(s):  
Liangliang Huang ◽  
Luzheng Zhang ◽  
Qing Shao ◽  
Linghong Lu ◽  
Xiaohua Lu ◽  
...  
Keyword(s):  
Carbon Dioxide ◽  
Carbon Nanotubes ◽  
Binary Mixture ◽  
Pore Size ◽  
Size Effects ◽  
Mixture Adsorption

A Combined Ab-Initio and Monte-Carlo Investigation of an Equimolar H2/He Mixture Adsorption in Silicon Nanotubes: Temperature, Pressure, and Pore Size Effects

2012 ◽  
Vol 9 (5) ◽  
pp. 737-744 ◽  
Author(s):  
Seyedehsaleheh Razavi ◽  
Seyed Majid Hashemianzadeh ◽  
Seyedehfatemeh Razavi ◽  
Sahra Balilehvand ◽  
Faramarz Yari ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Ab Initio ◽  
Pore Size ◽  
Size Effects ◽  
Silicon Nanotubes ◽  
Mixture Adsorption ◽  
Monte Carlo Investigation

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.

Carbon Dioxide/Nitrogen Separation Through Oxygenated Carbon Nanotubes‐Containing Polysulfone Membranes

2020 ◽  
Vol 394 (1) ◽  
pp. 2000058
Author(s):  
Marcelo Costa Flores ◽  
Kátia Cecília de Souza Figueiredo
Keyword(s):  
Carbon Dioxide ◽  
Carbon Nanotubes ◽  
Polysulfone Membranes
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