A proposed 2D framework for estimation of pore size distribution by double pulsed field gradient NMR

2012 ◽  
Vol 137 (22) ◽  
pp. 224201 ◽  
Author(s):  
Dan Benjamini ◽  
Yaniv Katz ◽  
Uri Nevo
Keyword(s):  
Pore Size Distribution ◽  
Pore Size ◽  
Size Distribution ◽  
Field Gradient ◽  
Pulsed Field Gradient Nmr ◽  
Pulsed Field

Controlling Gas Selectivity in Molecular Porous Liquids by Tuning the Cage Window Size

2019 ◽  
Author(s):  
Benjamin Egleston ◽  
Konstantin V. Luzyanin ◽  
Michael C. Brand ◽  
Rob Clowes ◽  
Michael E. Briggs ◽  
...  
Keyword(s):  
Nmr Spectroscopy ◽  
Chemical Synthesis ◽  
Field Gradient ◽  
Window Size ◽  
Standard Approach ◽  
Porous Solids ◽  
Pulsed Field Gradient Nmr ◽  
Pulsed Field ◽  
Cage Molecules ◽  
Gas Selectivity

Control of pore window size is the standard approach for tuning gas selectivity in porous solids. Here, we present the first example where this is translated into a molecular porous liquid formed from organic cage molecules. Reduction of the cage window size by chemical synthesis switches the selectivity from Xe-selective to CH<sub>4</sub>-selective, which is understood using <sup>129</sup>Xe, <sup>1</sup>H, and pulsed-field gradient NMR spectroscopy.

Controlling Gas Selectivity in Molecular Porous Liquids by Tuning the Cage Window Size

2019 ◽  
Author(s):  
Benjamin Egleston ◽  
Konstantin V. Luzyanin ◽  
Michael C. Brand ◽  
Rob Clowes ◽  
Michael E. Briggs ◽  
...  
Keyword(s):  
Nmr Spectroscopy ◽  
Chemical Synthesis ◽  
Field Gradient ◽  
Window Size ◽  
Standard Approach ◽  
Porous Solids ◽  
Pulsed Field Gradient Nmr ◽  
Pulsed Field ◽  
Cage Molecules ◽  
Gas Selectivity

Control of pore window size is the standard approach for tuning gas selectivity in porous solids. Here, we present the first example where this is translated into a molecular porous liquid formed from organic cage molecules. Reduction of the cage window size by chemical synthesis switches the selectivity from Xe-selective to CH<sub>4</sub>-selective, which is understood using <sup>129</sup>Xe, <sup>1</sup>H, and pulsed-field gradient NMR spectroscopy.

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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