Synthesis of nanoporous carbon with controlled pore size distribution and examination of its accessibility for electric double layer formation

2008 ◽  
Vol 111 (1-3) ◽  
pp. 307-313 ◽  
Author(s):  
Z.M. Sheng ◽  
J.N. Wang ◽  
J.C. Ye
Keyword(s):  
Pore Size Distribution ◽  
Pore Size ◽  
Size Distribution ◽  
Double Layer ◽  
Electric Double Layer ◽  
Nanoporous Carbon ◽  
Layer Formation

Kinetics of Double-Layer Formation: Influence of Porous Structure and Pore Size Distribution†

2010 ◽  
Vol 24 (6) ◽  
pp. 3378-3384 ◽  
Author(s):  
M. J. Bleda-Martínez ◽  
D. Lozano-Castelló ◽  
D. Cazorla-Amorós ◽  
E. Morallón
Keyword(s):  
Porous Structure ◽  
Pore Size Distribution ◽  
Pore Size ◽  
Size Distribution ◽  
Double Layer ◽  
Layer Formation ◽  
Kinetics Of

Facile simulation of carbon with wide pore size distribution for electric double-layer capacitance based on Helmholtz models

2015 ◽  
Vol 3 (32) ◽  
pp. 16535-16543 ◽  
Author(s):  
Wei Hsieh ◽  
Tzyy-Leng Allen Horng ◽  
Hsin-Chieh Huang ◽  
Hsisheng Teng
Keyword(s):  
Pore Size Distribution ◽  
Pore Size ◽  
Size Distribution ◽  
Double Layer ◽  
Density Functional ◽  
Local Density ◽  
Double Layer Capacitance ◽  
Local Density Functional Theory ◽  
Non Local ◽  
Forms Of Carbon

Incorporation of surface-based capacitances (C/S) simulated by Helmholtz models with pore size distribution obtained from the non-local density functional theory precisely predicts the double-layer capacitance of distinct forms of carbon.

Water Adsorption in Nanoporous Carbon Characterized by in Situ NMR: Measurements of Pore Size and Pore Size Distribution

2014 ◽  
Vol 118 (16) ◽  
pp. 8474-8480 ◽  
Author(s):  
Hai-Jing Wang ◽  
Alfred Kleinhammes ◽  
Thomas P. McNicholas ◽  
Jie Liu ◽  
Yue Wu
Keyword(s):  
Pore Size Distribution ◽  
Pore Size ◽  
Size Distribution ◽  
Water Adsorption ◽  
Nanoporous Carbon ◽  
In Situ Nmr

Effect of pore size distribution of coal-based activated carbons on double layer capacitance

2005 ◽  
Vol 50 (5) ◽  
pp. 1197-1206 ◽  
Author(s):  
Grażyna Gryglewicz ◽  
Jacek Machnikowski ◽  
Ewa Lorenc-Grabowska ◽  
Grzegorz Lota ◽  
Elzbieta Frackowiak
Keyword(s):  
Pore Size Distribution ◽  
Pore Size ◽  
Size Distribution ◽  
Double Layer ◽  
Activated Carbons ◽  
Double Layer Capacitance

scholarly journals Structure and Pore Size Distribution in Nanoporous Carbon

2022 ◽  
Author(s):  
Yanzhou Wang ◽  
Zheyong Fan ◽  
Ping Qian ◽  
Tapio Ala-Nissila ◽  
Miguel A. Caro
Keyword(s):  
Pore Size Distribution ◽  
Pore Size ◽  
Size Distribution ◽  
Nanoporous Carbon

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.

Sign in / Sign up

Export Citation Format

Share Document