Details
| Original language | English |
|---|---|
| Pages (from-to) | 4741-4743 |
| Number of pages | 3 |
| Journal | Advanced materials |
| Volume | 22 |
| Issue number | 42 |
| Publication status | Published - 2 Nov 2010 |
Abstract
The predicted permeation selectivity of a binary gas mixture for a metal-organic framework ZIF-8 membrane was estimated from combined Grand Canonical Monte Carlo (GCMC) simulations and infrared microscopy (IRM) data and compared with permeation measurements on a ZIF-8 membrane. It is shown that membrane selectivity can be predicted and hence porous materials can be preselected for membrane applications thus saving time and effort in R&D.
Keywords
- Membrane, Metal-organic frameworks, Modeling
ASJC Scopus subject areas
- Materials Science(all)
- General Materials Science
- Engineering(all)
- Mechanics of Materials
- Engineering(all)
- Mechanical Engineering
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In: Advanced materials, Vol. 22, No. 42, 02.11.2010, p. 4741-4743.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - Novel MOF-membrane for molecular sieving predicted by IR-diffusion studies and molecular modeling
AU - Bux, Helge
AU - Chmelik, Christian
AU - Van Baten, Jasper M.
AU - Krishna, Rajamani
AU - Caro, Jürgen
PY - 2010/11/2
Y1 - 2010/11/2
N2 - The predicted permeation selectivity of a binary gas mixture for a metal-organic framework ZIF-8 membrane was estimated from combined Grand Canonical Monte Carlo (GCMC) simulations and infrared microscopy (IRM) data and compared with permeation measurements on a ZIF-8 membrane. It is shown that membrane selectivity can be predicted and hence porous materials can be preselected for membrane applications thus saving time and effort in R&D.
AB - The predicted permeation selectivity of a binary gas mixture for a metal-organic framework ZIF-8 membrane was estimated from combined Grand Canonical Monte Carlo (GCMC) simulations and infrared microscopy (IRM) data and compared with permeation measurements on a ZIF-8 membrane. It is shown that membrane selectivity can be predicted and hence porous materials can be preselected for membrane applications thus saving time and effort in R&D.
KW - Membrane
KW - Metal-organic frameworks
KW - Modeling
UR - http://www.scopus.com/inward/record.url?scp=78149419137&partnerID=8YFLogxK
U2 - 10.1002/adma.201002066
DO - 10.1002/adma.201002066
M3 - Article
C2 - 20814920
AN - SCOPUS:78149419137
VL - 22
SP - 4741
EP - 4743
JO - Advanced materials
JF - Advanced materials
SN - 0935-9648
IS - 42
ER -