DFT modeling of CO2 and Ar low-pressure adsorption for accurate nanopore structure characterization in organic-rich shales. (15th September 2017)
- Record Type:
- Journal Article
- Title:
- DFT modeling of CO2 and Ar low-pressure adsorption for accurate nanopore structure characterization in organic-rich shales. (15th September 2017)
- Main Title:
- DFT modeling of CO2 and Ar low-pressure adsorption for accurate nanopore structure characterization in organic-rich shales
- Authors:
- Zhang, Li
Xiong, Yongqiang
Li, Yun
Wei, Mingming
Jiang, Wenmin
Lei, Rui
Wu, Zongyang - Abstract:
- Graphical abstract: Highlights: A variety of models are applied to fit the experimental adsorption isotherms. Performance of low-pressure gas adsorption using different adsorbents. DFT-based CO2 –Ar analysis is the best method to characterize the pore structures of shales. Abstract: Low-pressure gas adsorption analysis based on density functional theory (DFT) or non-local DFT (NLDFT) has become an increasingly reliable method for the characterization of nanopore structures in porous materials. The accuracy of the characterization of nanoporous structures in organic-rich shales can be improved by using a variety of probe molecules and models: carbon dioxide, nitrogen, and argon are considered using the CO2 -DFT, N2 /Ar-DFT, N2 /Ar-NLDFT models and so on. Three types of shale sample with different maturity levels (i.e., mudstone, oil shale, and gas shale) are studied to investigate the effect of soluble components and maturity on the nanopore structure. The results show that the CO2 -DFT and N2 /Ar-DFT models are more suitable than the other models based on DFT or NLDFT and that composite CO2 –Ar adsorption analysis is the most accurate for assessing micro-, meso-, and macropores in the shales over the complete nanopore range (∼0.33–100 nm). The best method (i.e., DFT-based CO2 –Ar analysis) is applied to characterize the pore structures of original and extracted shales, revealing that solvent extraction can increase the total pore volume (i.e., micro-, meso-, and macropore).Graphical abstract: Highlights: A variety of models are applied to fit the experimental adsorption isotherms. Performance of low-pressure gas adsorption using different adsorbents. DFT-based CO2 –Ar analysis is the best method to characterize the pore structures of shales. Abstract: Low-pressure gas adsorption analysis based on density functional theory (DFT) or non-local DFT (NLDFT) has become an increasingly reliable method for the characterization of nanopore structures in porous materials. The accuracy of the characterization of nanoporous structures in organic-rich shales can be improved by using a variety of probe molecules and models: carbon dioxide, nitrogen, and argon are considered using the CO2 -DFT, N2 /Ar-DFT, N2 /Ar-NLDFT models and so on. Three types of shale sample with different maturity levels (i.e., mudstone, oil shale, and gas shale) are studied to investigate the effect of soluble components and maturity on the nanopore structure. The results show that the CO2 -DFT and N2 /Ar-DFT models are more suitable than the other models based on DFT or NLDFT and that composite CO2 –Ar adsorption analysis is the most accurate for assessing micro-, meso-, and macropores in the shales over the complete nanopore range (∼0.33–100 nm). The best method (i.e., DFT-based CO2 –Ar analysis) is applied to characterize the pore structures of original and extracted shales, revealing that solvent extraction can increase the total pore volume (i.e., micro-, meso-, and macropore). However, the effect is not obvious in overmature gas shale. Micropores in the three shales display favorable pore size distributions of 0.4–0.7, 0.7–0.9, and 1.0–2.0 nm, respectively. … (more)
- Is Part Of:
- Fuel. Volume 204(2017)
- Journal:
- Fuel
- Issue:
- Volume 204(2017)
- Issue Display:
- Volume 204, Issue 2017 (2017)
- Year:
- 2017
- Volume:
- 204
- Issue:
- 2017
- Issue Sort Value:
- 2017-0204-2017-0000
- Page Start:
- 1
- Page End:
- 11
- Publication Date:
- 2017-09-15
- Subjects:
- Nanoporous structures -- Organic-rich shales -- Carbon dioxide/argon adsorption -- DFT/NLDFT models -- Favorable pore size distributions
Fuel -- Periodicals
Coal -- Periodicals
Coal
Fuel
Periodicals
662.6 - Journal URLs:
- http://www.sciencedirect.com/science/journal/latest/00162361 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.fuel.2017.05.046 ↗
- Languages:
- English
- ISSNs:
- 0016-2361
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 4048.000000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 417.xml