Repository logo

Infoscience

  • English
  • French
Log In
Logo EPFL, École polytechnique fédérale de Lausanne

Infoscience

  • English
  • French
Log In
  1. Home
  2. Academic and Research Output
  3. Journal articles
  4. Multipulsed Millisecond Ozone Gasification for Predictable Tuning of Nucleation and Nucleation-Decoupled Nanopore Expansion in Graphene for Carbon Capture
 
research article

Multipulsed Millisecond Ozone Gasification for Predictable Tuning of Nucleation and Nucleation-Decoupled Nanopore Expansion in Graphene for Carbon Capture

Hsu, Kuang-Jung  
•
Villalobos, Luis Francisco  
•
Huang, Shiqi  
Show more
July 28, 2021
ACS Nano

Predictable and tunable etching of angstrom-scale nanopores in single-layer graphene (SLG) can allow one to realize high-performance gas separation even from similar-sized molecules. We advance toward this goal by developing two etching regimes for SLG where the incorporation of angstrom-scale vacancy defects can be controlled. We screen several exposure profiles for the etchant, controlled by a multipulse millisecond treatment, using a mathematical model predicting the nucleation and pore expansion rates. The screened profiles yield a narrow pore-size-distribution (PSD) with a majority of defects smaller than missing 16 carbon atoms, suitable for CO2/N2 separation, attributing to the reduced pore expansion rate at a high pore density. Resulting nanoporous SLG (N-SLG) membranes yield attractive CO2 permeance of 4400 ± 2070 GPU and CO2/N2 selectivity of 33.4 ± 7.9. In the second etching regime, by limiting the supply of the etchant, the nanopores are allowed to expand while suppressing the nucleation events. Extremely attractive carbon capture performance marked with CO2 permeance of 8730 GPU, and CO2/N2 selectivity of 33.4 is obtained when CO2-selective polymeric chains are functionalized on the expanded nanopores. We show that the etching strategy is uniform and scalable by successfully fabricating high-performance centimeter-scale membrane.

  • Files
  • Details
  • Metrics
Loading...
Thumbnail Image
Name

acsnano.1c02927.pdf

Type

Publisher's Version

Version

Published version

Access type

openaccess

License Condition

CC BY-NC-ND

Size

6.4 MB

Format

Adobe PDF

Checksum (MD5)

2645b99d64c0299b10c5b3e9ee44c5ce

Logo EPFL, École polytechnique fédérale de Lausanne
  • Contact
  • infoscience@epfl.ch

  • Follow us on Facebook
  • Follow us on Instagram
  • Follow us on LinkedIn
  • Follow us on X
  • Follow us on Youtube
AccessibilityLegal noticePrivacy policyCookie settingsEnd User AgreementGet helpFeedback

Infoscience is a service managed and provided by the Library and IT Services of EPFL. © EPFL, tous droits réservés