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Published on: August 23, 2024
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Modelling of particle-laden flow inside nanomaterials
Yue Chan1, Jonathan J Wylie2, Liang Xia3
1School of Mathematical Sciences , University of Nottingham , 199 Taikang East Road, Ningbo 315100, People's Republic of China.
Proceedings. Mathematical, Physical, and Engineering Sciences
|September 13, 2016
Summary
This study uses the Nernst-Planck equation and mean-field theory to model flow-driven hydrogen storage in nanomaterials like graphene and graphene-oxide frameworks (GOFs). Findings reveal how flow velocity influences hydrogen layering and storage capacity within these nanostructures.
Area of Science:
- Multiscale modeling of nanomaterial-based gas storage.
- Computational physics and chemistry of porous materials.
Background:
- Existing nanoscale molecular encapsulation studies often neglect crucial macroscopic flow fields.
- Understanding flow dynamics is key to optimizing molecule confinement within nanostructures.
Purpose of the Study:
- To investigate flow-driven hydrogen storage in graphene and graphene-oxide frameworks (GOFs) using a multiscale approach.
- To analyze the impact of flow velocity and material structure on hydrogen encapsulation.
Main Methods:
- Application of the Nernst-Planck equation for macroscopic gas transport.
- Integration of molecular dynamics simulations and mean-field theory for molecular interactions.
- Investigation of hydrogen storage in doubly layered graphene sheets and GOFs.
Main Results:
- At low velocities, instantaneous monolayer formation on graphene, while GOFs form multilayers due to ligands.
- Higher velocities induce multilayer formation in graphene; complete filling occurs at even higher velocities.
- GOFs exhibit two voids per periodic unit at high velocities, with varying storage based on ligand density.
Conclusions:
- Macroscopic flow fields significantly impact hydrogen storage mechanisms in nanomaterials.
- Graphene and GOFs show distinct hydrogen storage behaviors influenced by their structure and flow conditions.
- The multiscale approach provides critical insights into optimizing gas encapsulation in nanostructures.
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