(426a) Development and Application of an Advanced Percolation Model for Pore Network Characterization By Physical Adsorption
AIChE Annual Meeting
2024
2024 AIChE Annual Meeting
Separations Division
Characterization of Adsorbent Materials
Tuesday, October 29, 2024 - 3:30pm to 3:51pm
Physical adsorption is one of the most widely used techniques to characterize porous materials because
of being reliable and able to assess micro- and mesopores within one approach. However, challenges
and open questions persist in characterizing disordered and hierarchically structured porous materials.
This study introduces a pore network model aiming to enhance the textural characterization of
nanoporous materials. Our model, based on percolation theory on a Bethe lattice, includes all
mechanisms known to contribute to adsorption hysteresis in mesoporous pore networks during capillary
condensation and evaporation. The model accounts for delayed and initiated condensation during
adsorption as well as equilibrium evaporation, pore blocking and cavitation during desorption. Coupled
with dedicated non-local-density functional theory (NLDFT) kernels, the proposed method provides a
unified framework for modeling the entire experimental adsorption-desorption isotherm, including
desorption hysteresis scans. Hence, this model unveils key pore network characteristics like the effective
connectivity, but also has the potential to determine pore size distributions of mesoporous materials by
taking quantitatively pore network effects into account. The applicability of the method is demonstrated
on a selected set of nanoporous silica materials exhibiting distinct types of hysteresis loops (types H1,
H2a, H1/H2a and H5), including ordered mesoporous silica networks, i.e, KIT-6 silica, hybrid SBA-
15/MCM-41 silica with plugged pores, but also two disordered silica pore networks, i.e., a hierarchical
meso-macroporous monolith and porous Vycor glass. For all materials, good correlation is found
between calculated and experimental primary adsorption and desorption isotherms as well as desorption
scans allowing for a determination of key pore network characteristics such as pore connectivity and
pore size distributions as well as a parameter correlated with the impact of pore network disorder and
corresponding effects on the adsorption behavior. The versatility and enriched textural insights provided
by the proposed novel network model allows for a comprehensive characterization previously
inaccessible, and hence will contribute to a further advancement in the textural characterization of novel
nanoporous materials. It has the potential to provide important guidance for the design and selection of
porous materials for optimising various applications, including separation processes (such as
chromatography), heterogeneous catalysis, gas-and energy storage.
of being reliable and able to assess micro- and mesopores within one approach. However, challenges
and open questions persist in characterizing disordered and hierarchically structured porous materials.
This study introduces a pore network model aiming to enhance the textural characterization of
nanoporous materials. Our model, based on percolation theory on a Bethe lattice, includes all
mechanisms known to contribute to adsorption hysteresis in mesoporous pore networks during capillary
condensation and evaporation. The model accounts for delayed and initiated condensation during
adsorption as well as equilibrium evaporation, pore blocking and cavitation during desorption. Coupled
with dedicated non-local-density functional theory (NLDFT) kernels, the proposed method provides a
unified framework for modeling the entire experimental adsorption-desorption isotherm, including
desorption hysteresis scans. Hence, this model unveils key pore network characteristics like the effective
connectivity, but also has the potential to determine pore size distributions of mesoporous materials by
taking quantitatively pore network effects into account. The applicability of the method is demonstrated
on a selected set of nanoporous silica materials exhibiting distinct types of hysteresis loops (types H1,
H2a, H1/H2a and H5), including ordered mesoporous silica networks, i.e, KIT-6 silica, hybrid SBA-
15/MCM-41 silica with plugged pores, but also two disordered silica pore networks, i.e., a hierarchical
meso-macroporous monolith and porous Vycor glass. For all materials, good correlation is found
between calculated and experimental primary adsorption and desorption isotherms as well as desorption
scans allowing for a determination of key pore network characteristics such as pore connectivity and
pore size distributions as well as a parameter correlated with the impact of pore network disorder and
corresponding effects on the adsorption behavior. The versatility and enriched textural insights provided
by the proposed novel network model allows for a comprehensive characterization previously
inaccessible, and hence will contribute to a further advancement in the textural characterization of novel
nanoporous materials. It has the potential to provide important guidance for the design and selection of
porous materials for optimising various applications, including separation processes (such as
chromatography), heterogeneous catalysis, gas-and energy storage.