Smart and solvent-switchable graphene-based membrane for graded molecular sieving

Area of Science:

• Materials Science
• Chemical Engineering
• Nanotechnology

Background:

• Stimulus-responsive membranes are crucial for advanced separation systems.
• Natural lipid membranes exhibit solvent-dependent transport properties.
• Graphene oxide (GO) membranes offer potential for molecular sieving but often lack tunable selectivity.

Purpose of the Study:

• To develop a smart, switchable molecular sieving membrane by incorporating porous graphene (PG) into graphene oxide (GO).
• To investigate the membrane's reversible response to different solvent types.
• To demonstrate its application in graded separation processes.

Main Methods:

• Fabrication of a hybrid GO-PG membrane.
• Characterization of membrane permeance and molecular weight cut-off (MWCO) in various solvents (water, methanol).
• Analysis of transport pathways and solvent-membrane interactions.

Main Results:

• The GO-PG membrane exhibited high water (45.52 L m⁻² h⁻¹ bar⁻¹) and methanol (13.56 L m⁻² h⁻¹ bar⁻¹) permeance.
• Reversible switching of MWCO from ~319 g mol⁻¹ in water to 960 g mol⁻¹ in methanol was observed.
• The switchable sieving behavior was attributed to solvent-induced changes in nanochannel transport pathways and interlayer spacing.

Conclusions:

• The GO-PG membrane demonstrates tunable, solvent-responsive molecular sieving capabilities.
• This smart membrane design enables efficient graded separation of solutes with varying molecular weights.
• The findings open new avenues for designing advanced membranes for complex separation challenges.