Mass Transport through Nanostructured Membranes: Towards a Predictive Tool

Area of Science:

• Membrane Science and Technology
• Physical Chemistry
• Chemical Engineering

Background:

• Understanding solvent transport through nanostructured membranes is crucial for optimizing separation processes.
• Existing models often lack the fundamental insight needed for accurate prediction of solvent flux and solute rejection.
• Solvent-resistant membranes are vital for advanced nanofiltration applications.

Purpose of the Study:

• To propose a novel mechanism for solvent transport in nanostructured membranes.
• To develop new mathematical models for predicting solvent flux and solute rejection.
• To incorporate the fundamental role of solute, solvent, and membrane affinity, specifically hydrogen-bonding contributions.

Main Methods:

• Developed a pore-flow transport mechanism.
• Introduced new parameters quantifying hydrogen-bonding contributions to solubility parameters for solutes, solvents, and membranes.
• Constructed a graphical map to predict solute rejection based on these hydrogen-bonding parameters.
• Validated the model using existing literature performance data.

Main Results:

• The new model accurately predicts solvent flux and solute rejection in nanofiltration.
• The hydrogen-bonding contribution to solubility parameters was identified as a key factor.
• The developed graphical map provides a predictive tool for solute rejection.
• Model predictions showed good agreement with literature data.

Conclusions:

• The proposed pore-flow mechanism and associated mathematical models offer a fundamental understanding of solvent transport.
• The inclusion of hydrogen-bonding affinity significantly improves the prediction of membrane performance.
• This approach provides a practical tool for designing and optimizing nanofiltration processes using solvent-resistant membranes.