Optimization of Reactive Ink Formulation for Controlled Additive Manufacturing of Copolymer Membrane...

Area of Science:

• Materials Science
• Chemical Engineering
• Data Science

Background:

• Nanostructured membranes offer solutions for permeability-selectivity challenges in molecule separations.
• Additive manufacturing enables reactive ink deposition for modifying membrane pore chemistry.
• Systematic optimization is lacking for large-scale membrane functionalization.

Purpose of the Study:

• To elucidate membrane functionalization mechanisms and optimal manufacturing conditions using click chemistry.
• To develop mathematical models for predicting ink chemistry and describing the functionalization process.
• To optimize ink formulations for reduced material usage and scalable membrane production.

Main Methods:

• Utilized a data science toolkit including nonlinear regression, uncertainty quantification, and design of experiments.
• Developed algebraic equations for reactive ink equilibrium concentrations and reaction-diffusion PDEs for functionalization.
• Validated ink chemistry with pH and UV-vis measurements; calibrated PDE parameters using FTIR spectroscopy.

Main Results:

• Established a validated modeling framework for membrane functionalization, reducing experimental redundancy.
• Identified an optimal ink formulation (Cu(II)/AA/alkyne = 1:1:2) and operational conditions.
• Achieved ≥90% functionalization with at least a 20% reduction in copper investment in a simulated roll-to-roll process.

Conclusions:

• The data science-enabled framework provides a functionalization protocol for scaling up multifunctional membrane designs.
• Optimized ink formulations reduce reliance on expensive and environmentally concerning materials.
• The approach is extendable for on-demand multifunctional membranes in applications like metal recovery from wastewater.