Ultrafiltration membranes used in pharmaceutical manufacturing and other industrial processes have long relied on separating molecules by size. Now, Cornell researchers have created porous materials that filter molecules by their chemical makeup.
Two molecules of identical size and weight but different chemistry, such as antibodies with distinct molecular structure, are difficult to separate using current ultrafiltration (UF) membrane technology. But in a study published Nov. 13 in Nature Communications, researchers find that blending chemically distinct block copolymer micelles - tiny self-assembling polymer spheres - could be applied to making membranes capable of filtering molecules by chemical affinity.
Scanning electron microscopy image (left) shows the surface of a porous asymmetric UF membrane created at Cornell by mixing chemically distinct block copolymer micelles. Machine-learning segmentation (right) identified patterns formed by different micelle types and chemistries, revealing how the approach could lead to UF membranes that sort by chemical affinity.
"This is the first real pathway to creating UF membranes with chemically diverse pore surfaces," said Ulrich Wiesner, the Spencer T. Olin Professor of Materials Science and Engineering, and the study's senior author. "In principle, post-fabrication processes may achieve this, but the cost would be prohibitive for industry to adopt it. This new approach could truly revolutionize ultrafiltration."
Taking inspiration from nature - such as protein channels in cells that can distinguish between similar-sized metal ions using pore wall chemistry - lead author Lilly Tsaur, Ph.D. '24, of the Wiesner group, explored how neutral and repulsive interactions among micelles influence their self-assembly within the top separation layer. By combining up to three distinct block copolymers, the team demonstrated how these competing interactions control where different chemistries appear in the pores of the film's surface.
"While in principle this is a really simple idea, in practice, developing this experimentally is really difficult," said Wiesner, also a professor in the Department of Design Tech. "In particular, identifying where the different micelle chemistries are located in the top separation layer is nontrivial."
Using scanning electron microscopy, Tsaur imaged hundreds of samples to study how the different micelles arranged themselves. Because imaging could not easily identify the chemistries, she used machine learning to detect subtle differences in pore patterns to identify where each micelle type appeared.
Co-author Fernando A. Escobedo, the Samuel W. and M. Diane Bodman Professor of Chemical and Biomolecular Engineering (Cornell Engineering), ran molecular simulations to help reveal rules that govern how the micelles self-organize - a challenge due to the large number of micelles and their tendency to assemble into states relatively far from equilibrium.
"This necessitated the use of highly coarse-grained models and numerous calibrations to capture the time and length scales involved in the experimental process," said Escobedo, who conducted the research with Luis Nieves-Rosado, Ph.D. '25.
The study builds on the Wiesner group's previous advances in block copolymer self-assembly that led to the founding of Terapore Technologies, a startup company led by Rachel Dorin, Ph.D. '13, that uses the group's scalable block copolymer process to make cost-effective UF membranes that separate viruses from biopharmaceuticals. The new research paves the way for companies to use the same manufacturing process to produce membranes that can perform affinity separations based on programming pore surface chemistry.
"Companies simply want to change the recipe, the 'magic dust,' that goes into the same process they've been using for decades in order to give membranes chemically diverse pore surfaces," Wiesner said. "Our method has the potential to lead to a paradigm shift in UF-based operations, and to open a whole new avenue for how to use UF membranes."
Beyond filtration, the research could lead to new materials with novel properties for applications such as smart coatings that respond to their environment and biosensors that detect specific molecules. Wiesner's group is continuing the work and developing methods to probe deeper into the top separation layer of these materials to see how the chemical patterns extend below the surface.
The research was supported by the National Science Foundation and was enabled by the Cornell Materials Research Science and Engineering Center and the Cornell Nuclear Magnetic Resonance Facility.
Syl Kacapyr is associate director of marketing and communications for Cornell Engineering.
