CAREER: Programming Polymer Assembly via Multiscale Molecular Design

PART 1: NON-TECHNICAL SUMMARY Soft materials play essential roles in technologies ranging from flexible electronics to personal protective gear and medical devices. Yet today’s synthetic materials rarely achieve the remarkable combination of strength, stretchability, and adaptability found in natural materials. This is attributed to limitations in our ability to build the multiscale structures that give rise to these exceptional properties in natural materials. This project addresses this challenge by studying how ions, simple charged species like those found in everyday salts, can be used to direct the assembly of polymers into multiscale organized networks. To uncover these design rules, the research team will develop a high-throughput experimental platform capable of rapidly exploring thousands of material combinations, using automated material handling and imaging. These automated tools will enable the quantitative assessment of how these different ingredients dictate network structure and performance, enabling a machine-learning mapping of the connection between molecular “inputs” and material “outputs.” The insights gained from this work are expected to advance the design of robust materials for biotechnology and are expected to impact a wide variety of soft matter dependent technologies by providing an experimental foundation for the incorporation of machine learning/artificial intelligence into bioinspired polymer processing. More broadly, these discoveries may benefit emerging technologies in soft robotics, sustainable manufacturing, wearable electronics, and interfaces that connect biological tissues with devices. The educational component of this project will broaden participation in science and strengthen the future STEM workforce. A collaboration with the Rhode Island School of Design (RISD) will create hands-on activities that illustrate how invisible molecular interactions give rise to visible material behavior, forging connections between chemistry, materials science, and artistic design. Undergraduate students will gain research experience with modern laboratory automation, data-rich experimentation, and scientific communication. Together, these efforts serve the national interest by advancing fundamental knowledge, promoting technological innovation, and training the next generation of scientists and designers. PART 2: TECHNICAL SUMMARY This CAREER proposal aims to establish a fundamental understanding of how molecular composition and polymer topology interact to govern the structure and properties of ion-stimulated phase separation (IS-PS) in proteomimetic polyelectrolytes. The overall goal is to enable the multiscale architecting of soft materials with programmable emergent properties, drawing inspiration from structure–assembly–function relationships observed in biogenic soft materials. More specifically, this proposal addresses a core challenge in polymer science: understanding and leveraging multiscale relationships among molecular structure, polymer topology, and processing methodology to design robust materials. The research plan has three scientific objectives: (1) develop a high-throughput experimental platform to investigate the interaction of IS-PS and polymer structure in network formation; (2) characterize the combined influence of polymer composition and topology within anisotropic graft polymer architectures on network structure and material properties under IS-PS conditions; and (3) use IS-PS as a templating strategy for double-network formation. This framework draws inspiration from biological systems that employ temporally controlled phase separation and concentration-induced ordering to fabricate hierarchical anisotropic networks (HANs)—the structural basis for the remarkable properties of tissues such as skin and cartilage. By integrating emerging insights into the IS-PS of proteomimetic polyelectrolytes with the liquid crystalline behavior of rod-like bottlebrush polymers, the pr NSF Award ID: 2542211 | Program: 01002627DB NSF RESEARCH & RELATED ACTIVIT,01002930DB NSF RESEARCH & RELATED ACTIVIT,01003031DB NSF RESEARCH & RELATED ACTIVIT | Principal Investigator: Benjamin McDonald | Institution: Brown University, PROVIDENCE, RI | Award Amount: $390,000 View on NSF Award Search: https://www.nsf.gov/awardsearch/show-award/?AWD_ID=2542211 View on Research.gov: https://www.research.gov/awardapi-service/v1/awards/2542211.html