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Sequence-defined Macromolecules for Advanced Materials Design

Christopher Alabi from Cornell University

Hierarchical self-assembly of functional materials with predictable properties requires the design and synthesis of programmable building blocks that encode information for self-organization across multiple length scales. Motivated by these opportunities and the need for sequence-control and structural diversity in polymeric materials research, I will present a versatile strategy for the assembly of sustainable cross-linkable sequence-defined macromolecules. This new sequence-defined oligocarbamate (SeDOC) platform overcomes the scalability issue that plagues the iterative assembly of sequence-defined macromolecules and enables the assembly of oligocarbamate macromers at the gram-scale. Data highlighting the effect of sequence on network topology, optical and mechanical properties will be discussed. Furthermore, I will discuss our research efforts toward designing a programmable macromer platform with molecular recognition motifs that can be used in non-aqueous media to encode information for hybridization. I will present data on selective pairs of complementary SeDOCs, characterized using multiple techniques, that can be created at scale and potentially used as ligands in a variety of chemical and materials applications.