Dylan Barber joined the Department of Materials Science and Engineering at UW–Madison as an Assistant Professor in August 2025. Dylan earned his B.A. in Chemistry from Williams College, where he started his research career as a polymer chemist designing antioxidant block copolymers for drug delivery under the mentorship of Sarah Goh. He earned his Ph.D. in Polymer Science and Engineering from the University of Massachusetts Amherst under the joint mentorship of Alfred J. Crosby and Todd Emrick, where he synthesized stimulus-responsive copolymers and used them to build programmable mesoscale filaments capable of selective co-assembly with foreign bodies in solution, self-assembly into filamentous bio-inspired bundles, and recapitulation of molecular-scale phenomena (e.g., block copolymers) at larger length-scales. In 2021, he started work as a Postdoctoral Fellow for Jennifer Lewis at Harvard University, where he developed strategies for manufacturing porous electrodes for electrochemical flow systems via direct ink writing, and the rational design, synthesis, and physical characterization of stable room-temperature zwitterionic liquids.
He now runs the Precision Polymer Group at UW–Madison, dedicated to the synthesis of novel polymers with tailored architectures that address grand challenges in energy generation, energy transduction, energy storage, the internet of things, human health, and a circular economy. Currently, he is curious about polymers that can be sorted into two broad classes:
Polarizable Soft Matter. Despite extraordinary potential for real-world impact, few materials combine a large dielectric constant with mechanical softness because both the fundamental physics of such materials and the synthetic chemistry that will build them are poorly understood. The Precision Polymers Group is addressing this by synthesizing and characterizing polymer melts that challenge the current paradigm of the molecular dipole in service of better energy technologies, robotics, and medicine.
Sequence-defined polymers. Control of polymer architecture at the level of individual repeat units will unlock molecular machines, molecular data storage, and elastomers with programmable self-degradation for closed-loop recycling. Yet, current strategies cannot deliver structural control at useful scale, speed, and purity. We develop high-throughput synthesis pathways to sequence-defined polymers with potential impact from data storage to sustainability.