Computationally Driven Discovery and Engineering of Multiblock Polymer Nanostructures Using Genetic Algorithms

Project Personnel

Glenn Fredrickson

Principal Investigator

University of California, Santa Barbara

Email

Kris Delaney

University of California, Santa Barbara

Email

Kevin Dorfman

University of Minnesota, Twin Cities

Email

Marc Hillmyer

University of Minnesota, Twin Cities

Email

Frank Bates

University of Minnesota, Twin Cities

Email

Funding Divisions

Division of Materials Research (DMR), Division of Mathematical Sciences (DMS)

This project will develop discovery tools that will enable the rational, computationally-assisted design of multiblock polymers for applications in medicine, microelectronics, separations, and energy production and storage, among others. Complicating factors in this class of soft materials are the myriad parameters that dictate molecular architecture, block sequence, and interactions and the wide range of self-assembled nanostructures that are possible. Through a concerted and iterative combination of theory, simulation, and experiment, global optimization tools will be devised and validated to predict the forward and reverse relationship between polymer architecture and nanostructure. The discovery tools developed in this program will be made widely available to the industrial and academic polymer materials community through a web-based job submission program hosted at the Minnesota Supercomputer Institute, and a searchable database will be constructed from the structure/sequence/morphology maps that result over the course of the project. This combined approach will dramatically reduce the timescale for discovery, design, and deployment of new multiblock polymers as advanced functional materials.

Designing Materials to Revolutionize and Engineer our Future (DMREF)