CAREER: Branch-Following and Bifurcation Methods to Identify Active Materials for Tomorrow's Sensors and Actuators

This Faculty Early Career Development (CAREER) award proposes to research a critical problem currently limiting the technological use of active materials for novel sensor/actuator applications is the lack of accurate analysis and design tools. The overall objective of this project is to develop and validate a branch-following and bifurcation computational methodology capable of systematically mapping out the active behavior of new sensor materials.

New atomistic material models will be developed for active material behavior and computational branch-following and bifurcation (BFB) methods, adapted specifically for studying crystalline materials, will be created. These models and methods will be capable of revealing the lattice-level mechanisms responsible for active behavior. The new techniques will be validated against recently obtained experimental data for the shape memory alloy NiTi and its ternary alloys. The results of this project will include the creation of new computational methods for accurately modeling and interrogating the free energy landscape of active materials and will ultimately result in the development of a mature and robust technology for the design of active materials.

This work is expected to provide a fresh perspective on the fundamental principles governing the behavior of active materials. In addition, this project will provide individual training for both graduate and undergraduate students. A web-site will be created to make the results of this work broadly accessible and to encourage the development of new interactions and collaborations between the PI and other research groups interested in similar problems. Finally, the PI will integrate research results into the undergraduate and graduate curriculum.