Dynamic Polymer Networks for Resilient and Adaptive Soft Machines

Abstract

Shape-morphing materials have emerged as an innovative technology to advance robotic device performance across applications spaces. However, due to their inherent compliance and softness they are typically vulnerable to mechanical damage and to changing harsh conditions in operating environments, and thus present inherent durability and reliability problems. Self-healing materials (repairing damage across length scales) offer a promising solution to these vulnerabilities; however, fundamental property trade-offs (e.g., strength vs kinetics) limit the full realization of their potential and their implementation in deployable, adaptive devices and machines. The results from this project will advance multifunctional aerospace materials performance, and will enable new capabilities in aerospace vehicles to manipulate boundary layer flow, optimize aerodynamic performance across flight regimes, and operate in unstructured hybrid environments.

Document Details

Document Type
DoD Grant Award
Publication Date
Feb 06, 2025
Source ID
FA95502410185

Entities

People

  • Abdon Pena-Francesch

Organizations

  • Air Force Office of Scientific Research
  • Board of Regents of the University of Michigan
  • United States Air Force

Tags

Readers

  • Reinforced Composite Materials
  • Robotics and Automation.
  • Systems Analysis and Design

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems
  • Autonomy
  • Autonomy - Autonomous System Control
  • Space