April 7 - 11, 2025
Seattle, Washington
Symposium Supporters
2025 MRS Spring Meeting & Exhibit
SB03.02.03

Biomimetic Composites of Aramid Nanofibers for Structural Energy in Robotics

When and Where

Apr 7, 2025
4:30pm - 4:45pm
Summit, Level 3, Room 332

Presenter(s)

Co-Author(s)

Nicholas Kotov1

University of Michigan1

Abstract

Nicholas Kotov1

University of Michigan1
Aramid nanofibers (ANFs) are derived from recycled Kevlar—a widely used polymer in military and transportation. Forming highly entangled systems of nanofibers with cartilage-like organization, ANFs serve as a foundation for a variety of biomimetic composites that combine multiple properties essential for robotics- toughness, lightweight, thermal insulation, and charge transport. Furthermore, by repurposing Kevlar, ANFs offer a sustainable pathway to create high-performance nanoscale membranes with transformative potential in energy storage and water purification technologies.

This talk will be specifically focused on the preparation of ANF-based charge storage technologies for robotics. The combination of high ionic transport, flexibility toughness and solvent compatibility, which make them ideal for various battery types. ANF can be particularly suitable for structural batteries that can be integrated in the body of different robotic devices designed double duty – to store charge and carry load simultaneously, which is also common in biology. The unique cartilage-like architecture can prevent dendrite formation, a common issue that shortens battery life, and thus significantly extend the lifespan of lithium-ion and other high-energy-density batteries. Furthermore, their thermal stability, with resilience to temperatures above 300°C, makes ANFs suitable for applications where enhanced safety and thermal management are essential.

Realization of Zn, Li-ion, Li-metal, and Li-S batteries using ANF membranes will be demonstrated. Their implementation in the live models of drones and humanoid robots will be discussed Leveraging graph theory and machine learning, researchers can fine-tune the balance of order and disorder in ANF composites, tailoring them for specific applications in robotics.

Symposium Organizers

Laia Mogas-Soldevila, University of Pennsylvania
Pietro Cataldi, Italian Institute of Technology
Florian Hartmann, Max Planck Institute
Dimitrios Papageorgiou, Queen Mary University of London

Session Chairs

Pietro Cataldi
Dimitrios Papageorgiou

In this Session