Morphing Networks Constructed of Responsive Polymeric Microfibers: Towards a Programmable Matter with Mesoscale Morphing Resolutions

Abstract

The realization of materials that can actively alter their form in a predefined and programmable manner has revolutionary implications for a broad range of fields, ranging from art and architecture to robotics and medicine. In particular, programmable matter with mesoscale (100 nm to 10 µm) morphing resolution holds a promise for unique applications including interfacing with microparticles, cells, and organelles, and interacting with light in the visible and IR regimes. Yet, obtaining morphing systems which respond to different cues with such resolution is highly challenging as it requires altering the material properties in the sub-micron scale. While lithography enabled forming mesoscale 2D Òcut-outsÓ that fold to form 3D shapes, a generic and robust approach that enables forming 2D polymeric macroscale structures that morph with a mesoscale resolution is still lacking. In this research, an innovative scheme for realizing programmable shape-morphing networks with microscale morphing resolutions is proposed. Inspired by active cytoskeletal networks in biological systems, these shape-morphing networks are hierarchically assembled from interconnected stimuli-responsive polymeric microfibers. Such synthetic fiber networks bridge the current gap between nano- and macroscale morphing systems, and as was established in preliminary studies, exhibit previously unexplored phenomena and new modes of morphing that emanate from their multiscale hierarchical structure. The fiber networks will be fabricated using the jet writing approach by spinning stimuli-responsive polymeric fibers on an XY moving stage in predefined patterns with high spatial accuracy, followed by chemical treatments. The obtained network s architecture and the resulting morphing will be examined in real-time in optical, confocal, and electron microscopy, and analyzed by image processing tools. Using these methods, the proposal focuses on the following objectives: 1) Development of shape-morphing fiber networks of novel compositions that exhibit dual stimuli responsiveness or respond to electromagnetic induced heating by the incorporation of conductive nanoparticles into a responsive polymeric matrix and by surface treatment. 2) Fabrication of inhomogeneous responsive 2D fiber networks via a modulated writing approach, characterization of the chemical and physical parameters that govern the shape-morphing, and using this knowledge for programming complex response patterns by the spatial design of the network s architecture. 3) Construction and characterization of the shape-morphing of 3D stacked stimuli-responsive fiber networks towards 3D shape-shifting materials with microscale morphing resolution. The proposed morphing fiber networks offer an original, versatile, and scalable strategy for the design and development of novel functional responsive materials with unique morphing behaviors and high spatial morphing resolutions. Successful accomplishment of this proposal is expected to significantly promote the state-of-the-art within several key areas of material science research and introduce unique new fundamental types of morphing behaviors that are not accessible in other systems. Furthermore, the proposed morphing networks open new design and fabrication avenues that will broadly impact the materials research and technology community and provide a programmable matter with microscale morphing resolutions that hold significant potential for a range of applications in the future, including micro-muscles, morphing optical devices on a chip, sensors, and tunable microscale separators.

Document Details

Document Type
DoD Grant Award
Publication Date
Jul 27, 2023
Source ID
W911NF2310257

Entities

People

  • Amit Sitt

Organizations

  • Army Contracting Command
  • Tel Aviv University
  • United States Army

Tags

Readers

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

Technology Areas

  • AI & ML
  • Autonomy
  • Biotechnology
  • Microelectronics