skip to main content


Title: Simple Synthesis of Elastomeric Photomechanical Switches That Self‐Heal
Abstract

This article introduces a simple two‐stage method to synthesize and program a photomechanical elastomer (PME) for light‐driven artificial muscle‐like actuations in soft robotics. First, photochromic azobenzene molecules are covalently attached to a polyurethane backbone via a two‐part step‐growth polymerization. Next, mechanical alignment is applied to induce anisotropic deformations in the PME‐actuating films. Cross‐linked through dynamic hydrogen bonds, the PMEs also possess autonomic self‐healing properties without external energy input. This self‐healing allows for a single alignment step of the PME film and subsequent “cut and paste” assembly for multi‐axis actuation of a self‐folded soft‐robotic gripper from a single degree of freedom optical input.

 
more » « less
NSF-PAR ID:
10462805
Author(s) / Creator(s):
 ;  ;  ;  ;  ;  ;  ;  ;  
Publisher / Repository:
Wiley Blackwell (John Wiley & Sons)
Date Published:
Journal Name:
Macromolecular Rapid Communications
Volume:
40
Issue:
4
ISSN:
1022-1336
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. Self-healing soft electronic and robotic devices can, like human skin, recover autonomously from damage. While current devices use a single type of dynamic polymer for all functional layers to ensure strong interlayer adhesion, this approach requires manual layer alignment. In this study, we used two dynamic polymers, which have immiscible backbones but identical dynamic bonds, to maintain interlayer adhesion while enabling autonomous realignment during healing. These dynamic polymers exhibit a weakly interpenetrating and adhesive interface, whose width is tunable. When multilayered polymer films are misaligned after damage, these structures autonomously realign during healing to minimize interfacial free energy. We fabricated devices with conductive, dielectric, and magnetic particles that functionally heal after damage, enabling thin-film pressure sensors, magnetically assembled soft robots, and underwater circuit assembly.

     
    more » « less
  2. Abstract

    Soft tissue injuries such as volumetric muscle loss (VML) are often too large to heal normally on their own, resulting in scar formation and functional deficits. Decellularized extracellular matrix (dECM) scaffolds placed into these wounds have shown the ability to modulate the immune response and drive constructive healing. This provides a potential solution for functional tissue regeneration, however, these acellular dECM scaffolds are challenging to fabricate into complex geometries. 3D bioprinting is uniquely positioned to address this, being able to create patient‐specific scaffolds based on clinical 3D imaging data. Here, a process to use freeform reversible embedding of suspended hydrogels (FRESH) 3D bioprinting and computed tomography (CT) imaging to build large volume, patient‐specific dECM patches (≈12 × 8 × 2 cm) for implantation into canine VML wound models is developed. Quantitative analysis shows that these dECM patches are dimensionally accurate and conformally adapt to the surface of complex wounds. Finally, this approach is extended to a human VML injury to demonstrate the fabrication of clinically relevant dECM scaffolds with precise control over fiber alignment and micro‐architecture. Together these advancements represent a step towards an improved, clinically translatable, patient‐specific treatment for soft tissue defects from trauma, tumor resection, and other surgical procedures.

     
    more » « less
  3. Abstract

    Nature excels in both self-healing and 3D shaping; for example, self-healable human organs feature functional geometries and microstructures. However, tailoring man-made self-healing materials into complex structures faces substantial challenges. Here, we report a paradigm of photopolymerization-based additive manufacturing of self-healable elastomer structures with free-form architectures. The paradigm relies on a molecularly designed photoelastomer ink with both thiol and disulfide groups, where the former facilitates a thiol-ene photopolymerization during the additive manufacturing process and the latter enables a disulfide metathesis reaction during the self-healing process. We find that the competition between the thiol and disulfide groups governs the photocuring rate and self-healing efficiency of the photoelastomer. The self-healing behavior of the photoelastomer is understood with a theoretical model that agrees well with the experimental results. With projection microstereolithography systems, we demonstrate rapid additive manufacturing of single- and multimaterial self-healable structures for 3D soft actuators, multiphase composites, and architected electronics. Compatible with various photopolymerization-based additive manufacturing systems, the photoelastomer is expected to open promising avenues for fabricating structures where free-form architectures and efficient self-healing are both desirable.

     
    more » « less
  4. Abstract

    Liquid crystals offer a dynamic platform for developing advanced photonics and soft actuation systems due to their unique and facile tunability and reconfigurability. Achieving precise spatial patterning of the liquid crystal alignment is critical to developing electro‐optical devices, programmable origami, directed colloidal assembly, and controlling active matter. Here, a simple method is demonstrated to achieve continuous 3D control of the directions of liquid crystal mesogens using a two‐step photo‐exposure process. In the first step, polarized light sets the orientation in the plane of confining substrates; the second step uses unpolarized light of a prescribed dose to set the out‐of‐plane orientation. The method enables smoothly varying orientational patterns with sub‐micrometer precision. As a demonstration, the setup is used to create gradient‐index lenses with parabolic refractive index profiles that remain stable without external electric fields. The lenses' focal length and sensitivity to light polarization are characterized through experimental and numerical methods. The findings pave the way for developing next‐generation photonic devices and actuated materials, with potential applications in molecular self‐assembly, re‐configurable optics, and responsive matter.

     
    more » « less
  5. Alkan, Can (Ed.)
    Abstract Motivation Pangenome variation graphs model the mutual alignment of collections of DNA sequences. A set of pairwise alignments implies a variation graph, but there are no scalable methods to generate such a graph from these alignments. Existing related approaches depend on a single reference, a specific ordering of genomes or a de Bruijn model based on a fixed k-mer length. A scalable, self-contained method to build pangenome graphs without such limitations would be a key step in pangenome construction and manipulation pipelines. Results We design the seqwish algorithm, which builds a variation graph from a set of sequences and alignments between them. We first transform the alignment set into an implicit interval tree. To build up the variation graph, we query this tree-based representation of the alignments to reduce transitive matches into single DNA segments in a sequence graph. By recording the mapping from input sequence to output graph, we can trace the original paths through this graph, yielding a pangenome variation graph. We present an implementation that operates in external memory, using disk-backed data structures and lock-free parallel methods to drive the core graph induction step. We demonstrate that our method scales to very large graph induction problems by applying it to build pangenome graphs for several species. Availability and implementation seqwish is published as free software under the MIT open source license. Source code and documentation are available at https://github.com/ekg/seqwish. seqwish can be installed via Bioconda https://bioconda.github.io/recipes/seqwish/README.html or GNU Guix https://github.com/ekg/guix-genomics/blob/master/seqwish.scm. 
    more » « less