Search for: All records

Soft machines will require soft materials that exhibit a rich diversity of functionality, including shape morphing and photoresponsivity. The combination of these functionalities enables useful behaviors in soft machines that can be further developed by synthesizing materials that exhibit localized responsivity. Localized responsivity of liquid crystal elastomers (LCEs), which are soft materials that exhibit shape morphing, can be enabled by formulating composite inks for direct ink writing (DIW). Gold nanorods (AuNRs) can be added to LCEs to enable photothermal shape change upon absorption of light through a localized surface plasmon resonance. We compared LCE formulations, focusing on their amenability for printing by DIW and the photoresponsivity of AuNRs. The local responsivity of different three-dimensional architectures enabled soft machines that could oscillate, crawl, roll, transport mass, and display other unique modes of actuation and motion in response to light, making these promising functional materials for advanced applications. 

Light- and ink-based 3D printing methods have vastly expanded the design space and geometric complexity of architected ceramics. However, light-based methods are typically confined to a relatively narrow range of preceramic and particle-laden resins, while ink-based methods are limited in geometric complexity due to layerwise assembly. Here, embedded 3D printing is combined with microwave-activated curing to generate architected ceramics with spatially controlled composition in freeform shapes. Aqueous colloidal inks are printed within a support matrix, rapidly cured via microwave-activated polymerization, and subsequently dried and sintered into dense architectures composed of one or more oxide materials. This integrated manufacturing method opens new avenues for the design and fabrication of complex ceramic architectures with programmed composition, density, and form for myriad applications. 

Granular hydrogel matrices have emerged as promising candidates for cell encapsulation, bioprinting, and tissue engineering. How- ever, it remains challenging to design and optimize these materials given their broad compositional and processing parameter space. Here, we combine experimentation and computation to create granular matrices composed of alginate-based bioblocks with controlled structure, rheological properties, and injectability pro- files. A custom machine learning pipeline is applied after each phase of experimentation to automatically map the multidimensional input-output patterns into condensed data-driven models. These models are used to assess generalizable predictability and define high-level design rules to guide subsequent phases of development and characterization. Our integrated, modular approach opens new avenues to understanding and controlling the behavior of complex soft materials. 

Dielectric elastomer actuators (DEAs) are among the fastest and most energy-efficient, shape-morphing materials. To date, their shapes have been controlled using patterned electrodes or stiffening elements. While their actuated shapes can be analyzed for prescribed configurations of electrodes or stiffening elements (the forward problem), the design of DEAs that morph into target shapes (the inverse problem) has not been fully addressed. Here, we report a simple analytical solution for the inverse design and fabrication of programmable shape-morphing DEAs. To realize the target shape, two mechanisms are combined to locally control the actuation magnitude and direction by patterning the number of local active layers and stiff rings of varying shapes, respectively. Our combined design and fabrication strategy enables the creation of complex DEA architectures that shape-morph into simple target shapes, for instance, those with zero, positive, and negative Gaussian curvatures as well as complex shapes, such as a face.

 

Implantable tubes, shunts, and other medical conduits are crucial for treating a wide range of conditions from ears and eyes to brain and liver but often impose serious risks of device infection, obstruction, migration, unreliable function, and tissue damage. Efforts to alleviate these complications remain at an impasse because of fundamentally conflicting design requirements: Millimeter-scale size is required to minimize invasiveness but exacerbates occlusion and malfunction. Here, we present a rational design strategy that reconciles these trade-offs in an implantable tube that is even smaller than the current standard of care. Using tympanostomy tubes (ear tubes) as an exemplary case, we developed an iterative screening algorithm and show how unique curved lumen geometries of the liquid-infused conduit can be designed to co-optimize drug delivery, effusion drainage, water resistance, and biocontamination/ingrowth prevention in a single subcapillary–length-scale device. Through extensive in vitro studies, we demonstrate that the engineered tubes enabled selective uni- and bidirectional fluid transport; nearly eliminated adhesion and growth of common pathogenic bacteria, blood, and cells; and prevented tissue ingrowth. The engineered tubes also enabled complete eardrum healing and hearing preservation and exhibited more efficient and rapid antibiotic delivery to the middle ear in healthy chinchillas compared with current tympanostomy tubes, without resulting in ototoxicity at up to 24 weeks. The design principle and optimization algorithm presented here may enable tubes to be customized for a wide range of patient needs.

 

ABSTRACT: Covalent adaptive networks combine the advantages of cross-linked elastomers and dynamic bonding in a single system. In this work, we demonstrate a simple one-pot method to prepare thiol−ene elastomers that exhibit reversible photoinduced switching from an elastomeric gel to fluid state. This behavior can be generalized to thiol−ene cross-linked elastomers composed of different backbone chemistries (e.g., polydimethylsiloxane, polyethylene glycol, and polyurethane) and vinyl groups (e.g., allyl, vinyl ether, and acrylate). Photoswitching from the gel to fluid state occurs in seconds upon exposure to UV light and can be repeated over at least 180 cycles. These thiol−ene elastomers also exhibit the ability to heal, remold, and serve as reversible adhesives. KEYWORDS: covalent adaptive network, elastomer chemistry, click chemistry, self-healing, photoresponsive materials, adhesives 

An integrated design, modeling, and multi‐material 3D printing platform for fabricating liquid crystal elastomer (LCE) lattices in both homogeneous and heterogeneous layouts with spatially programmable nematic director order and local composition is reported. Depending on their compositional topology, these lattices exhibit different reversible shape‐morphing transformations upon cycling above and below their respective nematic‐to‐isotropic transition temperatures. Further, it is shown that there is good agreement between their experimentally observed deformation response and model predictions for all LCE lattice designs evaluated. Lastly, an inverse design model is established and the ability to print LCE lattices with the predicted deformation behavior is demonstrated. This work opens new avenues for creating architected LCE lattices that may find potential application in energy‐dissipating structures, microfluidic pumping, mechanical logic, and soft robotics.