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Engineered living materials (ELMs) are an emerging class of biohybrid materials that have shown great promise with advanced capabilities unachievable by conventional materials. However, application of ELMs outside of the laboratory has been limited due to the need for periodic media replenishment or complete media immersion. We herein demonstrated the integration of capillary microfluidics for the autonomous and pump-free hydration of ELM hydrogels. We optimized 3D printing parameters, including exposure time and build plate lift and retract distances, to obtain microchannel dimensions capable of spontaneous capillary flow using a low-cost liquid crystal display stereolithographic apparatus (LCD-SLA) 3D printer and two hydrogel resins that are suitable for ELMs. Microchannel dimensions were accurate with ≤ 10% deviation between designed and measured widths and precise with coefficients of variation (CVs) <5% for microchannels ≥ 206.4 µm. We demonstrated proof-of-concept spontaneous capillary flow in 3D printed microfluidic devices using dye-incorporated lysogeny broth (LB). Snapshots of the devices captured up to 24 hours showed the diffusion of dye-incorporated LB throughout the bulk material. Through this proof-of-concept study, we have showcased the feasibility of integrating capillary microfluidics with ELMs for the autonomous and pump-free flow of fluids towards self-sustaining and long-term hydration. 

Unlike human intestines, which are long, hollow tubes, the intestines of sharks and rays contain interior helical structures surrounding a cylindrical hole. One function of these structures may be to create asymmetric flow, favoring passage of fluid down the digestive tract, from anterior to posterior. Here, we design and 3D print biomimetic models of shark intestines, in both rigid and deformable materials. We use the rigid models to test which physical parameters of the interior helices (the pitch, the hole radius, the tilt angle, and the number of turns) yield the largest flow asymmetries. These asymmetries exceed those of traditional Tesla valves, structures specifically designed to create flow asymmetry without any moving parts. When we print the biomimetic models in elastomeric materials so that flow can couple to the structure’s shape, flow asymmetry is significantly amplified; it is sevenfold larger in deformable structures than in rigid structures. Last, we 3D-print deformable versions of the intestine of a dogfish shark, based on a tomogram of a biological sample. This biomimic produces flow asymmetry comparable to traditional Tesla valves. The ability to influence the direction of a flow through a structure has applications in biological tissues and artificial devices across many scales, from large industrial pipelines to small microfluidic devices. 

Mechanical deformation of polymer networks causes molecular-level motion and bond scission that ultimately lead to material failure. Mitigating this strain-induced loss in mechanical integrity is a significant challenge, especially in the development of active and shape-memory materials. We report the additive manufacturing of mechanical metamaterials made with a protein-based polymer that undergo a unique stiffening and strengthening behavior after shape recovery cycles. We utilize a bovine serum albumin-based polymer and show that cyclic tension and recovery experiments on the neat resin lead to a ~60% increase in the strength and stiffness of the material. This is attributed to the release of stored length in the protein mechanophores during plastic deformation that is preserved after the recovery cycle, thereby leading to a “strain learning” behavior. We perform compression experiments on three-dimensionally printed lattice metamaterials made from this protein-based polymer and find that, in certain lattices, the strain learning effect is not only preserved but amplified, causing up to a 2.5× increase in the stiffness of the recovered metamaterial. These protein–polymer strain learning metamaterials offer a unique platform for materials that can autonomously remodel after being deformed, mimicking the remodeling processes that occur in natural materials. 

In this work, we introduce a 3D-printable virus-like particle (VLP)-enhanced cross-linked biopolymer system. 

Flexible and lightweight sensors can assess their environment for applications that include wearables for health monitoring and soft robotics.