Graphene is a two-dimensional material that offers a unique combination of low density, exceptional mechanical properties, large surface area and excellent electrical conductivity. Recent progress has produced bulk 3D assemblies of graphene, such as graphene aerogels, but they possess purely stochastic porous networks, which limit their performance compared with the potential of an engineered architecture. Here we report the fabrication of periodic graphene aerogel microlattices, possessing an engineered architecture via a 3D printing technique known as direct ink writing. The 3D printed graphene aerogels are lightweight, highly conductive and exhibit supercompressibility (up to 90% compressive strain). Moreover, the Young's moduli of the 3D printed graphene aerogels show an order of magnitude improvement over bulk graphene materials with comparable geometric density and possess large surface areas. Adapting the 3D printing technique to graphene aerogels realizes the possibility of fabricating a myriad of complex aerogel architectures for a broad range of applications.

We present a new class of architected materials that exhibit rapid, reversible, and sizable changes in effective stiffness.

Three-dimensional printing of multi-material parts relies upon efficient mixing of the ink components and a rapid response to composition changes. However, at low Reynolds numbers and large Peclet numbers, mixing disparate viscosity and density inks poses a challenge. In this study, the performance of active micromixers for disparate non-Newtonian inks is evaluated using both This article is protected by copyright. All rights reserved.2 experiments and computational fluid dynamics simulations. The mixing efficiencies are compared with scaling relationships for active micromixers. Using detailed simulation results, multiple factors are identified that can impact the micromixer response time during a composition change. Lastly, an active micromixer is proposed and evaluated to efficiently mix arbitrary multi-material ink compositions and produce fine composition gradients within printed parts.

The mixing of materials during additive manufacturing is a major benefit which allows one to compositionally and spatially tailor material properties, for example to locally control the reactivity in fuel: oxidizer systems known as thermites. This work characterizes an active mixing printhead used in conjunction with a 3D printing process known as Direct Ink Writing. Besides compositional control, a major benefit of this approach is that it offers a safe method for working with these materials which can otherwise be hazardous once mixed. Custom fuel and oxidizer inks are fed at fixed volumetric rates into an active mixing head, and both the rotational speed of the mixing impeller as well as the fuel:oxidizer ratio are varied. Upon ignition, the propagation speed increases with the rotational speed of the mixer and plateaus above a critical value of approximately 750 RPM. The critical mixing speed is corroborated by computational fluid simulations and an analytical expression that considers the inks' complex fluid behavior. Additionally, varying the composition results in a wide range of propagation speeds with peak reactivity corresponding to a fuel-rich formulation ( = 1.5). A test article incorporating a fast and slow-burning region demonstrates how spatial composition can manipulate the reactivity. This is the author manuscript accepted for publication and has undergone full peer review but has not been through the copyediting, typesetting, pagination and proofreading process, which may lead to differences between this version and the Version of Record. Please cite this article as

multimaterial DIW printer uses two separate ink dispensers joined at a single nozzle junction to simultaneously 3D print two viscoelastic inks through a single nozzle. Some models have been established to help control the printing of viscoelastic inks, but they have not been applicable for use in structures with complex compositional gradients. [18,22,23] As illustrated in Figure 1A, the toolpath of the printer is directly coupled with a desired composition (Φ) in order to determine the dispensing rate of each material. A distinction between the programmed dispensing rate of an ink (Q i ) and the measured flow rate out of the nozzle (Q Ni ) must be made when considering how to obtain an accurate compositional profile. Ideally, the increases and decreases in the measured ink flow rate synchronously follow the programmed dispensing rate. In reality, a number of factors introduce significant differences between the ideal ink dispensing rates and the realized outputs. Achieving accurate compositional 3D printing involving gradient transitions requires that we account for more complex behaviors, such as hydraulic compliance and non-Newtonian ink response, that result in significant differences between the programmed Q i and the realized Q Ni ( Figure 1B). For binary compositional changes within the same component, a combination of ink retraction and over extrusion can be used to account for these nonidealities. [22] For gradient compositional changes, the microfluidic circuit analogy (MCA) can be used to model and inform the ink dispensing profile that is required to achieve accurate compositional control ( Figure 1C).Here, we first describe the MCA model that is used to prescribe the ink-dispensing profile for improved compositional deposition accuracy in 3D-printed geometries with compositional gradients. We outline a calibration procedure to extract the MCA model parameters, which are then used in the MCA model to quantitatively guide the ink-dispensing profile for the desired compositional gradients to be printed. We finally validate the model in a DIW system using viscoelastic polydimethylsiloxane (PDMS) inks with time-dependent compositional changes. The ability to print multiple materials with accurate compositional profiles in a programmable manner enables the fabrication of new functional materials that were previously inaccessible.We use a model based on the microfluidic circuit analogy to determine the correct ink dispensing profiles required for 3D printing of structures with compositional gradients requires accurate dispensing control to achieve desired profiles. Here, empirical data are used with a model based on the microfluidic circuit analogy (MCA) to project dispense rate profiles that yield improved compositional accuracy in the printed part. Since minor variation in the experimental setup for each printing session can result in significant changes, a calibration procedure is developed to measure the system response. This calibration enables the extraction of the empirical MCA model parameters speci...