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Acoustic/elastic metamaterials that rely on engineered microstructures instead of chemical composition enable a rich variety of extraordinary effective properties that are suited for various applications including vibration/noise isolation, high-resolution medical imaging, and energy harvesting and mitigation. However, the static nature of these elastic wave guides limits their potential for active elastic-wave guiding, as microstructure transformation remains a challenge to effectively apply in traditional elastic metamaterials due to the interplay of polarization and structural sensitivity. Here, a tunable, locally resonant structural waveguide is proposed and demonstrated for active vibration bandgap switching and elastic-wave manipulation between 1000–4000 Hz based on 3D printed building blocks of zinc-neutralized poly(ethylene- co -methacrylic acid) ionomer (Surlyn 9910). The ionomer exhibits shape memory behavior to enable rearrangement into new shape patterns through application of thermal stimuli that tunes mechanical performance in both space and time dimensions (4D metamaterial). The thermally induced shape-reorganization is programed to flip a series of frequency bands from passbands to bandgaps and vice versa . The continuously switched bandwidth can exceed 500 Hz. Consequently, altering the bandgap from “on” to “off” produces programmable elastic-wave propagation paths to achieve active wave guiding phenomena. An anisotropic cantilever-in-mass model is demonstrated to predict the self-adaptive dynamic responses of the printed structures with good agreement between the analytical work and experimental results. The tunable metamaterial-based waveguides illustrate the potential of 4D printed shape memory polymers in the designing and manufacturing of intelligent devices for elastic-wave control and vibration isolation. 

Efficiently and accurately simulating partial differential equations(PDEs) in and around arbitrarily defined geometries, especially with high levels of adaptivity, has significant implications for different application domains. A key bottleneck in the above process is the fast construction of a "good" adaptively-refined mesh. In this work, we present an efficient novel octree-based adaptive discretization approach capable of caring out arbitrarily shaped void regions from the parent domain: an essential requirement for fluid simulations around complex objects. 

Drug development suffers from a lack of predictive and human-relevant in vitro models. Organ-on-chip (OOC) technology provides advanced culture capabilities to generate physiologically appropriate, human-based tissue in vitro , therefore providing a route to a predictive in vitro model. However, OOC technologies are often created at the expense of throughput, industry-standard form factors, and compatibility with state-of-the-art data collection tools. Here we present an OOC platform with advanced culture capabilities supporting a variety of human tissue models including liver, vascular, gastrointestinal, and kidney. The platform has 96 devices per industry standard plate and compatibility with contemporary high-throughput data collection tools. Specifically, we demonstrate programmable flow control over two physiologically relevant flow regimes: perfusion flow that enhances hepatic tissue function and high-shear stress flow that aligns endothelial monolayers. In addition, we integrate electrical sensors, demonstrating quantification of barrier function of primary gut colon tissue in real-time. We utilize optical access to the tissues to directly quantify renal active transport and oxygen consumption via integrated oxygen sensors. Finally, we leverage the compatibility and throughput of the platform to screen all 96 devices using high content screening (HCS) and evaluate gene expression using RNA sequencing (RNA-seq). By combining these capabilities in one platform, physiologically-relevant tissues can be generated and measured, accelerating optimization of an in vitro model, and ultimately increasing predictive accuracy of in vitro drug screening.