Modular Morphing Lattices for Large-Scale Underwater Continuum Robotic Structures.

In this study, we present a method to construct meter-scale deformable structures for underwater robotic applications by discretely assembling mechanical metamaterials. We address the challenge of scaling up nature-like deformable structures while remaining structurally efficient by combining rigid and compliant facets to form custom unit cells that assemble into lattices. The unit cells generate controlled local anisotropies that architect the global deformation of the robotic structure. The resulting flexibility allows better unsteady flow control that enables highly efficient propulsion and optimized force profile manipulations. We demonstrate the utility of this approach in two models. The first is a morphing beam snake-like robot that can generate thrust at specific anguilliform swimming parameters. The second is a morphing surface hydrofoil that, when compared with a rigid wing at the same angles of attack (AoAs), can increase the lift coefficient up to 0.6. In addition, in lower AoAs, the L∕D ratio improves by 5 times, whereas in higher angles it improves by 1.25 times. The resulting hydrodynamic performance demonstrates the potential to achieve accessible, scalable, and simple to design and assemble morphing structures for more efficient and effective future ocean exploration and exploitation.

Toughening and Healing of CFRPs by Diels-Alder-Based Nano-Modified Resin through Melt Electro-Writing Process Technique.

In the current study, a novel approach in terms of the incorporation of self-healing agent (SHA) into unidirectional (UD) carbon fiber reinforced plastics (CFRPs) has been demonstrated. More precisely, Diels-Alder (DA) mechanism-based resin (Bis-maleimide type) containing or not four layered graphene nanoplatelets (GNPs) at the amount of 1 wt% was integrated locally in the mid-thickness area of CFRPs by melt electro-writing process (MEP). Based on that, CFRPs containing or not SHA were fabricated and further tested under Mode I interlaminar fracture toughness experiments. According to experimental results, modified CFRPs exhibited a considerable enhancement in the interlaminar fracture toughness properties (peak load (Pmax) and fracture toughness energy I (GIC) values). After Mode I interlaminar fracture toughness testing, the damaged samples followed the healing process and then were tested again under identical experimental conditions. The repeating of the tests revealed moderate healing efficiency (H.E.) since part of the interlaminar fracture toughness properties were restored. Furthermore, three-point bending (3PB) experiments were conducted, with the aim of assessing the effect of the incorporated SHA on the in-plane mechanical properties of the final CFRPs. Finally, optical microscopy (OM) examinations were performed to investigate the activated/involved damage mechanisms.

Discretely assembled mechanical metamaterials.

Mechanical metamaterials offer exotic properties based on local control of cell geometry and their global configuration into structures and mechanisms. Historically, these have been made as continuous, monolithic structures with additive manufacturing, which affords high resolution and throughput, but is inherently limited by process and machine constraints. To address this issue, we present a construction system for mechanical metamaterials based on discrete assembly of a finite set of parts, which can be spatially composed for a range of properties such as rigidity, compliance, chirality, and auxetic behavior. This system achieves desired continuum properties through design of the parts such that global behavior is governed by local mechanisms. We describe the design methodology, production process, numerical modeling, and experimental characterization of metamaterial behaviors. This approach benefits from incremental assembly, which eliminates scale limitations, best-practice manufacturing for reliable, low-cost part production, and interchangeability through a consistent assembly process across part types.

Machine learning metrology of cell confinement in melt electrowritten three-dimensional biomaterial substrates.

Tuning cell shape by altering the biophysical properties of biomaterial substrates on which cells operate would provide a potential shape-driven pathway to control cell phenotype. However, there is an unexplored dimensional scale window of three-dimensional (3D) substrates with precisely tunable porous microarchitectures and geometrical feature sizes at the cell's operating length scales (10-100 µm). This paper demonstrates the fabrication of such high-fidelity fibrous substrates using a melt electrowriting (MEW) technique. This advanced manufacturing approach is biologically qualified with a metrology framework that models and classifies cell confinement states under various substrate dimensionalities and architectures. Using fibroblasts as a model cell system, the mechanosensing response of adherent cells is investigated as a function of variable substrate dimensionality (2D vs. 3D) and porous microarchitecture (randomly oriented, "non-woven" vs. precision-stacked, "woven"). Single-cell confinement states are modeled using confocal fluorescence microscopy in conjunction with an automated single-cell bioimage data analysis workflow that extracts quantitative metrics of the whole cell and sub-cellular focal adhesion protein features measured. The extracted multidimensional dataset is employed to train a machine learning algorithm to classify cell shape phenotypes. The results show that cells assume distinct confinement states that are enforced by the prescribed substrate dimensionalities and porous microarchitectures with the woven MEW substrates promoting the highest cell shape homogeneity compared to non-woven fibrous substrates. The technology platform established here constitutes a significant step towards the development of integrated additive manufacturing-metrology platforms for a wide range of applications including fundamental mechanobiology studies and 3D bioprinting of tissue constructs to yield specific biological designs qualified at the single-cell level.

Influence of Transition Metal Dichalcogenide Surfaces on Cellular Morphology and Adhesion.

This article presents the effect of transition metal dichalcogenide (TMD) surfaces and their geometric arrangements on resulting cellular morphology and adhesion. WS2 and MoS2 on SiO2 and polydimethylsiloxane (PDMS) substrates were utilized as cell culture platforms, and cell-substrate interactions were probed via analysis of cellular morphometric features (i.e., cell area and circularity) of neonatal human dermal fibroblasts (NHDFs) and metrology of TMD surfaces. It was quantitatively confirmed that the presence of TMDs on substrates resulted in an overall enhanced cellular morphology, even on SiO2 substrates adverse to cellular adhesion. On a localized scale, distinct TMD geometric features at sites of adhesion were measured and correlated with the observed cell morphology. Geometric parameters of TMDs, including TMD island count and total TMD area, exhibited positive correlations with the resulting morphology of cells by enhancing cellular areas and elongations. Further, geometric properties were compared to cell area per TMD island, and positive correlations were observed with TMD island size parameters. Cells adhered at heterogeneous locations with combinations of exposed TMD and SiO2, demonstrating an enhanced morphology in relation to the number of TMD islands in a cell's local area and the geometric size parameters of TMD islands within the cell's operating length scale. The proposed mechanisms of cellular adhesion on TMD-modified surfaces are attributed to the role of surface properties (e.g., stiffness, friction, and hydrophobicity) of TMD and underlying SiO2 and their combined effects during progressive stages of cellular adhesion. These findings provide insight toward possibilities of tailoring adhesion of cells guided by geometric parameters of TMDs.

Numerical investigation of dynamic microorgan devices as drug screening platforms. Part I: Macroscale modeling approach & validation.

The dynamic nature of in vitro drug metabolism models demands reliable numerical tools to determine key design parameter values towards high-fidelity cell-based platforms of in vivo drug metabolism. This paper represents the first of a two-part model-based investigation of a 3D dynamic microorgan device (DMD). The prescribed tissue model in this paper is precisely embedded within a DMD by 3D bioprinting hydrogel encapsulated liver cells into a patterned array of microchannels. A perfusing drug substrate is biotransformed by liver cells encapsulated within porous hydrogel walls. Therefore, the free and porous flow regime equations are first solved in tandem to derive the laminar velocity profile and wall shear stresses in the entire shear-mediated flow regime. These equations are then coupled with a convection-diffusion equation and Michaelis-Menten reaction terms, resulting in an effective convection-diffusion-cell kinetics model. A key consideration addressed herein is mechanotransduction where shear stresses on the encapsulated cells alter subcellular liver enzyme reaction rates. Cells are incorporated into the geometric model implicitly (macroscale) as enzyme reaction structures uniformly distributed throughout the DMD length. Transient simulations enable effluent drug metabolite profile determination wherein the proposed macroscale modeling approach is validated with an experimental drug flow study.

Numerical investigation of dynamic microorgan devices as drug screening platforms. Part II: Microscale modeling approach and validation.

The authors have previously reported a rigorous macroscale modeling approach for an in vitro 3D dynamic microorgan device (DMD). This paper represents the second of a two-part model-based investigation where the effect of microscale (single liver cell-level) shear-mediated mechanotransduction on drug biotransformation is deconstructed. Herein, each cell is explicitly incorporated into the geometric model as single compartmentalized metabolic structures. Each cell's metabolic activity is coupled with the microscale hydrodynamic Wall Shear Stress (WSS) simulated around the cell boundary through a semi-empirical polynomial function as an additional reaction term in the mass transfer equations. Guided by the macroscale model-based hydrodynamics, only 9 cells in 3 representative DMD domains are explicitly modeled. Dynamic and reaction similarity rules based on non-dimensionalization are invoked to correlate the numerical and empirical models, accounting for the substrate time scales. The proposed modeling approach addresses the key challenge of computational cost towards modeling complex large-scale DMD-type system with prohibitively high cell densities. Transient simulations are implemented to extract the drug metabolite profile with the microscale modeling approach validated with an experimental drug flow study. The results from the author's study demonstrate the preferred implementation of the microscale modeling approach over that of its macroscale counterpart.