Mechanical integrated circuit materials.

Recent developments in autonomous engineered matter have introduced the ability for intelligent materials to process environmental stimuli and functionally adapt1-4. To formulate a foundation for such an engineered living material paradigm, researchers have introduced sensing5-11 and actuating12-16 functionalities in soft matter. Yet, information processing is the key functional element of autonomous engineered matter that has been recently explored through unconventional techniques with limited computing scalability17-20. Here we uncover a relation between Boolean mathematics and kinematically reconfigurable electrical circuits to realize all combinational logic operations in soft, conductive mechanical materials. We establish an analytical framework that minimizes the canonical functions of combinational logic by the Quine-McCluskey method, and governs the mechanical design of reconfigurable integrated circuit switching networks in soft matter. The resulting mechanical integrated circuit materials perform higher-level arithmetic, number comparison, and decode binary data to visual representations. We exemplify two methods to automate the design on the basis of canonical Boolean functions and individual gate-switching assemblies. We also increase the computational density of the materials by a monolithic layer-by-layer design approach. As the framework established here leverages mathematics and kinematics for system design, the proposed approach of mechanical integrated circuit materials can be realized on any length scale and in a wide variety of physics.

Towards enduring autonomous robots via embodied energy.

Autonomous robots comprise actuation, energy, sensory and control systems built from materials and structures that are not necessarily designed and integrated for multifunctionality. Yet, animals and other organisms that robots strive to emulate contain highly sophisticated and interconnected systems at all organizational levels, which allow multiple functions to be performed simultaneously. Herein, we examine how system integration and multifunctionality in nature inspires a new paradigm for autonomous robots that we call Embodied Energy. Whereas most untethered robots use batteries to store energy and power their operation, recent advancements in energy-storage techniques enable chemical or electrical energy sources to be embodied directly within the structures and materials used to create robots, rather than requiring separate battery packs. This perspective highlights emerging examples of Embodied Energy in the context of developing autonomous robots.

Mechanical computing.

Mechanical mechanisms have been used to process information for millennia, with famous examples ranging from the Antikythera mechanism of the Ancient Greeks to the analytical machines of Charles Babbage. More recently, electronic forms of computation and information processing have overtaken these mechanical forms, owing to better potential for miniaturization and integration. However, several unconventional computing approaches have recently been introduced, which blend ideas of information processing, materials science and robotics. This has raised the possibility of new mechanical computing systems that augment traditional electronic computing by interacting with and adapting to their environment. Here we discuss the use of mechanical mechanisms, and associated nonlinearities, as a means of processing information, with a view towards a framework in which adaptable materials and structures act as a distributed information processing network, even enabling information processing to be viewed as a material property, alongside traditional material properties such as strength and stiffness. We focus on approaches to abstract digital logic in mechanical systems, discuss how these systems differ from traditional electronic computing, and highlight the challenges and opportunities that they present.

Intelligent electroactive material systems with self-adaptive mechanical memory and sequential logic.

By synthesizing the requisite functionalities of intelligence in an integrated material system, it may become possible to animate otherwise inanimate matter. A significant challenge in this vision is to continually sense, process, and memorize information in a decentralized way. Here, we introduce an approach that enables all such functionalities in a soft mechanical material system. By integrating nonvolatile memory with continuous processing, we develop a sequential logic-based material design framework. Soft, conductive networks interconnect with embedded electroactive actuators to enable self-adaptive behavior that facilitates autonomous toggling and counting. The design principles are scaled in processing complexity and memory capacity to develop a model 8-bit mechanical material that can solve linear algebraic equations based on analog mechanical inputs. The resulting material system operates continually to monitor the current mechanical configuration and to autonomously search for solutions within a desired error. The methods created in this work are a foundation for future synthetic general intelligence that can empower materials to autonomously react to diverse stimuli in their environment.

Optomechanical computing in liquid crystal elastomers.

Embodied decision-making in soft, engineered matter has sparked recent interest towards the development of intelligent materials. Such decision-making capabilities can be realized in soft materials via digital information processing with combinational logic operations. Although previous research has explored soft material actuators and embedded logic in soft materials, achieving a high degree of autonomy in these material systems remains a challenge. Light is an ideal stimulus to trigger information processing in soft materials due to its low thermal effect and remote use. Thus, one approach for developing soft, autonomous materials is to integrate optomechanical computing capabilities in photoresponsive materials. Here, we establish a methodology to embed combinational logic circuitry in a photoresponsive liquid crystal elastomer (LCE) film. These LCEs are designed with embedded switches and integrated circuitry using liquid metal-based conductive traces. The resulting optomechanical computing LCEs can effectively process optical information via light, thermal, and mechanical energy conversion. The methods introduced in this work to fabricate a material capable of optical information processing can facilitate the implementation of a sense of sight in soft robotic systems and other compliant devices.

Topology optimization for the design of folding liquid crystal elastomer actuators.

Aligned liquid crystal elastomers (LCEs) are capable of undergoing large reversible shape change in response to thermal stimuli and may act as actuators for many potential applications such as self-assembly and deployment of micro devices. Recent advances in LCE patterning tools have demonstrated sub-millimetre control of director orientation, enabling the preparation of materials with arbitrarily complex director fields. However, without design tools to connect the 2D director pattern with the activated 3D shape, LCE design relies on intuition and trial and error. Here we present a design methodology to generate reliable folding in monolithic LCEs designed with topology optimization. The distributions of order/disorder and director orientations are optimized so that the remotely actuated deformation closely matches a target deformation for origami folding. The optimal design exhibits a strategy to counteract the mechanical frustration that may lead to an undesirable deformation, such as anti-clastic bending. Multi-hinge networks were developed using insights from the optimal hinge designs and were demonstrated through the fabrication and reversible actuation of a self-folding box. Topology optimization provides an important step towards leveraging the opportunities afforded by LCE patterning into functional designs.

Optical microscopy and confocal data of aerosol jet printed lines over a 16-hour print duration.

Optical microscopy images and confocal data for Aerosol Jet Printed (AJP) lines over a 16 hour print duration is provide in this dataset ("Mapping Drift in Morphology and Electrical Performance in Aerosol Jet Printing" [1]). Lines were uninterruptedly printed by AJP on a glass substrate using silver nanoparticle ink over a 16-hour time frame. The ink used for this experiment was a 0.6:0.3:0.2 mL mixture of Clariant Prelect TPS 50 G2 silver nanoparticle ink, ethylene glycol, and deionized water, respectively. Deposition was achieved with an Optomec AJ 300-UP Aerosol JetTM Deposition System using a Sprint Series Ultrasonic Atomizer MAX, aerodynamic filtering, and a nozzle having an orifice diameter of 150 µm. The typical focus ratio of 1.75 within standard range was used. The optical microscopic images of 350 µm AJP printed lines at 80 different time points were then selectively collected. Keyence VK-X200 with 150x magnification was used, which provided 50 µm to 267 pixel resolution image with more than 1000 cross-sections at each time point. Filtering of the pixels with outlying heights was performed with a multi-file analyzer. The dataset was primarily collected to understand system-level, temporal drifts in print morphology, which would further allow to predict electrical performance in time domain. Additional purposes for the dataset include: 1) benchmark dataset for morphology and print performance between AJP systems and print settings, 2) test data for new image filtering, segmentation, and classification algorithms and 3) baseline training data for real-time, in situ classification of operational time windows for AJP feedback control.

Digital logic gates in soft, conductive mechanical metamaterials.

Integrated circuits utilize networked logic gates to compute Boolean logic operations that are the foundation of modern computation and electronics. With the emergence of flexible electronic materials and devices, an opportunity exists to formulate digital logic from compliant, conductive materials. Here, we introduce a general method of leveraging cellular, mechanical metamaterials composed of conductive polymers to realize all digital logic gates and gate assemblies. We establish a method for applying conductive polymer networks to metamaterial constituents and correlate mechanical buckling modes with network connectivity. With this foundation, each of the conventional logic gates is realized in an equivalent mechanical metamaterial, leading to soft, conductive matter that thinks about applied mechanical stress. These findings may advance the growing fields of soft robotics and smart mechanical matter, and may be leveraged across length scales and physics.

Conductivity and radio frequency performance data for silver nanoparticle inks deposited via aerosol jet deposition and processed under varying conditions.

In fabricating electronic components or devices via Aerosol Jet Printing (AJP) there are numerous options for commercially available Metal NanoParticle (MNP) inks. Regardless of the MNP ink selected, the electrical properties of the final product are not commensurate to those of the bulk metal due to the inherent porosity and impurity-infused composition that is characteristic of these heterogeneous feedstock. Hence, choosing the best MNP ink for a particular application can be difficult, even among those based on the same metal, as each ink formulation can yield different performance metrics depending on the specific formulation and the conditions under which it is processed. In this article, the DC conductivity of AJP pads and the Radio Frequency (RF) transmission loss of AJP Coplanar Waveguides (CPWs) are presented for three different, commercially available silver MNP inks; Advanced Nano Products (ANP) Silverjet DGP 40LT-15C, Clariant Prelect TPS 50 G2, and UT Dots UTDAg40X. We determined conductivity values by measuring the printed pad thicknesses using stylus profilometry and measuring sheet resistances using a co-linear 4-point probe. Additionally, we collected RF spectra using a performance network analyzer over the 10 MHz - 40 GHz range. A complete description of the preparation, AJP procedure, and sintering is provided. Conductivity and RF data are presented for several scenarios including sintering temperatures, sintering atmospheres, and un-sintered storage conditions. We anticipate this dataset will serve as a useful reference for benchmarking electrical performance and troubleshooting pre- and post-processing steps for Ag nanoparticle based AJP inks.

Belousov-Zhabotinsky autonomic hydrogel composites: Regulating waves via asymmetry.

Belousov-Zhabotinsky (BZ) autonomic hydrogel composites contain active nodes of immobilized catalyst (Ru) encased within a nonactive matrix. Designing functional hierarchies of chemical and mechanical communication between these nodes enables applications ranging from encryption, sensors, and mechanochemical actuators to artificial skin. However, robust design rules and verification of computational models are challenged by insufficient understanding of the relative importance of local (molecular) heterogeneities, active node shape, and embedment geometry on transient and steady-state behavior. We demonstrate the predominance of asymmetric embedment and node shape in low-strain, BZ-gelatin composites and correlate behavior with gradients in BZ reactants. Asymmetric embedment of square and rectangular nodes results in directional steady-state waves that initiate at the embedded edge and propagate toward the free edge. In contrast, symmetric embedment does not produce preferential wave propagation because of a lack of diffusion gradient across the catalyzed region. The initiation at the embedded edge is correlated with bromide absorption by the inactive matrix, which locally elevates the bromate concentration required for catalyst oxidation. The competition between embedment asymmetry and node geometry was used to demonstrate a repeatable switch in wave direction that functions as a signal delay. Furthermore, signal propagation in or out of the composite was demonstrated via embedment asymmetry and relative dimensions of a T-shaped active network node. Overall, structural asymmetry provides a robust approach to controlling initiation and orientation of chemical-mechanical communication within composite BZ gels.

Synchronicity in composite hydrogels: Belousov-Zhabotinsky (BZ) active nodes in gelatin.

Synchronization of motion, task, or communication is responsible for the successful function of many living systems. Composite Belousov-Zhabotinsky (BZ) self-oscillating hydrogels exhibit a sufficiently complex chemical-mechanical feedback to develop synchrony and other dynamical behaviors. In the context of BZ gels, synchrony is the sustained, oscillating oxidation with constant phase of two or more catalyst-immobilized gel segments. However, design criteria to control chemical-mechanical synchronization through patterning of the reaction catalyst are lacking. To characterize the fundamental units of composite device design, the periodic oxidation behavior of isolated nodes, node pairs, and multinode systems were investigated. Isolated nodes of Ru-immobilized gelatin exhibited three distinct, volume-dependent, regimes of oscillation: (i) long period (10-40 min), (ii) biperiod (mix of long and short), and (iii) short period (2.5 min). Node pairs and multinode grids of Ru gelatin were embedded in plain gelatin through a film stacking or 3D printing technique. The fraction of synchronized node pairs decreased with increasing interspace distance. Embedment increased the probability of synchronization, with 100% synchronization for interspace distances of less than 10 times the characteristic length of the reaction-diffusion process. The phase difference between synchronized node pairs transitioned from in-phase at small interspace distances to antiphase at large distances, providing the first experimental verification of antiphase synchrony in composite BZ gels. From these design criteria and fabrication techniques, the chemical-mechanical feedback of BZ composites can be programmed through strategic patterning of the catalyst to build BZ devices for sensor, trigger, or chemical computing applications.

Shape-reprogrammable polymers: encoding, erasing, and re-encoding.

Shape-reprogramming in a polymer is demonstrated, where prescribed 3D geometric information can be encoded, decoded, erased, and re-encoded. In essence, the shape-reprogrammable polymer (SRP) acts as computer hardware that can be reformatted and reprogrammed repeatedly. Such SRPs have the potential to be repurposed directly without going through material disposal and recycling.

Quantification of embryonic atrioventricular valve biomechanics during morphogenesis.

Tissue assembly in the developing embryo is a rapid and complex process. While much research has focused on genetic regulatory machinery, understanding tissue level changes such as biomechanical remodeling remains a challenging experimental enigma. In the particular case of embryonic atrioventricular valves, micro-scale, amorphous cushions rapidly remodel into fibrous leaflets while simultaneously interacting with a demanding mechanical environment. In this study we employ two microscale mechanical measurement systems in conjunction with finite element analysis to quantify valve stiffening during valvulogenesis. The pipette aspiration technique is compared to a uniaxial load deformation, and the analytic expression for a uniaxially loaded bar is used to estimate the nonlinear material parameters of the experimental data. Effective modulus and strain energy density are analyzed as potential metrics for comparing mechanical stiffness. Avian atrioventricular valves from globular Hamburger-Hamilton stages HH25-HH34 were tested via the pipette method, while the planar HH36 leaflets were tested using the deformable post technique. Strain energy density between HH25 and HH34 septal leaflets increased 4.6±1.8 fold (±SD). The strain energy density of the HH36 septal leaflet was four orders of magnitude greater than the HH34 pipette result. Our results establish morphological thresholds for employing the micropipette aspiration and deformable post techniques for measuring uniaxial mechanical properties of embryonic tissues. Quantitative biomechanical analysis is an important and underserved complement to molecular and genetic experimentation of embryonic morphogenesis.

Computational simulation of hemodynamic-driven growth and remodeling of embryonic atrioventricular valves.

Embryonic heart valves develop under continuous and demanding hemodynamic loading. The particular contributions of fluid pressure and shear tractions in valve morphogenesis are difficult to decouple experimentally. To better understand how fluid loads could direct valve formation, we developed a computational model of avian embryonic atrioventricular (AV) valve (cushion) growth and remodeling using experimentally derived parameters for the blood flow and the cushion stiffness. Through an iterative scheme, we first solved the fluid loads on the axisymmetric AV canal and cushion model geometry. We then applied the fluid loads to the cushion and integrated the evolution equations to determine the growth and remodeling. After a set time of growth, we updated the fluid domain to reflect the change in cushion geometry and resolved for the fluid forces. The rate of growth and remodeling was assumed to be a function of the difference between the current stress and an isotropic homeostatic stress state. The magnitude of the homeostatic stress modulated the rate of volume addition during the evolution. We found that the pressure distribution on the AV cushion was sufficient to generate leaflet-like elongation in the direction of flow, through inducing tissue resorption on the inflow side of cushion and expansion on the outflow side. Conversely, shear tractions minimally altered tissue volume, but regulated the remodeling of tissue near the cushion surface, particular at the leading edge. Significant shear and circumferential residual stresses developed as the cushion evolved. This model offers insight into how natural and perturbed mechanical environments may direct AV valvulogenesis and provides an initial framework on which to incorporate more mechano-biological details.

Serotonin potentiates transforming growth factor-beta3 induced biomechanical remodeling in avian embryonic atrioventricular valves.

Embryonic heart valve primordia (cushions) maintain unidirectional blood flow during development despite an increasingly demanding mechanical environment. Recent studies demonstrate that atrioventricular (AV) cushions stiffen over gestation, but the molecular mechanisms of this process are unknown. Transforming growth factor-beta (TGFß) and serotonin (5-HT) signaling modulate tissue biomechanics of postnatal valves, but less is known of their role in the biomechanical remodeling of embryonic valves. In this study, we demonstrate that exogenous TGFß3 increases AV cushion biomechanical stiffness and residual stress, but paradoxically reduces matrix compaction. We then show that TGFß3 induces contractile gene expression (RhoA, aSMA) and extracellular matrix expression (col1α2) in cushion mesenchyme, while simultaneously stimulating a two-fold increase in proliferation. Local compaction increased due to an elevated contractile phenotype, but global compaction appeared reduced due to proliferation and ECM synthesis. Blockade of TGFß type I receptors via SB431542 inhibited the TGFß3 effects. We next showed that exogenous 5-HT does not influence cushion stiffness by itself, but synergistically increases cushion stiffness with TGFß3 co-treatment. 5-HT increased TGFß3 gene expression and also potentiated TGFß3 induced gene expression in a dose-dependent manner. Blockade of the 5HT2b receptor, but not 5-HT2a receptor or serotonin transporter (SERT), resulted in complete cessation of TGFß3 induced mechanical strengthening. Finally, systemic 5-HT administration in ovo induced cushion remodeling related defects, including thinned/atretic AV valves, ventricular septal defects, and outflow rotation defects. Elevated 5-HT in ovo resulted in elevated remodeling gene expression and increased TGFß signaling activity, supporting our ex-vivo findings. Collectively, these results highlight TGFß/5-HT signaling as a potent mechanism for control of biomechanical remodeling of AV cushions during development.