Showing papers by "Wright-Patterson Air Force Base published in 2020"

Strain engineering and epitaxial stabilization of halide perovskites.

Abstract: Strain engineering is a powerful tool with which to enhance semiconductor device performance1,2. Halide perovskites have shown great promise in device applications owing to their remarkable electronic and optoelectronic properties3–5. Although applying strain to halide perovskites has been frequently attempted, including using hydrostatic pressurization6–8, electrostriction9, annealing10–12, van der Waals force13, thermal expansion mismatch14, and heat-induced substrate phase transition15, the controllable and device-compatible strain engineering of halide perovskites by chemical epitaxy remains a challenge, owing to the absence of suitable lattice-mismatched epitaxial substrates. Here we report the strained epitaxial growth of halide perovskite single-crystal thin films on lattice-mismatched halide perovskite substrates. We investigated strain engineering of α-formamidinium lead iodide (α-FAPbI3) using both experimental techniques and theoretical calculations. By tailoring the substrate composition—and therefore its lattice parameter—a compressive strain as high as 2.4 per cent is applied to the epitaxial α-FAPbI3 thin film. We demonstrate that this strain effectively changes the crystal structure, reduces the bandgap and increases the hole mobility of α-FAPbI3. Strained epitaxy is also shown to have a substantial stabilization effect on the α-FAPbI3 phase owing to the synergistic effects of epitaxial stabilization and strain neutralization. As an example, strain engineering is applied to enhance the performance of an α-FAPbI3-based photodetector. A method of deposition of mixed-cation hybrid perovskite films as lattice-mismatched substrates for an α-FAPbI3 film is described, giving strains of up to 2.4 per cent while also stabilizing the metastable α-FAPbI3 phase for several hundred days.

Controlling interdependent meso-nanosecond dynamics and defect generation in metal 3D printing

Abstract: State-of-the-art metal 3D printers promise to revolutionize manufacturing, yet they have not reached optimal operational reliability. The challenge is to control complex laser-powder-melt pool interdependency (dependent upon each other) dynamics. We used high-fidelity simulations, coupled with synchrotron experiments, to capture fast multitransient dynamics at the meso-nanosecond scale and discovered new spatter-induced defect formation mechanisms that depend on the scan strategy and a competition between laser shadowing and expulsion. We derived criteria to stabilize the melt pool dynamics and minimize defects. This will help improve build reliability.

Tunable quadruple-well ferroelectric van der Waals crystals.

Abstract: The family of layered thio- and seleno-phosphates has gained attention as potential control dielectrics for the rapidly growing family of two-dimensional and quasi-two-dimensional electronic materials. Here we report a combination of density functional theory calculations, quantum molecular dynamics simulations and variable-temperature, -pressure and -bias piezoresponse force microscopy data to predict and verify the existence of an unusual ferroelectric property—a uniaxial quadruple potential well for Cu displacements—enabled by the van der Waals gap in copper indium thiophosphate (CuInP2S6). The calculated potential energy landscape for Cu displacements is strongly influenced by strain, accounting for the origin of the negative piezoelectric coefficient and rendering CuInP2S6 a rare example of a uniaxial multi-well ferroelectric. Experimental data verify the coexistence of four polarization states and explore the temperature-, pressure- and bias-dependent piezoelectric and ferroelectric properties, which are supported by bias-dependent molecular dynamics simulations. These phenomena offer new opportunities for both fundamental studies and applications in data storage and electronics. The atomic displacements that generate ferroelectricity in materials commonly fit a double-well potential energy surface. Here, ferroelectricity in two-dimensional CuInP2S6 is shown to fit a quadruple well due to the van der Waals gap between layers of this material.

Point-of-Use Detection of Environmental Fluoride via a Cell-Free Riboswitch-Based Biosensor.

Abstract: Advances in biosensor engineering have enabled the design of programmable molecular systems to detect a range of pathogens, nucleic acids, and chemicals. Here, we engineer and field-test a biosensor for fluoride, a major groundwater contaminant of global concern. The sensor consists of a cell-free system containing a DNA template that encodes a fluoride-responsive riboswitch regulating genes that produce a fluorescent or colorimetric output. Individual reactions can be lyophilized for long-term storage and detect fluoride at levels above 2 ppm, the Environmental Protection Agency's most stringent regulatory standard, in both laboratory and field conditions. Through onsite detection of fluoride in a real-world water source, this work provides a critical proof-of-principle for the future engineering of riboswitches and other biosensors to address challenges for global health and the environment.

An Overview of the Thermomechanical Processing of α/β Titanium Alloys: Current Status and Future Research Opportunities

Abstract: Current understanding of the principles underlying the thermomechanical processing (TMP) of α/β titanium alloys is reviewed. Attention is focused on the formulation of constitutive descriptions for plastic flow under hot-working conditions, the evolution of microstructure, the occurrence of defects, and novel/emerging TMP techniques. With regard to constitutive behavior, descriptions of the plastic flow of the individual phases and two-phase alloys per se are summarized. The important influence of phase morphology, size, and volume fraction on plastic flow is emphasized. Mechanisms which underlie microstructure evolution include beta recrystallization (in the high-temperature β field), the development of dislocation substructure and its effect on dynamic and static spheroidization of colony microstructures (in the two-phase field), static and dynamic coarsening of primary α, and the development of deformation and transformation textures. In the area of defects, the effect of TMP variables and starting microstructure on the formation of cavities, the persistence of microtexture, and the development of undesirably-coarse β grain structures are described. The current status of relatively new processing techniques for α/β titanium alloys such as low-temperature superplastic forming and solid-state joining (via linear friction or friction-stir methods) are also briefly reviewed. Last, R&D which could help to resolve deficiencies in the current knowledge base for TMP of α/β titanium alloys are summarized for each of the areas.

Ultrafast pyroelectric photodetection with on-chip spectral filters.

Abstract: Thermal detectors, such as bolometric, pyroelectric and thermoelectric devices, are uniquely capable of sensing incident radiation for any electromagnetic frequency; however, the response times of practical devices are typically on the millisecond scale1–7. By integrating a plasmonic metasurface with an aluminium nitride pyroelectric thin film, we demonstrate spectrally selective, room-temperature pyroelectric detectors from 660–2,000 nm with an instrument-limited 1.7 ns full width at half maximum and 700 ps rise time. Heat generated from light absorption diffuses through the subwavelength absorber into the pyroelectric film producing responsivities up to 0.18 V W−1 due to the temperature-dependent spontaneous polarization of the pyroelectric films. Moreover, finite-element simulations reveal the possibility of reaching a 25 ps full width at half maximum and 6 ps rise time rivalling that of semiconductor photodiodes8. This design approach has the potential to realize large-area, inexpensive gigahertz pyroelectric detectors for wavelength-specific detection from the ultraviolet to short-wave infrared or beyond for, for example, high-speed hyperspectral imaging. The ultrafast response of a pyroelectric sensor with near-infrared responsivity is demonstrated by combining a pyroelectric thermal detector with wavelength-selective nanoparticle absorbers.

Charge-programmed three-dimensional printing for multi-material electronic devices

Abstract: Three-dimensional (3D) printing can create complex geometries that could be of use in the development of electronics. However, the approach is mainly limited to non-functional structural materials, and the 3D printing of electronic devices typically requires multiple process stages of embedding, spraying and writing. Here, we report a 3D printing approach that can volumetrically deposit multiple functional materials within arbitrary 3D layouts to create electronic devices in a single step. Our approach prints 3D structures with a programmable mosaic of distinct surface charge regions, creating a platform to deposit functional materials into complex architectures based on localized electrostatic attraction. The technique allows selective volumetric depositions of single metals and also diverse active material combinations, including ceramic, semiconducting, magnetic and colloidal materials, into site-specific 3D topologies. To illustrate the capabilities of our approach, we use it to fabricate devices with 3D electronic interfaces that can be used for tactile sensing, internal wave mapping and shape self-sensing. A 3D printing technique that produces structures with programmable patterns of charged surface, allowing different functional materials to be deposited in pre-defined regions, can be used to create electronic devices with a single printing step.

Improved Geometric Path Enumeration for Verifying ReLU Neural Networks

Abstract: Neural networks provide quick approximations to complex functions, and have been increasingly used in perception as well as control tasks. For use in mission-critical and safety-critical applications, however, it is important to be able to analyze what a neural network can and cannot do. For feed-forward neural networks with ReLU activation functions, although exact analysis is NP-complete, recently-proposed verification methods can sometimes succeed.

From the beaker to the body: translational challenges for electrochemical, aptamer-based sensors

Abstract: The ultimate goal of implantable bioanalytical sensors is to enable the continuous and precise monitoring of clinically and physiologically important targets in the body for prolonged periods. Electrochemical, aptamer-based (E-AB) sensors already achieve this goal in a modular way, so far allowing the multihour in vivo monitoring of over half a dozen molecular targets without relying on their specific chemical reactivities. E-AB sensors achieve this modularity by employing nucleic acid aptamers as recognition elements, which can reversibly and selectively bind to molecular targets even in complex biological fluids such as unprocessed blood. However, the translation of the E-AB platform from bench-top, in vitro proof-of-concept demonstrations to truly relevant in vivo clinical applications still faces challenges, some of which are dependent on innovations in the fields of material sciences, interfacial chemistry, biomedical engineering and data management. In this review we critically discuss some of the challenges that the E-AB platform still needs to overcome before it can achieve full, unhindered translation to biomedical and clinical research, decentralized diagnostics and medical applications.

Oxidation of Gallium-based Liquid Metal Alloys by Water

Abstract: Gallium alloys with other low melting point metals, such as indium or tin, to form room-temperature liquid eutectic systems. The gallium in the alloys rapidly forms a thin surface oxide when exposed to ambient oxygen. This surface oxide has been previously exploited for self-stabilization of liquid metal nanoparticles, retention of metastable shapes, and imparting stimuli-responsive behavior to the alloy surface. In this work, we study the effect of water as an oxidant and its role in defining the alloy surface chemistry. We identify several pathways that can lead to the formation of gallium oxide hydroxide (GaOOH) crystallites, which may be undesirable in many applications. Furthermore, we find that some crystallite formation pathways can be reinforced by typical top-down particle synthesis techniques like sonication. This improved understanding of interfacial interactions provides critical insight for process design and implementation of advanced devices that utilize the unique coupling of flexibility and conductivity offered by these gallium-based liquid metal alloys.

Nanoscale electro-thermal interactions in AlGaN/GaN high electron mobility transistors

Abstract: Self-heating in AlGaN/GaN high electron mobility transistors (HEMTs) negatively impacts device performance and reliability. Under nominal operating conditions, a hot-spot in the device channel develops under the drain side corner of the gate due to a concentration of volumetric heat generation leading to nonequilibrium carrier interactions and non-Fourier heat conduction. These subcontinuum effects obscure identification of the most salient processes impacting heating. In response, we examine self-heating in GaN-on-Si HEMTs via measurements of channel temperature using above-bandgap UV thermoreflectance imaging in combination with fully coupled electrothermal modeling. The methods together highlight the interplay of heat concentration and subcontinuum thermal transport showing that channel temperature cannot be determined solely by continuum scale heat transfer principles. Under conditions of equal power dissipation (PDISS = VDS × IDS = 250 mW), for example, a higher VDS bias (∼23 V) resulted in an ∼44% larger rise in peak junction temperature compared to that for a lower VDS (∼7.5 V) condition. The difference arises primarily due to reduction in the heat generating volume when operating under partially pinched-off (i.e., high VDS) conditions. Self-heating amplifies with this reduction as heating now takes place primarily over length scales less than the mean free path of the phonons tasked with energy dissipation. Being less efficient, the subcontinuum transport restricts thermal transport away from the device hot-spot causing a net increase in channel temperature. Taken together, even purely thermally driven device mean-time-to-failure is not, therefore, based on power dissipation alone as both bias dependence and subcontinuum thermal transport influence device lifetime.

Melanin Produced by the Fast-Growing Marine Bacterium Vibrio natriegens through Heterologous Biosynthesis: Characterization and Application.

Abstract: Melanin is a pigment produced by organisms throughout all domains of life. Due to its unique physicochemical properties, biocompatibility, and biostability, there has been an increasing interest in the use of melanin for broad applications. In the vast majority of studies, melanin has been either chemically synthesized or isolated from animals, which has restricted its use to small-scale applications. Using bacteria as biocatalysts is a promising and economical alternative for the large-scale production of biomaterials. In this study, we engineered the marine bacterium Vibrio natriegens, one of the fastest-growing organisms, to synthesize melanin by expressing a heterologous tyrosinase gene and demonstrated that melanin production was much faster than in previously reported heterologous systems. The melanin of V. natriegens was characterized as a polymer derived from dihydroxyindole-2-carboxylic acid (DHICA) and, similarly to synthetic melanin, exhibited several characteristic and useful features. Electron microscopy analysis demonstrated that melanin produced from V. natriegens formed nanoparticles that were assembled as "melanin ghost" structures, and the photoprotective properties of these particles were validated by their protection of cells from UV irradiation. Using a novel electrochemical reverse engineering method, we observed that melanization conferred redox activity to V. natriegens Moreover, melanized bacteria were able to quickly adsorb the organic compound trinitrotoluene (TNT). Overall, the genetic tractability, rapid division time, and ease of culture provide a set of attractive properties that compare favorably to current E. coli production strains and warrant the further development of this chassis as a microbial factory for natural product biosynthesis.IMPORTANCE Melanins are macromolecules that are ubiquitous in nature and impart a large variety of biological functions, including structure, coloration, radiation resistance, free radical scavenging, and thermoregulation. Currently, in the majority of investigations, melanins are either chemically synthesized or extracted from animals, which presents significant challenges for large-scale production. Bacteria have been used as biocatalysts to synthesize a variety of biomaterials due to their fast growth and amenability to genetic engineering using synthetic biology tools. In this study, we engineered the extremely fast-growing bacterium V. natriegens to synthesize melanin nanoparticles by expressing a heterologous tyrosinase gene with inducible promoters. Characterization of the melanin produced from V. natriegens-produced tyrosinase revealed that it exhibited physical and chemical properties similar to those of natural and chemically synthesized melanins, including nanoparticle structure, protection against UV damage, and adsorption of toxic compounds. We anticipate that producing and controlling melanin structures at the nanoscale in this bacterial system with synthetic biology tools will enable the design and rapid production of novel biomaterials for multiple applications.

Individual Differences in Trust in Autonomous Robots: Implications for Transparency

Abstract: The introduction of increasingly intelligent and autonomous systems raises novel human factors challenges for human–machine teaming. People utilize differing mental models in understanding the functioning of complex systems that may be capable of social agency. Operators may perceive the machine as either a complex tool or a humanlike teammate. When the “advanced tool” mental model is adopted, operator trust may reflect individual differences in expectations of automation. By contrast, when the “teammate” mental model is activated, trust may depend on evaluative attitudes to robots. This article investigates predictors of trust in an autonomous robot detecting threat on either a physics-based or psychological basis. Distinct dimensions of physics-based and psychological trust are identified, corresponding to advanced tool and team mental models, respectively. Dispositional perceptions of automation, measured with the perfect automation schema scale, are associated with both aspects of trust. By contrast, the negative attitudes toward robots scale is specifically associated with lower psychological trust. The findings suggest that transparency information should be designed for compatibility with the operator's mental model in order to support accurate trust calibration and situation awareness. Transparency may be personalized to emphasize either the machine's data-analytic capabilities (advanced tool) or its humanlike social functioning (teammate).

Autonomous materials discovery driven by Gaussian process regression with inhomogeneous measurement noise and anisotropic kernels.

Abstract: A majority of experimental disciplines face the challenge of exploring large and high-dimensional parameter spaces in search of new scientific discoveries. Materials science is no exception; the wide variety of synthesis, processing, and environmental conditions that influence material properties gives rise to particularly vast parameter spaces. Recent advances have led to an increase in the efficiency of materials discovery by increasingly automating the exploration processes. Methods for autonomous experimentation have become more sophisticated recently, allowing for multi-dimensional parameter spaces to be explored efficiently and with minimal human intervention, thereby liberating the scientists to focus on interpretations and big-picture decisions. Gaussian process regression (GPR) techniques have emerged as the method of choice for steering many classes of experiments. We have recently demonstrated the positive impact of GPR-driven decision-making algorithms on autonomously-steered experiments at a synchrotron beamline. However, due to the complexity of the experiments, GPR often cannot be used in its most basic form, but rather has to be tuned to account for the special requirements of the experiments. Two requirements seem to be of particular importance, namely inhomogeneous measurement noise (input-dependent or non-i.i.d.) and anisotropic kernel functions, which are the two concepts that we tackle in this paper. Our synthetic and experimental tests demonstrate the importance of both concepts for experiments in materials science and the benefits that result from including them in the autonomous decision-making process.

Efficient Closed-loop Maximization of Carbon Nanotube Growth Rate using Bayesian Optimization.

Abstract: A major technological challenge in materials research is the large and complex parameter space, which hinders experimental throughput and ultimately slows down development and implementation. In single-walled carbon nanotube (CNT) synthesis, for instance, the poor yield obtained from conventional catalysts is a result of limited understanding of input-to-output correlations. Autonomous closed-loop experimentation combined with advances in machine learning (ML) is uniquely suited for high-throughput research. Among the ML algorithms available, Bayesian optimization (BO) is especially apt for exploration and optimization within such high-dimensional and complex parameter space. BO is an adaptive sequential design algorithm for finding the global optimum of a black-box objective function with the fewest possible measurements. Here, we demonstrate a promising application of BO in CNT synthesis as an efficient and robust algorithm which can (1) improve the growth rate of CNT in the BO-planner experiments over the seed experiments up to a factor 8; (2) rapidly improve its predictive power (or learning); (3) Consistently achieve good performance regardless of the number or origin of seed experiments; (4) exploit a high-dimensional, complex parameter space, and (5) achieve the former 4 tasks in just over 100 hundred experiments (~8 experimental hours) - a factor of 5× faster than our previously reported results.

Giant Nonreciprocity of Surface Acoustic Waves enabled by the Magnetoelastic Interaction

Abstract: Nonreciprocity, the defining characteristic of isolators, circulators and a wealth of other applications in radio/microwave communications technologies, is in general difficult to achieve as most physical systems incorporate symmetries that prevent the effect. In particular, acoustic waves are an important medium for information transport, but they are inherently symmetric in time. In this work, we report giant nonreciprocity in the transmission of surface acoustic waves (SAWs) on lithium niobate substrate coated with ferromagnet/insulator/ferromagnet (FeGaB/Al2O3/FeGaB) multilayer structure. We exploit this novel structure with a unique asymmetric band diagram, and expand on magnetoelastic coupling theory to show how the magnetic bands couple with acoustic waves only in a single direction. We measure 48.4 dB (ratio of 1:100,000) isolation which outperforms current state of the art microwave isolator devices in a novel acoustic wave system that facilitates unprecedented size, weight, and power reduction. Additionally, these results offer a promising platform to study nonreciprocal SAW devices.

RF Power Performance of Sc(Al,Ga)N/GaN HEMTs at Ka-Band

Abstract: We report the RF power results of Sc(Al,Ga)N/GaN high electron mobility transistors (HEMTs). We show dc, small-signal RF and load-pull performance at 30 GHz with two barrier alloys—a ternary of ScAlN and a quaternary of ScAlGaN. The active layers are grown by molecular beam epitaxy on a GaN-on-SiC template. The Sc(Al,Ga)N HEMTs with 120 nm gate length achieve transconductance >700 mS/mm and >70 GHz cutoff frequency. The quaternary ScAlGaN sample shows reduced current collapse during pulsed I-V and load-pull characterization. The ScAlGaN HEMT delivers 5.77 W/mm output power ( ${V}_{D}= {20}$ V) and 47% power-added efficiency ( ${V}_{D}= {15}$ V) when tuned for maximum power and efficiency, respectively.

Computational search for magnetic and non-magnetic 2D topological materials using unified spin–orbit spillage screening

Abstract: Two-dimensional topological materials (2D TMs) have a variety of properties that make them attractive for applications including spintronics and quantum computation. However, there are only a few such experimentally known materials. To help discover new 2D TMs, we develop a unified and computationally inexpensive approach to identify magnetic and non-magnetic 2D TMs, including gapped and semi-metallic topological classifications, in a high-throughput way using density functional theory-based spin–orbit spillage, Wannier-interpolation, and related techniques. We first compute the spin–orbit spillage for the ~1000 2D materials in the JARVIS-DFT dataset, resulting in 122 materials with high-spillage values. Then, we use Wannier-interpolation to carry-out Z2, Chern-number, anomalous Hall conductivity, Curie temperature, and edge state calculations to further support the predictions. We identify various topologically non-trivial classes such as quantum spin-Hall insulators, quantum anomalous-Hall insulators, and semimetals. For a few predicted materials, we run G0W0+SOC and DFT+U calculations. We find that as we introduce many-body effects, only a few materials retain non-trivial band-topology, suggesting the importance of high-level density functional theory (DFT) methods in predicting 2D topological materials. However, as an initial step, the automated spillage screening and Wannier-approach provide useful predictions for finding new topological materials and to narrow down candidates for experimental synthesis and characterization.

Giant nonreciprocity of surface acoustic waves enabled by the magnetoelastic interaction.

Abstract: Nonreciprocity, the defining characteristic of isolators, circulators, and a wealth of other applications in radio/microwave communications technologies, is generally difficult to achieve as most physical systems incorporate symmetries that prevent the effect. In particular, acoustic waves are an important medium for information transport, but they are inherently symmetric in time. In this work, we report giant nonreciprocity in the transmission of surface acoustic waves (SAWs) on lithium niobate substrate coated with ferromagnet/insulator/ferromagnet (FeGaB/Al2O3/FeGaB) multilayer structure. We exploit this structure with a unique asymmetric band diagram and expand on magnetoelastic coupling theory to show how the magnetic bands couple with acoustic waves only in a single direction. We measure 48.4-dB (power ratio of 1:69,200) isolation that outperforms current state-of-the-art microwave isolator devices in a previously unidentified acoustic wave system that facilitates unprecedented size, weight, and power reduction. In addition, these results offer a promising platform to study nonreciprocal SAW devices.

Inverse design of broadband highly reflective metasurfaces using neural networks

Abstract: Metamaterials exhibit optical properties not observed in traditional materials. Such behavior emerges from the interaction of light with precisely engineered subwavelength features built from different constituent materials. Recent research into the design and fabrication of metamaterial-based devices has established a foundation for the next generation of functional materials. Of particular interest is the all-dielectric metasurface, a two-dimensional metamaterial exploiting shape-dependent resonant features while avoiding losses through the use of dielectric building blocks. However, even this simple metamaterial class has a nearly infinite number of possible configurations; researchers now require new methods to efficiently explore these types of design spaces. In this work, we employ rigorous coupled wave analysis to calculate reflection and transmission spectra associated with a class of open-cylinder all-dielectric metasurface. By altering the geometric parameters of open-cylinder metasurfaces, we generate a sparse training data set and construct artificial neural networks capable of relating metasurface geometries to reflection and transmission spectra. Here, we successfully demonstrate that pseudo autodecoder neural networks can suggest device geometries based on a requested optical performance---inverting the design process for this metasurface class. As an example, we query for and discover a particular open-cylinder metasurface displaying a reflection band $R\ensuremath{\ge}99%$ centered at ${\ensuremath{\lambda}}_{0}=1550\phantom{\rule{0.16em}{0ex}}\mathrm{nm}$ that is much broader $\mathrm{\ensuremath{\Delta}}\ensuremath{\lambda}=450\phantom{\rule{0.16em}{0ex}}\mathrm{nm}$ than anything reported for optical metasurfaces. We then analyze the modal interplay in the open-cylinder metasurface to better understand the underlying physics driving the broadband behavior. Ultimately, we conclude that neural networks are ideally suited for generally approaching these types of complex inverse design problems.

Shape-Programmed Fabrication and Actuation of Magnetically Active Micropost Arrays.

Abstract: Micro- and nanotextured surfaces with reconfigurable textures can enable advancements in the control of wetting and heat transfer, directed assembly of complex materials, and reconfigurable optics, among many applications. However, reliable and programmable directional shape in large scale is significant for prescribed applications. Herein, we demonstrate the self-directed fabrication and actuation of large-area elastomer micropillar arrays, using magnetic fields to both program a shape-directed actuation response and rapidly and reversibly actuate the arrays. Specifically, alignment of magnetic microparticles during casting of micropost arrays with hemicylindrical shapes imparts a deterministic anisotropy that can be exploited to achieve the prescribed, large-deformation bending or twisting of the pillars. The actuation coincides with the finite element method, and we demonstrate reversible, noncontact magnetic actuation of arrays of tens of thousands of pillars over hundreds of cycles, with the bending and twisting angles of up to 72 and 61°, respectively. Moreover, we demonstrate the use of the surfaces to control anisotropic liquid spreading and show that the capillary self-assembly of actuated micropost arrays enables highly complex architectures to be fabricated. The present technique could be scaled to indefinite areas using cost-effective materials and casting techniques, and the principle of shape-directed pillar actuation can be applied to other active material systems.