Tuning the Properties of Multi-Stable Structures Post-Fabrication Via the Two-Way Shape Memory Polymer Effect.

Multi-stable elements are commonly employed to design reconfigurable and adaptive structures, because they enable large and reversible shape changes in response to changing loads, while simultaneously allowing self-locking capabilities. However, existing multi-stable structures have properties that depend on their initial design and cannot be tailored post-fabrication. Here, a novel design approach is presented that combines multi-stable structures with two-way shape memory polymers. By leveraging both the one-way and two-way shape memory effect under bi-axial strain conditions, the structures can re-program their 3D shape, bear loads, and self-actuate. Results demonstrate that the structures' shape and stiffness can be tuned post-fabrication at the user's need and the multi-stability can be suppressed or activated on command. The control of multi-stability prevents undesired snapping of the structures and enables higher load-bearing capability, compared to conventional multi-stable systems. The proposed approach offers the possibility to augment the functionality of existing multi-stable concepts, showing potential for the realization of highly adaptable mechanical structures that can reversibly switch between being mono and multi-stable and that can undergo shape changes in response to a change in temperature.

From Basic Principles of Protein-Polysaccharide Association to the Rational Design of Thermally Sensitive Materials.

Biology resolves design requirements toward functional materials by creating nanostructured composites, where individual components are combined to maximize the macroscale material performance. A major challenge in utilizing such design principles is the trade-off between the preservation of individual component properties and emerging composite functionalities. Here, polysaccharide pectin and silk fibroin were investigated in their composite form with pectin as a thermal-responsive ion conductor and fibroin with exceptional mechanical strength. We show that segregative phase separation occurs upon mixing, and within a limited compositional range, domains ∼50 nm in size are formed and distributed homogeneously so that decent matrix collective properties are established. The composite is characterized by slight conformational changes in the silk domains, sequestering the hydrogen-bonded ß-sheets as well as the emergence of randomized pectin orientations. However, most dominant in the composite's properties is the introduction of dense domain interfaces, leading to increased hydration, surface hydrophilicity, and increased strain of the composite material. Using controlled surface charging in X-ray photoelectron spectroscopy, we further demonstrate Ca ions (Ca2+) diffusion in the pectin domains, with which the fingerprints of interactions at domain interfaces are revealed. Both the thermal response and the electrical conductance were found to be strongly dependent on the degree of composite hydration. Our results provide a fundamental understanding of the role of interfacial interactions and their potential applications in the design of material properties, polysaccharide-protein composites in particular.

AI-aided geometric design of anti-infection catheters.

Bacteria can swim upstream in a narrow tube and pose a clinical threat of urinary tract infection to patients implanted with catheters. Coatings and structured surfaces have been proposed to repel bacteria, but no such approach thoroughly addresses the contamination problem in catheters. Here, on the basis of the physical mechanism of upstream swimming, we propose a novel geometric design, optimized by an artificial intelligence model. Using Escherichia coli, we demonstrate the anti-infection mechanism in microfluidic experiments and evaluate the effectiveness of the design in three-dimensionally printed prototype catheters under clinical flow rates. Our catheter design shows that one to two orders of magnitude improved suppression of bacterial contamination at the upstream end, potentially prolonging the in-dwelling time for catheter use and reducing the overall risk of catheter-associated urinary tract infection.

Control of Mechanical and Fracture Properties in Two-Phase Materials Reinforced by Continuous, Irregular Networks.

Composites with high strength and high fracture resistance are desirable for structural and protective applications. Most composites, however, suffer from poor damage tolerance and are prone to unpredictable fractures. Understanding the behavior of materials with an irregular reinforcement phase offers fundamental guidelines for tailoring their performance. Here, the fracture nucleation and propagation in two phase composites, as a function of the topology of their irregular microstructures is studied. A stochastic algorithm is used to design the polymeric reinforcing network, achieving independent control of topology and geometry of the microstructure. By tuning the local connectivity of isodense tiles and their assembly into larger structures, the mechanical and fracture properties of the architected composites are tailored at the local and global scale. Finally, combining different reinforcing networks into a spatially determined meso-scale assembly, it is demonstrated how the spatial propagation of fracture in architected composite materials can be designed and controlled a priori.

Microscale acoustic metamaterials as conformal sonotransparent skull prostheses.

Functional ultrasound imaging enables sensitive, high-resolution imaging of neural activity in freely behaving animals and human patients. However, the skull acts as an aberrating and absorbing layer for sound waves, leading to most functional ultrasound experiments being conducted after skull removal. In pre-clinical settings, craniotomies are often covered with a polymethylpentene film, which offers limited longitudinal imaging, due to the film's poor conformability, and limited mechanical protection, due to the film's low stiffness. Here, we introduce a skull replacement consisting of a microstructured, conformal acoustic window based on mechanical metamaterials, designed to offer high stiffness-to-density ratio and sonotransparency. We test the acoustic window in vivo, via terminal and survival experiments on small animals. Long-term biocompatibility and lasting signal sensitivity are demonstrated over a long period of time (> 4 months) by conducting ultrasound imaging in mouse models implanted with the metamaterial skull prosthesis.

Flexible biomimetic block copolymer composite for temperature and long-wave infrared sensing.

Biological compounds often provide clues to advance material designs. Replicating their molecular structure and functional motifs in artificial materials offers a blueprint for unprecedented functionalities. Here, we report a flexible biomimetic thermal sensing (BTS) polymer that is designed to emulate the ion transport dynamics of a plant cell wall component, pectin. Using a simple yet versatile synthetic procedure, we engineer the physicochemical properties of the polymer by inserting elastic fragments in a block copolymer architecture, making it flexible and stretchable. The thermal response of our flexible polymer outperforms current state-of-the-art temperature sensing materials, including vanadium oxide, by up to two orders of magnitude. Thermal sensors fabricated from these composites exhibit a sensitivity that exceeds 10 mK and operate stably between 15° and 55°C, even under repeated mechanical deformations. We demonstrate the use of our flexible BTS polymer in two-dimensional arrays for spatiotemporal temperature mapping and broadband infrared photodetection.

Growth rules for irregular architected materials with programmable properties.

Biomaterials display microstructures that are geometrically irregular and functionally efficient. Understanding the role of irregularity in determining material properties offers a new path to engineer materials with superior functionalities, such as imperfection insensitivity, enhanced impact absorption, and stress redirection. We uncover fundamental, probabilistic structure-property relationships using a growth-inspired program that evokes the formation of stochastic architectures in natural systems. This virtual growth program imposes a set of local rules on a limited number of basic elements. It generates materials that exhibit a large variation in functional properties starting from very limited initial resources, which echoes the diversity of biological systems. We identify basic rules to control mechanical properties by independently varying the microstructure's topology and geometry in a general, graph-based representation of irregular materials.

Epidemic management and control through risk-dependent individual contact interventions.

Testing, contact tracing, and isolation (TTI) is an epidemic management and control approach that is difficult to implement at scale because it relies on manual tracing of contacts. Exposure notification apps have been developed to digitally scale up TTI by harnessing contact data obtained from mobile devices; however, exposure notification apps provide users only with limited binary information when they have been directly exposed to a known infection source. Here we demonstrate a scalable improvement to TTI and exposure notification apps that uses data assimilation (DA) on a contact network. Network DA exploits diverse sources of health data together with the proximity data from mobile devices that exposure notification apps rely upon. It provides users with continuously assessed individual risks of exposure and infection, which can form the basis for targeting individual contact interventions. Simulations of the early COVID-19 epidemic in New York City are used to establish proof-of-concept. In the simulations, network DA identifies up to a factor 2 more infections than contact tracing when both harness the same contact data and diagnostic test data. This remains true even when only a relatively small fraction of the population uses network DA. When a sufficiently large fraction of the population (≳ 75%) uses network DA and complies with individual contact interventions, targeting contact interventions with network DA reduces deaths by up to a factor 4 relative to TTI. Network DA can be implemented by expanding the computational backend of existing exposure notification apps, thus greatly enhancing their capabilities. Implemented at scale, it has the potential to precisely and effectively control future epidemics while minimizing economic disruption.

Biological matrix composites from cultured plant cells.

We present an approach to fabricate biological matrix composites made entirely from cultured plant cells. We utilize the cell's innate ability to synthesize nanofibrillar cell walls, which serve as the composite's fundamental building blocks. Following a controlled compression/dehydration process, the cells arrange into lamellar structures with hierarchical features. We demonstrate that the native cell wall nanofibrils tether adjacent cells together through fibrillar interlocking and intermolecular hydrogen bonding. These interactions facilitate intercellular adhesion and eliminate the need for other binders. Our fabrication process utilizes the entire plant cell, grown in an in vitro culture; requires no harsh chemical treatments or waste-generating extraction or selection processes; and leads to bulk biocomposites that can be produced in situ and biodegrade in soil. The final mechanical properties are comparable to commodity plastics and can be further modulated by introducing filler particles.

Mechanical cloak via data-driven aperiodic metamaterial design.

SignificanceAn invisibility cloak to conceal objects from an outside observer has long been a subject of interest in metamaterial design. While cloaks have been manufactured for optical, thermal, and electric fields, limited progress has been made for mechanical cloaks. Most existing designs rely on mapping-based methods, which have so far been limited to special base cells and a narrow selection of voids with simple shapes. In this study, we develop a fundamentally different approach by exploiting data-driven designs to offer timely, customized solutions to mechanical cloaking that were previously difficult to obtain. Through simulations and experimental validations, we show that excellent cloaking performance can be achieved for various boundary conditions, shapes of voids, base cells, and even multiple voids.

Cell wall and cytoskeletal contributions in single cell biomechanics of Nicotiana tabacum.

Studies on the mechanics of plant cells usually focus on understanding the effects of turgor pressure and properties of the cell wall (CW). While the functional roles of the underlying cytoskeleton have been studied, the extent to which it contributes to the mechanical properties of cells is not elucidated. Here, we study the contributions of the CW, microtubules (MTs) and actin filaments (AFs), in the mechanical properties of Nicotiana tabacum cells. We use a multiscale biomechanical assay comprised of atomic force microscopy and micro-indentation in solutions that (i) remove MTs and AFs and (ii) alter osmotic pressures in the cells. To compare measurements obtained by the two mechanical tests, we develop two generative statistical models to describe the cell's behaviour using one or both datasets. Our results illustrate that MTs and AFs contribute significantly to cell stiffness and dissipated energy, while confirming the dominant role of turgor pressure.

Structured fabrics with tunable mechanical properties.

Structured fabrics, such as woven sheets or chain mail armours, derive their properties both from the constitutive materials and their geometry1,2. Their design can target desirable characteristics, such as high impact resistance, thermal regulation, or electrical conductivity3-5. Once realized, however, the fabrics' properties are usually fixed. Here we demonstrate structured fabrics with tunable bending modulus, consisting of three-dimensional particles arranged into layered chain mails. The chain mails conform to complex shapes2, but when pressure is exerted at their boundaries, the particles interlock and the chain mails jam. We show that, with small external pressure (about 93 kilopascals), the sheets become more than 25 times stiffer than in their relaxed configuration. This dramatic increase in bending resistance arises because the interlocking particles have high tensile resistance, unlike what is found for loose granular media. We use discrete-element simulations to relate the chain mail's micro-structure to macroscale properties and to interpret experimental measurements. We find that chain mails, consisting of different non-convex granular particles, undergo a jamming phase transition that is described by a characteristic power-law function akin to the behaviour of conventional convex media. Our work provides routes towards lightweight, tunable and adaptive fabrics, with potential applications in wearable exoskeletons, haptic architectures and reconfigurable medical supports.

Robotic surfaces with reversible, spatiotemporal control for shape morphing and object manipulation.

Continuous and controlled shape morphing is essential for soft machines to conform, grasp, and move while interacting safely with their surroundings. Shape morphing can be achieved with two-dimensional (2D) sheets that reconfigure into target 3D geometries, for example, using stimuli-responsive materials. However, most existing solutions lack the ability to reprogram their shape, face limitations on attainable geometries, or have insufficient mechanical stiffness to manipulate objects. Here, we develop a soft, robotic surface that allows for large, reprogrammable, and pliable shape morphing into smooth 3D geometries. The robotic surface consists of a layered design composed of two active networks serving as artificial muscles, one passive network serving as a skeleton, and cover scales serving as an artificial skin. The active network consists of a grid of strips made of heat-responsive liquid crystal elastomers (LCEs) containing stretchable heating coils. The magnitude and speed of contraction of the LCEs can be controlled by varying the input electric currents. The 1D contraction of the LCE strips activates in-plane and out-of-plane deformations; these deformations are both necessary to transform a flat surface into arbitrary 3D geometries. We characterize the fundamental deformation response of the layers and derive a control scheme for actuation. We demonstrate that the robotic surface provides sufficient mechanical stiffness and stability to manipulate other objects. This approach has potential to address the needs of a range of applications beyond shape changes, such as human-robot interactions and reconfigurable electronics.

Photosynthesis-assisted remodeling of three-dimensional printed structures.

The mechanical properties of engineering structures continuously weaken during service life because of material fatigue or degradation. By contrast, living organisms are able to strengthen their mechanical properties by regenerating parts of their structures. For example, plants strengthen their cell structures by transforming photosynthesis-produced glucose into stiff polysaccharides. In this work, we realize hybrid materials that use photosynthesis of embedded chloroplasts to remodel their microstructures. These materials can be used to three-dimensionally (3D)-print functional structures, which are endowed with matrix-strengthening and crack healing when exposed to white light. The mechanism relies on a 3D-printable polymer that allows for an additional cross-linking reaction with photosynthesis-produced glucose in the material bulk or on the interface. The remodeling behavior can be suspended by freezing chloroplasts, regulated by mechanical preloads, and reversed by environmental cues. This work opens the door for the design of hybrid synthetic-living materials, for applications such as smart composites, lightweight structures, and soft robotics.

Structure and Biomechanics during Xylem Vessel Transdifferentiation in Arabidopsis thaliana.

Individual plant cells are the building blocks for all plantae and artificially constructed plant biomaterials, like biocomposites. Secondary cell walls (SCWs) are a key component for mediating mechanical strength and stiffness in both living vascular plants and biocomposite materials. In this paper, we study the structure and biomechanics of cultured plant cells during the cellular developmental stages associated with SCW formation. We use a model culture system that induces transdifferentiation of Arabidopsis thaliana cells to xylem vessel elements, upon treatment with dexamethasone (DEX). We group the transdifferentiation process into three distinct stages, based on morphological observations of the cell walls. The first stage includes cells with only a primary cell wall (PCW), the second covers cells that have formed a SCW, and the third stage includes cells with a ruptured tonoplast and partially or fully degraded PCW. We adopt a multi-scale approach to study the mechanical properties of cells in these three stages. We perform large-scale indentations with a micro-compression system in three different osmotic conditions. Atomic force microscopy (AFM) nanoscale indentations in water allow us to isolate the cell wall response. We propose a spring-based model to deconvolve the competing stiffness contributions from turgor pressure, PCW, SCW and cytoplasm in the stiffness of differentiating cells. Prior to triggering differentiation, cells in hypotonic pressure conditions are significantly stiffer than cells in isotonic or hypertonic conditions, highlighting the dominant role of turgor pressure. Plasmolyzed cells with a SCW reach similar levels of stiffness as cells with maximum turgor pressure. The stiffness of the PCW in all of these conditions is lower than the stiffness of the fully-formed SCW. Our results provide the first experimental characterization of the mechanics of SCW formation at single cell level.

Programming temporal morphing of self-actuated shells.

Advances in shape-morphing materials, such as hydrogels, shape-memory polymers and light-responsive polymers have enabled prescribing self-directed deformations of initially flat geometries. However, most proposed solutions evolve towards a target geometry without considering time-dependent actuation paths. To achieve more complex geometries and avoid self-collisions, it is critical to encode a spatial and temporal shape evolution within the initially flat shell. Recent realizations of time-dependent morphing are limited to the actuation of few, discrete hinges and cannot form doubly curved surfaces. Here, we demonstrate a method for encoding temporal shape evolution in architected shells that assume complex shapes and doubly curved geometries. The shells are non-periodic tessellations of pre-stressed contractile unit cells that soften in water at rates prescribed locally by mesostructure geometry. The ensuing midplane contraction is coupled to the formation of encoded curvatures. We propose an inverse design tool based on a data-driven model for unit cells' temporal responses.

Metamaterials with engineered failure load and stiffness.

Architected materials or metamaterials have proved to be a very effective way of making materials with unusual mechanical properties. For example, by designing the mesoscale geometry of architected materials, it is possible to obtain extremely high stiffness-to-weight ratio or unusual Poisson's ratio. However, much of this work has focused on designing properties like stiffness and density, and much remains unknown about the critical load to failure. This is the focus of the current work. We show that the addition of local internal prestress in selected regions of architected materials enables the design of materials where the critical load to failure can be optimized independently from the density and/or quasistatic stiffness. We propose a method to optimize the specific load to failure and specific stiffness using sensitivity analysis and derive the maximum bounds on the attainable properties. We demonstrate the method in a 2D triangular lattice and a 3D octahedral truss, showing excellent agreement between experimental and theoretical results. The method can be used to design materials with predetermined fracture load, failure location, and fracture paths.

Characterization of Vertically Aligned Carbon Nanotube Forests Grown on Stainless Steel Surfaces.

Vertically aligned carbon nanotube (CNT) forests are a particularly interesting class of nanomaterials, because they combine multifunctional properties, such as high energy absorption, compressive strength, recoverability, and super-hydrophobicity with light weight. These characteristics make them suitable for application as coating, protective layers, and antifouling substrates for metallic pipelines and blades. Direct growth of CNT forests on metals offers the possibility of transferring the tunable CNT functionalities directly onto the desired substrates. Here, we focus on characterizing the structure and mechanical properties, as well as wettability and adhesion, of CNT forests grown on different types of stainless steel. We investigate the correlations between composition and morphology of the steel substrates with the micro-structure of the CNTs and reveal how the latter ultimately controls the mechanical and wetting properties of the CNT forest. Additionally, we study the influence of substrate morphology on the adhesion of CNTs to their substrate. We highlight that the same structure-property relationships govern the mechanical performance of CNT forests grown on steels and on Si.

Untethered soft robotic matter with passive control of shape morphing and propulsion.

There is growing interest in creating untethered soft robotic matter that can repeatedly shape-morph and self-propel in response to external stimuli. Toward this goal, we printed soft robotic matter composed of liquid crystal elastomer (LCE) bilayers with orthogonal director alignment and different nematic-to-isotropic transition temperatures (T NI) to form active hinges that interconnect polymeric tiles. When heated above their respective actuation temperatures, the printed LCE hinges exhibit a large, reversible bending response. Their actuation response is programmed by varying their chemistry and printed architecture. Through an integrated design and additive manufacturing approach, we created passively controlled, untethered soft robotic matter that adopts task-specific configurations on demand, including a self-twisting origami polyhedron that exhibits three stable configurations and a "rollbot" that assembles into a pentagonal prism and self-rolls in programmed responses to thermal stimuli.

Experimental realization of on-chip topological nanoelectromechanical metamaterials.

Guiding waves through a stable physical channel is essential for reliable information transport. However, energy transport in high-frequency mechanical systems, such as in signal-processing applications1, is particularly sensitive to defects and sharp turns because of back-scattering and losses2. Topological phenomena in condensed matter systems have shown immunity to defects and unidirectional energy propagation3. Topological mechanical metamaterials translate these properties into classical systems for efficient phononic energy transport. Acoustic and mechanical topological metamaterials have so far been realized only in large-scale systems, such as arrays of pendulums4, gyroscopic lattices5,6, structured plates7,8 and arrays of rods, cans and other structures acting as acoustic scatterers9-12. To fulfil their potential in device applications, mechanical topological systems need to be scaled to the on-chip level for high-frequency transport13-15. Here we report the experimental realization of topological nanoelectromechanical metamaterials, consisting of two-dimensional arrays of free-standing silicon nitride nanomembranes that operate at high frequencies (10-20 megahertz). We experimentally demonstrate the presence of edge states, and characterize their localization and Dirac-cone-like frequency dispersion. Our topological waveguides are also robust to waveguide distortions and pseudospin-dependent transport. The on-chip integrated acoustic components realized here could be used in unidirectional waveguides and compact delay lines for high-frequency signal-processing applications.