Nanolattices: An Emerging Class of Mechanical Metamaterials

Micrometer-scale poly(ethylene glycol) with enhanced mechanical performance

Strong and lightweight materials are highly desired. Here we report the emergence of a compressive strength exceeding 2 GPa in a directly printed poly(ethylene glycol) micropillar. This strong and highly crosslinked micropillar is not brittle, instead, it behaves like rubber under compression. Experimental results show that the micropillar sustains a strain approaching 70%, absorbs energy up to 310 MJ/m3, and displays an almost 100% recovery after cyclic loading. Simple micro-lattices (e.g., honeycombs) of poly(ethylene glycol) also display high strength at low structural densities. By combining a series of control experiments, computational simulations and in situ characterization, we find that the key to achieving such mechanical performance lies in the fabrication of a highly homogeneous structure with suppressed defect formation. Our discovery unveils a generalizable approach for achieving a performance leap in polymeric materials and provides a complementary approach to enhance the mechanical performance of low-density latticed structures.

Exploiting multiscale dynamic toughening in multicomponent alloy metamaterials for extreme impact mitigation

Mechanical metamaterials can unlock extreme properties by leveraging lightweight structural design principles and unique deformation mechanisms. However, research has predominantly focused on their quasi-static characteristics, leaving their behavior under extreme dynamic conditions, especially at length scales relevant to practical applications largely unexplored. Here, we present a strategy to achieve extreme impact mitigation at the macroscale by combining shell-based microarchitecture with an additively manufactured medium-entropy alloy (MEA) featuring low stacking fault energy (SFE). Notably, the shell-based architecture amplifies the effective dynamic stress within the metamaterial compared to truss-based morphologies, leading to the earlier activation of multiscale toughening mechanisms in the alloy. The low SFE of the MEA enables the evolution of a diverse array of defect types, thereby prolonging strain hardening behavior across seven orders of magnitude in strain rate. These fundamental insights could establish the groundwork for developing scalable, lightweight, impact-resistant metamaterials for structural and defense applications.

Ideal energy-absorbing metamaterials based on self-locking bistable structures

Energy-absorbing materials with high absorption capacity and self-locking mechanisms are ideal candidates for impact protection. Despite great demands, the current designs either have limited energy absorption capacity or lack self-locking capabilities. To address such limits, we propose a novel type of energy-absorbing metamaterial with both a rectangular force-displacement curve for efficient energy absorption and a steady-state transition capability for locking. By combining the curved beam customized through topology optimization with a snap-fit structure, the ideal energy-absorbing structure is achieved. The deliberately engineered locking mechanism, activated after energy absorption, endows the structure with high programmability and the capability for flexible adjustment. Experimental characterization through additive manufacturing confirms that the error between the force-displacement curve of the designed structure and the target is less than 8.55%, and the energy absorption capacity is improved by 75% compared to the unoptimized bistable structure. The locking of the steady state is accomplished sequentially, which ensures the precision and reliability of the design and provides a basis for application in energy absorption systems. Moreover, the metamaterial also exhibits exceptional impact resistance and protective properties, as confirmed through experimental testing. This study rigorously integrates complex nonlinear mechanical behaviors, paving a new way for the development of highly controllable and optimized energy absorption systems.

Scalable Fabrication of Thick Opals through Drop-Casting Concentrated Suspensions with In-Solution Ordering

Self-assembled materials, studied for optical, mechanical, and fluidic applications, have not yet been widely adopted due to slow manufacturing times. We demonstrate a drop-casting process that provides a rapid approach to fabricate large and thick opals from 40 to 55% w/v solutions of charged polystyrene particles. The high concentration allows for rapid drying, leading to fast assembly times, and the charged particles repel in solution and partially order prior to evaporation. Cryo-FIB SEM images of frozen solutions combined with inverse opals fabricated from still-wet templates visualize the particle ordering prior to assembly. This method produces well-ordered opals with areas of 6.25-100 cm2 and thickness of 100-150 μm, which take 0.5-1.25 h to assemble. In addition, the procedure enables continuous fabrication using a doctor blade to spread the material across the substrate. We demonstrate feasible and scalable opal and inverse opal fabrication.

Lightweight, Strong and Stiff Lattice Structures Inspired by Solid Solution Strengthening

In engineering design, introducing lattice structures offers a cost-effective method for reducing weight while enhancing load-bearing efficiency, compared to merely enhancing the material strength of a solid component. Among the various lattice structure configurations developed thus far, the strength and stiffness of these structures remain significantly below their theoretical limits. This study demonstrates that the theoretical limits of strength and stiffness in lattice structures can be achieved by mimicking the solid solution strengthening mechanism in materials science. This innovative structure achieves the highest load-bearing efficiency to date and is applicable to lattice structures of any geometric configuration. The introduction of the sosoloid structure, a lattice structure with struts reinforced along the loading direction, increases the theoretical limits of lattice strength and stiffness by 20% and 27.5%, respectively, compared to traditional uniform lattice structures. The most effective enhancement is observed when sosoloid structures exhibit the highest material utilization rate and optimal spatial layout. These findings offer a general approach to achieving high load-bearing structures and have broad application prospects in lightweight and high-strength structures, such as human bone design and energy absorption.

Double-network-inspired mechanical metamaterials

Mechanical metamaterials can achieve high stiffness and strength at low densities, but often at the expense of low ductility and stretchability-a persistent trade-off in materials. In contrast, double-network hydrogels feature interpenetrating compliant and stiff polymer networks, and exhibit unprecedented combinations of high stiffness and stretchability, resulting in exceptional toughness. Here we present double-network-inspired metamaterials by integrating monolithic truss (stiff) and woven (compliant) components into a metamaterial architecture, which achieves a tenfold increase in stiffness and stretchability compared to its pure counterparts. Nonlinear computational mechanics models elucidate that enhanced energy dissipation in these double-network-inspired metamaterials stems from increased frictional dissipation due to entanglements between networks. Through introduction of internal defects, which typically degrade mechanical properties, we demonstrate a threefold increase in energy dissipation for these metamaterials via failure delocalization. This work opens avenues for developing metamaterials in a high-compliance regime inspired by polymer network topologies.

Characterization and Inverse Design of Stochastic Mechanical Metamaterials Using Neural Operators

Machine learning (ML) is emerging as a transformative tool for the design of mechanical metamaterials, offering properties that far surpass those achievable through lab-based trial-and-error methods. However, a major challenge in current inverse design strategies is their reliance on extensive computational and/or experimental datasets, which becomes particularly problematic for designing micro-scale stochastic architected materials that exhibit nonlinear mechanical behaviors. Here, a comprehensive end-to-end scientific ML framework, leveraging deep neural operators (including DeepONet and its variants) is introduced, to directly learn the relationship between the complete microstructure and mechanical response of architected metamaterials from sparse but high-quality in situ experimental data. Various neural operators and standard neural networks are systematically compared to identify the model that offers better interpretability and accuracy. The approach facilitates the efficient inverse design of structures tailored to specific nonlinear mechanical behaviors. Results obtained from stochastic spinodal microstructures, printed using two-photon lithography, reveal that the prediction error for mechanical responses is within a range of 5 - 10%. This work underscores that by employing neural operators with advanced nano- and micro-mechanical experiments, the design of complex micro-architected materials with desired properties becomes feasible, even in scenarios constrained by data scarcity. This work marks a significant advancement in the field of materials-by-design, potentially heralding a new era in the discovery and development of next-generation metamaterials with unparalleled mechanical characteristics derived directly from experimental insights.

Bioinspired Nanoscale 3D Printing of Calcium Phosphates Using Bone Prenucleation Clusters

Calcium phosphates (CaPs) are ubiquitous in biological structures, such as vertebrate bones and teeth, and have been widely used in biomedical applications. However, fabricating CaPs at the nanoscale in 3D has remained a significant challenge, particularly due to limitations in current nanofabrication techniques, such as two-photon polymerization (2pp), which are not applicable for creating CaP nanostructures. In this study, a novel approach is presented to 3D print CaP structures with unprecedented resolution of ≈300 nm precision, achieving a level of detail three orders of magnitude finer than any existing additive manufacturing techniques for CaPs. This advancement is achieved by leveraging bioinspired chemistry, utilizing bone prenucleation nanoclusters (PNCs, average size of 5 nm), within a photosensitive resin. These nanoclusters form a highly transparent photoresist, overcoming the light-scattering typically associated with larger calcium phosphate-based nanoparticles. This method not only allows for nanopatterning of CaPs on diverse substrates, but also enables the precise control of microstructure down to the level of submicron grains. The method paves the way for the developing of bioinspired metamaterials, lightweight damage-tolerant materials, cell-modulating interfaces, and precision-engineered coatings.

Enabling three-dimensional architected materials across length scales and timescales

Architected materials provide a pathway to defy the limitations of monolithic materials through their engineered microstructures or geometries, allowing them to exhibit unique and extreme properties. Thus far, most studies on architected materials have been limited to fabricating periodic structures in small tessellations and investigating them under mostly quasi-static conditions, but explorations of more complex architecture designs and their properties across length scales and timescales will be essential to fully uncover the potential of this materials system. In this Perspective, we summarize state-of-the-art approaches to realizing multiscale architected materials and highlight existing knowledge gaps and opportunities in their design, fabrication and characterization. We also propose a roadmap to accelerate the discovery of architected materials with programmable properties via the synergistic combination of experimental and computational efforts. Finally, we identify research opportunities and open questions in the development of next-generation architected materials, intelligent devices and integrated systems that can bridge the gap between the conception and implementation of these materials in real-world engineering applications.

Ultrahigh Specific Strength by Bayesian Optimization of Carbon Nanolattices

Nanoarchitected materials are at the frontier of metamaterial design and have set the benchmark for mechanical performance in several contemporary applications. However, traditional nanoarchitected designs with conventional topologies exhibit poor stress distributions and induce premature nodal failure. Here, using multi-objective Bayesian optimization and two-photon polymerization, optimized carbon nanolattices with an exceptional specific strength of 2.03 MPa m3 kg-1 at low densities <215 kg m-3 are created. Generative design optimization provides experimental improvements in strength and Young's modulus by as much as 118% and 68%, respectively, at equivalent densities with entirely different lattice failure responses. Additionally, the reduction of nanolattice strut diameters to 300 nm produces a unique high-strength carbon with a pyrolysis-induced atomic gradient of 94% sp2 aromatic carbon and low oxygen impurities. Using multi-focus multi-photon polymerization, a millimeter-scalable metamaterial consisting of 18.75 million lattice cells with nanometer dimensions is demonstrated. Combining Bayesian optimized designs and nanoarchitected pyrolyzed carbon, the optimal nanostructures exhibit the strength of carbon steel at the density of Styrofoam offering unparalleled capabilities in light-weighting, fuel reduction, and contemporary design applications.

A metamaterial scaffold beyond modulus limits: enhanced osteogenesis and angiogenesis of critical bone defects

Metallic scaffolds have shown promise in regenerating critical bone defects. However, limitations persist in achieving a modulus below 100 MPa due to insufficient strength. Consequently, the osteogenic impact of lower modulus and greater bone tissue strain ( > 1%) remains unclear. Here, we introduce a metamaterial scaffold that decouples strength and modulus through two-stage deformation. The scaffold facilitates an effective modulus of only 13 MPa, ensuring adaptability during bone regeneration. Followed by a stiff stage, it provides the necessary strength for load-bearing requirements. In vivo, the scaffold induces > 2% callus strain, upregulating calcium channels and HIF-1α to enhance osteogenesis and angiogenesis. 4-week histomorphology reveals a 44% and 498% increase in new bone fraction versus classic scaffolds with 500 MPa and 13 MPa modulus, respectively. This design transcends traditional modulus-matching paradigms, prioritizing bone tissue strain requirements. Its tunable mechanical properties also present promising implications for advancing osteogenesis mechanisms and addressing clinical challenges.

Characteristics of Polybenzoxazine Aerogels as Thermal Insulation and Flame-Retardant Materials

Polybenzoxazine-based aerogels are a unique class of materials that combine the desirable properties of aerogels-such as low density, high porosity, and excellent thermal insulation-with the outstanding characteristics of polybenzoxazines-such as high thermal stability, low water absorption, and superior mechanical strength. Polybenzoxazines are a type of thermosetting polymer derived from benzoxazine monomers. Several features of polybenzoxazines can be retained within the aerogels synthesized through them. The excellent thermal resistance of polybenzoxazines, which can withstand temperatures above 200-300 °C, makes their aerogel able to withstand extreme thermal environments. The inherent structure of polybenzoxazines, rich in aromatic rings and nitrogen and oxygen atoms, imparts flame-retardant property. Their highly crosslinked structure provides excellent resistance to solvents, acids, and bases. Above all, through their molecular design flexibility, their physical, mechanical, and thermal properties can be tubed to suit specific applications. In this review, the synthesis of polybenzoxazine aerogels, including various steps such as monomer synthesis, gel formation, solvent exchange and drying, and finally curing are discussed in detail. The application of these aerogels in thermal insulation and flame-retardant materials is given importance. The challenges and future prospects of further enhancing their properties and expanding their utility are also summarized.

Bio-Informed Porous Mineral-Based Composites

Certain biominerals, such as sea sponges and echinoderm skeletons, display a fascinating combination of mechanical properties and adaptability due to the well-defined structures spanning various length scales. These materials often possess high density normalized mechanical properties because they contain well-defined pores. The density-normalized mechanical properties of synthetic minerals are often inferior because the pores are stochastically distributed, resulting in an inhomogeneous stress distribution. The mechanical properties of synthetic materials are limited by the degree of structural and compositional control currently available fabrication methods offer. In the first part of this review, examples of structural elements nature uses to impart exceptional density normalized Young's moduli to its porous biominerals are showcased. The second part highlights recent advancements in the fabrication of bio-informed mineral-based composites possessing pores with diameters that span a wide range of length scales. The influence of the processing of mineral-based composites on their structures and mechanical properties is summarized. Thereby, it is aimed at encouraging further research directed to the sustainable, energy-efficient fabrication of synthetic lightweight yet stiff mineral-based composites.

Spatio-Selective Reconfiguration of Mechanical Metamaterials Through the Use of Dynamic Covalent Chemistries

Mechanical metamaterials achieve unprecedented mechanical properties through their periodically interconnected unit cell structure. However, their geometrical design and resulting mechanical properties are typically fixed during fabrication. Despite efforts to implement covalent adaptable networks (CANs) into metamaterials for permanent shape reconfigurability, emphasis is given to global rather than local shape reconfiguration. Furthermore, the change of effective material properties like Poisson's ratio remains to be explored. In this work, a non-isocyanate polyurethane elastomeric CAN, which can be thermally reconfigured, is introduced into a metamaterial architecture. Structural reconfiguration allows for the local and global reprogramming of the Poisson's ratio with change of unit cell angle from 60° to 90° for the auxetic and 120° to 90° for the honeycomb metamaterial. The respective Poisson's ratio changes from -1.4 up to -0.4 for the auxetic and from +0.7 to +0.2 for the honeycomb metamaterial. Carbon nanotubes are deposited on the metamaterials to enable global and spatial electrothermal heating for on-demand reshaping with a heterogeneous Poisson's ratio ranging from -2 to ≈0 for a single auxetic or +0.6 to ≈0 for a single honeycomb metamaterial. Finite element simulations reveal how permanent geometrical reconfiguration results from locally and globally relaxed heated patterns.

Strain learning in protein-based mechanical metamaterials

Mechanical deformation of polymer networks causes molecular-level motion and bond scission that ultimately lead to material failure. Mitigating this strain-induced loss in mechanical integrity is a significant challenge, especially in the development of active and shape-memory materials. We report the additive manufacturing of mechanical metamaterials made with a protein-based polymer that undergo a unique stiffening and strengthening behavior after shape recovery cycles. We utilize a bovine serum albumin-based polymer and show that cyclic tension and recovery experiments on the neat resin lead to a ~60% increase in the strength and stiffness of the material. This is attributed to the release of stored length in the protein mechanophores during plastic deformation that is preserved after the recovery cycle, thereby leading to a "strain learning" behavior. We perform compression experiments on three-dimensionally printed lattice metamaterials made from this protein-based polymer and find that, in certain lattices, the strain learning effect is not only preserved but amplified, causing up to a 2.5× increase in the stiffness of the recovered metamaterial. These protein-polymer strain learning metamaterials offer a unique platform for materials that can autonomously remodel after being deformed, mimicking the remodeling processes that occur in natural materials.

Imperfection-Enabled Strengthening of Ultra-Lightweight Lattice Materials

Lattice materials are an emerging family of advanced engineering materials with unique advantages for lightweight applications. However, the mechanical behaviors of lattice materials at ultra-low relative densities are still not well understood, and this severely limits their lightweighting potential. Here, a high-precision micro-laser powder bed fusion technique is dveloped that enables the fabrication of metallic lattices with a relative density range much wider than existing studies. This technique allows to confirm that cubic lattices in compression undergo a yielding-to-buckling failure mode transition at low relative densities, and this transition fundamentally changes the usual strength ranking from plate > shell > truss at high relative densities to shell > plate > truss or shell > truss > plate at low relative densities. More importantly, it is shown that increasing bending energy ratio in the lattice through imperfections such as slightly-corrugated geometries can significantly enhance the stability and strength of lattice materials at ultra-low relative densities. This counterintuitive result suggests a new way for designing ultra-lightweight lattice materials at ultra-low relative densities.

Parameter-Independent Deformation Behaviour of Diagonally Reinforced Doubly Re-Entrant Honeycomb

In this study, a novel unit cell design is proposed, which eliminates the buckling tendency of the auxetic honeycomb. The novel unit cell design is a more balanced, diagonally reinforced doubly re-entrant auxetic honeycomb structure (x-reinforced auxetic honeycomb for short). We investigated and compared this novel unit cell design against a wide parameter range. Compression tests were carried out on specimens 3D-printed with a special, unique, flexible but tough resin mixture. The results showed that the additional, centrally pronounced reinforcements resulted in increased deformation stability; parameter-independent, non-buckling deformation behaviour is achieved; however, the novel structure is no longer auxetic. Mechanical properties, such as compression resistance and energy absorption capability, also increased significantly-An almost four times increase can be observed. In contrast to the deformation behaviour (which became predictable and constant), the mechanical properties can be precisely adjusted for the desired application. This novel structure was also investigated in a highly accurate, validated finite element environment, which showed that critical stress values are formed in well-supported regions, meaning that critical failure is unlikely. Our novel lattice unit cell design elevated the auxetic honeycomb to the realm of modern, high performance and widely applicable lattice structures.

Nanoporous amorphous carbon nanopillars with lightweight, ultrahigh strength, large fracture strain, and high damping capability

Simultaneous achievement of lightweight, ultrahigh strength, large fracture strain, and high damping capability is challenging because some of these mechanical properties are mutually exclusive. Here, we utilize self-assembled polymeric carbon precursor materials in combination with scalable nano-imprinting lithography to produce nanoporous carbon nanopillars. Remarkably, nanoporosity induced via sacrificial template significantly reduces the mass density of amorphous carbon to 0.66 ~ 0.82 g cm-3 while the yield and fracture strengths of nanoporous carbon nanopillars are higher than those of most engineering materials with the similar mass density. Moreover, these nanopillars display both elastic and plastic behavior with large fracture strain. A reversible part of the sp2-to-sp3 transition produces large elastic strain and a high loss factor (up to 0.033) comparable to Ni-Ti shape memory alloys. The irreversible part of the sp2-to-sp3 transition enables plastic deformation, leading to a large fracture strain of up to 35%. These findings are substantiated using simulation studies. None of the existing structural materials exhibit a comparable combination of mass density, strength, deformability, and damping capability. Hence, the results of this study illustrate the potential of both dense and nanoporous amorphous carbon materials as superior structural nanomaterials.

Exploring Stimuli-Responsive Natural Processes for the Fabrication of High-Performance Materials

Climate change and environmental pollution have underscored the urgency for more sustainable alternatives in synthetic polymer production. Nature's repertoire of biopolymers with excellent multifaceted properties alongside biodegradability could inspire next-generation innovative green polymer fabrication routes. Stimuli-induced processing, driven by changes in environmental factors, such as pH, ionic strength, and mechanical forces, plays a crucial role in natural polymeric self-assembly process. This perspective aims to close the gap in understanding biopolymer formation by highlighting the essential role of stimuli triggers in facilitating the bottom-up fabrication, allowing for the formation of intricate hierarchical structures. In particular, this perspective will delve into the stimuli-responsive processing of high-performance biopolymers produced by mussels, caddisflies, velvet worms, sharks, whelks, and squids, which are known for their robust mechanical properties, durability, and wet adhesion capabilities. Finally, we provide an overview of current advancements and challenges in understanding stimuli-induced natural formation pathways and their translation to biomimetic materials.

Well-Ordered Bicontinuous Nanohybrids from a Bottom-Up Approach for Enhanced Strength and Toughness

Biomimicking natural structures to create structural materials with superior mechanical performance is an area of extensive attention, yet achieving both high strength and toughness remains challenging. This study presents a novel bottom-up approach using self-assembled block copolymer templating to synthesize bicontinuous nanohybrids composed of well-ordered nanonetwork hydroxyapatite (HAp) embedded in poly(methyl methacrylate) (PMMA). This structuring transforms intrinsically brittle HAp into a ductile material, while hybridization with PMMA alleviates the strength reduction caused by porosity. The resultant bicontinuous PMMA/HAp nanohybrids, reinforced at the interface, exhibit high strength and toughness due to the combined effects of topology, nanosize, and hybridization. This work suggests a conceptual framework for fabricating flexible thin films with mechanical properties significantly surpassing those of traditional composites and top-down approaches.

Text-to-Microstructure Generation Using Generative Deep Learning

Designing novel materials is greatly dependent on understanding the design principles, physical mechanisms, and modeling methods of material microstructures, requiring experienced designers with expertise and several rounds of trial and error. Although recent advances in deep generative networks have enabled the inverse design of material microstructures, most studies involve property-conditional generation and focus on a specific type of structure, resulting in limited generation diversity and poor human-computer interaction. In this study, a pioneering text-to-microstructure deep generative network (Txt2Microstruct-Net) is proposed that enables the generation of 3D material microstructures directly from text prompts without additional optimization procedures. The Txt2Microstruct-Net model is trained on a large microstructure-caption paired dataset that is extensible using the algorithms provided. Moreover, the model is sufficiently flexible to generate different geometric representations, such as voxels and point clouds. The model's performance is also demonstrated in the inverse design of material microstructures and metamaterials. It has promising potential for interactive microstructure design when associated with large language models and could be a user-friendly tool for material design and discovery.

Superior fracture resistance and topology-induced intrinsic toughening mechanism in 3D shell-based lattice metamaterials

Lattice metamaterials have demonstrated remarkable mechanical properties at low densities. As these architected materials advance toward real-world applications, their tolerance for damage and defects becomes a limiting factor. However, a thorough understanding of the fracture resistance and fracture mechanisms in lattice metamaterials, particularly for the emerging shell-based lattices, has remained elusive. Here, using a combination of in situ fracture experiments and finite element simulations, we show that shell-based lattice metamaterials with Schwarz P minimal surface topology exhibit superior fracture resistance compared to conventional octet truss lattices, with average improvements in initiation toughness up to 150%. This superiority is attributed to the unique shell-based architecture that enables more efficient load transfer and higher energy dissipation through material damage, structural plasticity, and material plasticity. Our study reveals a topology-induced intrinsic toughening mechanism in shell-based lattices and highlights these architectures as a superior design route for creating lightweight and high-performance mechanical metamaterials.

Tailoring Stress-Strain Curves of Flexible Snapping Mechanical Metamaterial for On-Demand Mechanical Responses via Data-Driven Inverse Design

By incorporating soft materials into the architecture, flexible mechanical metamaterials enable promising applications, e.g., energy modulation, and shape morphing, with a well-controllable mechanical response, but suffer from spatial and temporal programmability towards higher-level mechanical intelligence. One feasible solution is to introduce snapping structures and then tune their responses by accurately tailoring the stress-strain curves. However, owing to the strongly coupled nonlinearity of structural deformation and material constitutive model, it is difficult to deduce their stress-strain curves using conventional ways. Here, a machine learning pipeline is trained with the finite element analysis data that considers those strongly coupled nonlinearities to accurately tailor the stress-strain curves of snapping metamaterialfor on-demand mechanical response with an accuracy of 97.41%, conforming well to experiment. Utilizing the established approach, the energy absorption efficiency of the snapping-metamaterial-based device can be tuned within the accessible range to realize different rebound heights of a falling ball, and soft actuators can be spatially and temporally programmed to achieve synchronous and sequential actuation with a single energy input. Purely relying on structure designs, the accurately tailored metamaterials increase the devices' tunability/programmability. Such an approach can potentially extend to similar nonlinear scenarios towards predictable or intelligent mechanical responses.

Programmable responsive metamaterials for mechanical computing and robotics

Unconventional computing based on mechanical metamaterials has been of growing interest, including how such metamaterials might process information via autonomous interactions with their environment. Here we describe recent efforts to combine responsive materials with nonlinear mechanical metamaterials to achieve stimuli-responsive mechanical logic and computation. We also describe some key challenges and opportunities in the design and construction of these devices, including the lack of comprehensive computational tools, and the challenges associated with patterning multi-material mechanisms.

Nondestructive Imaging of Manufacturing Defects in Microarchitected Materials

Defects in microarchitected materials exhibit a dual nature, capable of both unlocking innovative functionalities and degrading their performance. Specifically, while intentional defects are strategically introduced to customize and enhance mechanical responses, inadvertent defects stemming from manufacturing errors can disrupt the symmetries and intricate interactions within these materials. In this study, we demonstrate a nondestructive optical imaging technique that can precisely locate defects inside microscale metamaterials, as well as provide detailed insights on the specific type of defect.

Biomineral-Based Composite Materials in Regenerative Medicine

Regenerative medicine aims to address substantial defects by amplifying the body's natural regenerative abilities and preserving the health of tissues and organs. To achieve these goals, materials that can provide the spatial and biological support for cell proliferation and differentiation, as well as the micro-environment essential for the intended tissue, are needed. Scaffolds such as polymers and metallic materials provide three-dimensional structures for cells to attach to and grow in defects. These materials have limitations in terms of mechanical properties or biocompatibility. In contrast, biominerals are formed by living organisms through biomineralization, which also includes minerals created by replicating this process. Incorporating biominerals into conventional materials allows for enhanced strength, durability, and biocompatibility. Specifically, biominerals can improve the bond between the implant and tissue by mimicking the micro-environment. This enhances cell differentiation and tissue regeneration. Furthermore, biomineral composites have wound healing and antimicrobial properties, which can aid in wound repair. Additionally, biominerals can be engineered as drug carriers, which can efficiently deliver drugs to their intended targets, minimizing side effects and increasing therapeutic efficacy. This article examines the role of biominerals and their composite materials in regenerative medicine applications and discusses their properties, synthesis methods, and potential uses.

Mechanical Performance of Copper-Nanocluster-Polymer Nanolattices

A type of copper-nanocluster-polymer composites is reported and showcased that their 3D nanolattices exhibit a superior combination of high strength, toughness, deformability, resilience, and damage-tolerance. Notably, the strength and toughness of ultralight copper-nanocluster-polymer nanolattices in some cases surpass current best performers, including alumina, nickel, and other ceramic or metallic lattices at low densities. Additionally, copper-nanocluster-polymer nanolattices are super-resilient, crack-resistant, and one-step printed under ambient condition which can be easily integrated into sophisticated microsystems as highly effective internal protectors. The findings suggest that, unlike traditional nanocomposites, the laser-induced interface and the high fraction of ultrasmall Cu15 nanoclusters as crosslinking junctions contribute to the marked nonlinear elasticity of copper-nanocluster-polymer network, which synergizes with the lattice-topology effect and culminates in the exceptional mechanical performance.

Mechanically Robust Self-Organized Crack-Free Nanocellular Graphene with Outstanding Electrochemical Properties in Sodium Ion Battery

Crack-free nanocellular graphenes are attractive materials with extraordinary mechanical and electrochemical properties, but their homogeneous synthesis on the centimeter scale is challenging. Here, a strong nanocellular graphene film achieved by the self-organization of carbon atoms using liquid metal dealloying and employing a defect-free amorphous precursor is reported. This study demonstrates that a Bi melt strongly catalyzes the self-structuring of graphene layers at low processing temperatures. The robust nanoarchitectured graphene displays a high-genus seamless framework and exhibits remarkable tensile strength (34.8 MPa) and high electrical conductivity (1.6 × 104 S m-1). This unique material has excellent potential for flexible and high-rate sodium-ion battery applications.

Realization of all two-dimensional Bravais lattices with metasurface-based interference lithography

Proximity-field nanopatterning (PnP) have been used recently as a rapid, cost-effective, and large-scale fabrication method utilizing volumetric interference patterns generated by conformal phase masks. Despite the effectiveness of PnP processes, their design diversity has not been thoroughly explored. Here, we demonstrate that the possibility of generating any two-dimensional lattice with diverse motifs. By controlling the amplitude, phase, and polarization of each diffraction beam, we can implement all two-dimensional Bravais lattices in three-dimensional space. The results may provide diverse applications that require three-dimensional nanostructures from optical materials and structural materials to energy storage or conversion materials.

Microarchitected Compliant Scaffolds of Pyrolytic Carbon for 3D Muscle Cell Growth

The integration of additive manufacturing technologies with the pyrolysis of polymeric precursors enables the design-controlled fabrication of architected 3D pyrolytic carbon (PyC) structures with complex architectural details. Despite great promise, their use in cellular interaction remains unexplored. This study pioneers the utilization of microarchitected 3D PyC structures as biocompatible scaffolds for the colonization of muscle cells in a 3D environment. PyC scaffolds are fabricated using micro-stereolithography, followed by pyrolysis. Furthermore, an innovative design strategy using revolute joints is employed to obtain novel, compliant structures of architected PyC. The pyrolysis process results in a pyrolysis temperature- and design-geometry-dependent shrinkage of up to 73%, enabling the geometrical features of microarchitected compatible with skeletal muscle cells. The stiffness of architected PyC varies with the pyrolysis temperature, with the highest value of 29.57 ± 0.78 GPa for 900 °C. The PyC scaffolds exhibit excellent biocompatibility and yield 3D cell colonization while culturing skeletal muscle C2C12 cells. They further induce good actin fiber alignment along the compliant PyC construction. However, no conclusive myogenic differentiation is observed here. Nevertheless, these results are highly promising for architected PyC scaffolds as multifunctional tissue implants and encourage more investigations in employing compliant architected PyC structures for high-performance tissue engineering applications.

Decoupling particle-impact dissipation mechanisms in 3D architected materials

Ultralight architected materials enabled by advanced manufacturing processes have achieved density-normalized strength and stiffness properties that are inaccessible to bulk materials. However, the majority of this work has focused on static loading and elastic-wave propagation. Fundamental understanding of the mechanical behavior of architected materials under large-deformation dynamic conditions remains limited, due to the complexity of mechanical responses and shortcomings of characterization methods. Here, we present a microscale suspended-plate impact testing framework for three-dimensional micro-architected materials, where supersonic microparticles to velocities of up to 850 m/s are accelerated against a substrate-decoupled architected material to quantify its energy dissipation characteristics. Using ultra-high-speed imaging, we perform in situ quantification of the impact energetics on two types of architected materials as well as their constituent nonarchitected monolithic polymer, indicating a 47% or greater increase in mass-normalized energy dissipation under a given impact condition through use of architecture. Post-mortem characterization, supported by a series of quasi-static experiments and high-fidelity simulations, shed light on two coupled mechanisms of energy dissipation: material compaction and particle-induced fracture. Together, experiments and simulations indicate that architecture-specific resistance to compaction and fracture can explain a difference in dynamic impact response across architectures. We complement our experimental and numerical efforts with dimensional analysis which provides a predictive framework for kinetic-energy absorption as a function of material parameters and impact conditions. We envision that enhanced understanding of energy dissipation mechanisms in architected materials will serve to define design considerations toward the creation of lightweight impact-mitigating materials for protective applications.

Spatially Programmable Architected Materials Inspired by the Metallurgical Phase Engineering

Programmable architected materials with the capabilities of precisely storing predefined mechanical behaviors and adaptive deformation responses upon external stimulations are desirable to help increase the performance and the organic integration of materials with surrounding environments. Here, a new approach inspired by the physical metallurgical principles is proposed to allow the materials designers to not only enhance the global strength but also precisely tune mechanical properties (such as strength, modulus, and plastic deformation) locally in architected materials to create a new class of intelligent mechanical metamaterials. Such programmable materials not only have high strength and plastic deformation stability but also the ability to regulate the local deformation states and spatially control the internal propagation of deformation. This innovative approach also provides new and effective ways to enhance the adaptivity of the materials thanks to responsive strengths that not only make the materials increasingly stronger but also allow threshold-based adaptive responses to external loading.

Pneumatic elastostatics of multi-functional inflatable lattices: realization of extreme specific stiffness with active modulation and deployability

As a consequence of intense investigation on possible topologies of periodic lattices, the limit of specific elastic moduli that can be achieved solely through unit cell-level geometries in artificially engineered lattice-based materials has reached a point of saturation. There exists a robust rationale to involve more elementary-level mechanics for pushing such boundaries further to develop extreme lightweight multi-functional materials with adequate stiffness. We propose a novel class of inflatable lattice materials where the global-level stiffness can be derived based on a fundamentally different mechanics compared with conventional lattices having beam-like solid members, leading to extreme specific stiffness due to the presence of air in most of the lattice volume. Furthermore, such inflatable lattices would add multi-functionality in terms of on-demand performances such as compact storing, portability and deployment along with active stiffness modulation as a function of air pressure. We have developed an efficient unit cell-based analytical approach therein to characterize the effective elastic properties including the effect of non-rigid joints. The proposed inflatable lattices would open new frontiers in engineered materials and structures that will find critical applications in a range of technologically demanding industries such as aircraft structures, defence, soft robotics, space technologies, biomedical and various other mechanical systems.

Wafer-Scale Fabrication of 2D Nanostructures via Thermomechanical Nanomolding

With shrinking dimensions in integrated circuits, sensors, and functional devices, there is a pressing need to develop nanofabrication techniques with simultaneous control of morphology, microstructure, and material composition over wafer length scales. Current techniques are largely unable to meet all these conditions, suffering from poor control of morphology and defect structure or requiring extensive optimization or post-processing to achieve desired nanostructures. Recently, thermomechanical nanomolding (TMNM) has been shown to yield single-crystalline, high aspect ratio nanowires of metals, alloys, and intermetallics over wafer-scale distances. Here, TMNM is extended for wafer-scale fabrication of 2D nanostructures. Using In, Al, and Cu, nanomold nanoribbons with widths < 50 nm, depths ≈0.5-1 µm and lengths ≈7 mm into Si trenches at conditions compatible is successfully with back end of line processing . Through SEM cross-section imaging and 4D-STEM grain orientation maps, it is shown that the grain size of the bulk feedstock is transferred to the nanomolded structures up to and including single crystal Cu. Based on the retained microstructures of molded 2D Cu, the deformation mechanism during molding for 2D TMNM is discussed.

Deep Learning in Mechanical Metamaterials: From Prediction and Generation to Inverse Design

Mechanical metamaterials are meticulously designed structures with exceptional mechanical properties determined by their microstructures and constituent materials. Tailoring their material and geometric distribution unlocks the potential to achieve unprecedented bulk properties and functions. However, current mechanical metamaterial design considerably relies on experienced designers' inspiration through trial and error, while investigating their mechanical properties and responses entails time-consuming mechanical testing or computationally expensive simulations. Nevertheless, recent advancements in deep learning have revolutionized the design process of mechanical metamaterials, enabling property prediction and geometry generation without prior knowledge. Furthermore, deep generative models can transform conventional forward design into inverse design. Many recent studies on the implementation of deep learning in mechanical metamaterials are highly specialized, and their pros and cons may not be immediately evident. This critical review provides a comprehensive overview of the capabilities of deep learning in property prediction, geometry generation, and inverse design of mechanical metamaterials. Additionally, this review highlights the potential of leveraging deep learning to create universally applicable datasets, intelligently designed metamaterials, and material intelligence. This article is expected to be valuable not only to researchers working on mechanical metamaterials but also those in the field of materials informatics.

Machine learning-enabled constrained multi-objective design of architected materials

Architected materials that consist of multiple subelements arranged in particular orders can demonstrate a much broader range of properties than their constituent materials. However, the rational design of these materials generally relies on experts' prior knowledge and requires painstaking effort. Here, we present a data-efficient method for the high-dimensional multi-property optimization of 3D-printed architected materials utilizing a machine learning (ML) cycle consisting of the finite element method (FEM) and 3D neural networks. Specifically, we apply our method to orthopedic implant design. Compared to uniform designs, our experience-free method designs microscale heterogeneous architectures with a biocompatible elastic modulus and higher strength. Furthermore, inspired by the knowledge learned from the neural networks, we develop machine-human synergy, adapting the ML-designed architecture to fix a macroscale, irregularly shaped animal bone defect. Such adaptation exhibits 20% higher experimental load-bearing capacity than the uniform design. Thus, our method provides a data-efficient paradigm for the fast and intelligent design of architected materials with tailored mechanical, physical, and chemical properties.

Ultrastrong colloidal crystal metamaterials engineered with DNA

Lattice-based constructs, often made by additive manufacturing, are attractive for many applications. Typically, such constructs are made from microscale or larger elements; however, smaller nanoscale components can lead to more unusual properties, including greater strength, lighter weight, and unprecedented resiliencies. Here, solid and hollow nanoparticles (nanoframes and nanocages; frame size: ~15 nanometers) were assembled into colloidal crystals using DNA, and their mechanical strengths were studied. Nanosolid, nanocage, and nanoframe lattices with identical crystal symmetries exhibit markedly different specific stiffnesses and strengths. Unexpectedly, the nanoframe lattice is approximately six times stronger than the nanosolid lattice. Nanomechanical experiments, electron microscopy, and finite element analysis show that this property results from the buckling, densification, and size-dependent strain hardening of nanoframe lattices. Last, these unusual open architectures show that lattices with structural elements as small as 15 nanometers can retain a high degree of strength, and as such, they represent target components for making and exploring a variety of miniaturized devices.

Mechanical metamaterials and beyond

Mechanical metamaterials enable the creation of structural materials with unprecedented mechanical properties. However, thus far, research on mechanical metamaterials has focused on passive mechanical metamaterials and the tunability of their mechanical properties. Deep integration of multifunctionality, sensing, electrical actuation, information processing, and advancing data-driven designs are grand challenges in the mechanical metamaterials community that could lead to truly intelligent mechanical metamaterials. In this perspective, we provide an overview of mechanical metamaterials within and beyond their classical mechanical functionalities. We discuss various aspects of data-driven approaches for inverse design and optimization of multifunctional mechanical metamaterials. Our aim is to provide new roadmaps for design and discovery of next-generation active and responsive mechanical metamaterials that can interact with the surrounding environment and adapt to various conditions while inheriting all outstanding mechanical features of classical mechanical metamaterials. Next, we deliberate the emerging mechanical metamaterials with specific functionalities to design informative and scientific intelligent devices. We highlight open challenges ahead of mechanical metamaterial systems at the component and integration levels and their transition into the domain of application beyond their mechanical capabilities.

Deformation and Durability of Soft Three-Dimensional-Printed Polycarbonate Urethane Porous Membranes for Potential Use in Pelvic Organ Prolapse

Pelvic organ prolapse (POP) is the herniation of the pelvic organs into the vaginal space, resulting in the feeling of a bulge and organ dysfunction. Treatment of POP often involves repositioning the organs using a polypropylene mesh, which has recently been found to have relatively high rates of complications. Complications have been shown to be related to stiffness mismatches between the vagina and polypropylene, and unstable knit patterns resulting in mesh deformations with mechanical loading. To overcome these limitations, we have three-dimensional (3D)-printed a porous, monofilament membrane composed of relatively soft polycarbonate-urethane (PCU) with a stable geometry. PCU was chosen for its tunable properties as it is comprised of both hard and soft segments. The bulk mechanical properties of PCU were first characterized by testing dogbone samples, demonstrating the dependence of PCU mechanical properties on its measurement environment and the effect of print pathing. The pore dimensions and load-relative elongation response of the 3D-printed PCU membranes under monotonic tensile loading were then characterized. Finally, a fatigue study was performed on the 3D-printed membrane to evaluate durability, showing a similar fatigue resistance with a commercial synthetic mesh and hence its potential as a replacement.

Auxeticity as a Mechanobiological Tool to Create Meta-Biomaterials

Mechanical and morphological design parameters, such as stiffness or porosity, play important roles in creating orthopedic implants and bone substitutes. However, we have only a limited understanding of how the microarchitecture of porous scaffolds contributes to bone regeneration. Meta-biomaterials are increasingly used to precisely engineer the internal geometry of porous scaffolds and independently tailor their mechanical properties (e.g., stiffness and Poisson's ratio). This is motivated by the rare or unprecedented properties of meta-biomaterials, such as negative Poisson's ratios (i.e., auxeticity). It is, however, not clear how these unusual properties can modulate the interactions of meta-biomaterials with living cells and whether they can facilitate bone tissue engineering under static and dynamic cell culture and mechanical loading conditions. Here, we review the recent studies investigating the effects of the Poisson's ratio on the performance of meta-biomaterials with an emphasis on the relevant mechanobiological aspects. We also highlight the state-of-the-art additive manufacturing techniques employed to create meta-biomaterials, particularly at the micrometer scale. Finally, we provide future perspectives, particularly for the design of the next generation of meta-biomaterials featuring dynamic properties (e.g., those made through 4D printing).

Multifunctional Hierarchical Metamaterial for Thermal Insulation and Electromagnetic Interference Shielding at Elevated Temperatures

The custom design of lightweight cellular materials is widely concerned due to effectively improved mechanical properties and functional applications. However, the strength attenuation and brittleness behavior hinder honeycomb structure design for the ceramic monolith. Herein, the ceramic matrix composite metamaterial (CCM) with a negative Poisson's ratio and high specific strength, exhibiting superelasticity, stability, and high compressive strength, is customized by combining centripetal freeze-casting and hierarchical structures. CCM maintains a negative Poisson's ratio response under compression with the lowest value reaching -0.16, and the relationship between CCM's specific modulus and density is E ∼ ρ^1.3, which indicates the mechanical metamaterial characteristic of high specific strength. In addition to the extraordinary mechanical performance endowed by hierarchical structures, the CCM exhibits excellent thermal insulation and electromagnetic interference shielding properties, in which the thermal conductivity is 30.62 mW·m^-1·K^-1 and the electromagnetic interference (EMI) shielding efficiency (SE) reaches 40 dB at room temperature. The specific EMI shielding efficiency divided by thickness (SSE/t) of CCM can reach 9416 dB·cm²·g^-1 at 700 °C due to its stability at elevated temperatures, which is 100 times higher than that of traditional ceramic matrix composites. Moreover, the designed hierarchical structure and metamaterial properties provide a potential scheme to implement cellular materials with collaborative optimization in structure and function.

A sinterless, low-temperature route to 3D print nanoscale optical-grade glass

Three-dimensional (3D) printing of silica glass is dominated by techniques that rely on traditional particle sintering. At the nanoscale, this limits their adoption within microsystem technology, which prevents technological breakthroughs. We introduce the sinterless, two-photon polymerization 3D printing of free-form fused silica nanostructures from a polyhedral oligomeric silsesquioxane (POSS) resin. Contrary to particle-loaded sacrificial binders, our POSS resin itself constitutes a continuous silicon-oxygen molecular network that forms transparent fused silica at only 650°C. This temperature is 500°C lower than the sintering temperatures for fusing discrete silica particles to a continuum, which brings silica 3D printing below the melting points of essential microsystem materials. Simultaneously, we achieve a fourfold resolution enhancement, which enables visible light nanophotonics. By demonstrating excellent optical quality, mechanical resilience, ease of processing, and coverable size scale, our material sets a benchmark for micro- and nano-3D printing of inorganic solids.

Tunable Mechanical Response of Self-Assembled Nanoparticle Superlattices

Self-assembled nanoparticle superlattices (NPSLs) are an emergent class of self-architected nanocomposite materials that possess promising properties arising from precise nanoparticle ordering. Their multiple coupled properties make them desirable as functional components in devices where mechanical robustness is critical. However, questions remain about NPSL mechanical properties and how shaping them affects their mechanical response. Here, we perform in situ nanomechanical experiments that evidence up to an 11-fold increase in stiffness (∼1.49 to 16.9 GPa) and a 5-fold increase in strength (∼88 to 426 MPa) because of surface stiffening/strengthening from shaping these nanomaterials via focused-ion-beam milling. To predict the mechanical properties of shaped NPSLs, we present discrete element method (DEM) simulations and an analytical core-shell model that capture the FIB-induced stiffening response. This work presents a route for tunable mechanical responses of self-architected NPSLs and provides two frameworks to predict their mechanical response and guide the design of future NPSL-containing devices.

Elastically Isotropic Truss-Plate-Hybrid Hierarchical Microlattices with Enhanced Modulus and Strength

Bioinspired hierarchical design principles have been employed to create advanced architected materials. Here, a new type of truss-plate-hybrid two-level hierarchical architecture is created, referred to as the ISO-COP hierarchical lattice (isotropic truss at the first level and cubic+octet plate at the second level), in which truss-based unit cells are arranged according to the topology of the plate-based unit cell. Finite element analyses reveal that the ISO-COP hierarchical lattice outperforms the best existing octet-truss hierarchical lattices based on fractal geometries in achieving elastic isotropy and enhanced moduli. According to the designed architecture, ISO-COP and several other comparison hierarchical microlattices are fabricated via projection microstereolithography. In situ compression tests demonstrate that the fabricated ISO-COP microlattices exhibit elastic isotropy and enhanced moduli, as predicted from finite element simulations, and superior strength compared with existing fractal octet-truss hierarchical lattices. Theoretical models are further developed to predict the dependence of modulus and failure modes on two design parameters of the hierarchical lattices, with results in good agreement with those from experiments. This study relates mechanical properties of ISO-COP hierarchical lattices to their architectures at each level of hierarchy and exemplifies a route to harnessing hierarchical design principles to create architected materials with desired mechanical properties.

3D Printed Graphene-Based Metamaterials: Guesting Multi-Functionality in One Gain

Advanced functional materials with fascinating properties and extended structural design have greatly broadened their applications. Metamaterials, exhibiting unprecedented physical properties (mechanical, electromagnetic, acoustic, etc.), are considered frontiers of physics, material science, and engineering. With the emerging 3D printing technology, the manufacturing of metamaterials becomes much more convenient. Graphene, due to its superior properties such as large surface area, superior electrical/thermal conductivity, and outstanding mechanical properties, shows promising applications to add multi-functionality into existing metamaterials for various applications. In this review, the aim is to outline the latest developments and applications of 3D printed graphene-based metamaterials. The structure design of different types of metamaterials and the fabrication strategies for 3D printed graphene-based materials are first reviewed. Then the representative explorations of 3D printed graphene-based metamaterials and multi-functionality that can be introduced with such a combination are further discussed. Subsequently, challenges and opportunities are provided, seeking to point out future directions of 3D printed graphene-based metamaterials.

3D-Printed Micro/Nano-Scaled Mechanical Metamaterials: Fundamentals, Technologies, Progress, Applications, and Challenges

Micro/nano-scaled mechanical metamaterials have attracted extensive attention in various fields attributed to their superior properties benefiting from their rationally designed micro/nano-structures. As one of the most advanced technologies in the 21st century, additive manufacturing (3D printing) opens an easier and faster path for fabricating micro/nano-scaled mechanical metamaterials with complex structures. Here, the size effect of metamaterials at micro/nano scales is introduced first. Then, the additive manufacturing technologies to fabricate mechanical metamaterials at micro/nano scales are introduced. The latest research progress on micro/nano-scaled mechanical metamaterials is also reviewed according to the type of materials. In addition, the structural and functional applications of micro/nano-scaled mechanical metamaterials are further summarized. Finally, the challenges, including advanced 3D printing technologies, novel material development, and innovative structural design, for micro/nano-scaled mechanical metamaterials are discussed, and future perspectives are provided. The review aims to provide insight into the research and development of 3D-printed micro/nano-scaled mechanical metamaterials.

Mechanical Properties of Internally Hierarchical Multiphase Lattices Inspired by Precipitation Strengthening Mechanisms

In metal metallurgy, precipitation strengthening is widely used to increase material strength by utilizing the impediment effect of the second-phase particles on dislocation movements. Inspired by this mechanism, in this paper, novel multiphase heterogeneous lattice materials are developed with enhanced mechanical properties utilizing a similar hindering effect of second-phase lattice cells on the shear band propagation. For this purpose, biphase and triphase lattice samples are fabricated using high-speed multi jet fusion (MJF) and digital light processing (DLP) additive manufacturing techniques, and a parametric study is carried out to investigate their mechanical properties. Different from the conventional random distribution, the second-phase and third-phase cells in this work are continuously distributed along the regular pattern of a larger-scale lattice to form internal hierarchical lattice structures. The results show that the triphase lattices possess balanced mechanical properties. Interestingly, this indicates that introducing a relatively weak phase also has the potential to improve the stiffness and plateau stress, which is distinct from the common mixed rule. This work is aimed at providing new references for the heterogeneous lattice design with outstanding mechanical properties through material microstructure inspiration.

Scaling Law for Impact Resistance of Amorphous Alloys Connecting Atomistic Molecular Dynamics with Macroscale Experiments

Establishing scaling laws for amorphous alloys is of critical importance for describing their mechanical behavior at different size scales. In this paper, taking Ni₂Ta amorphous metallic alloy as a prototype materials system, we derive the scaling law of impact resistance for amorphous alloys. We use laser-induced supersonic micro-ballistic impact experiments to measure for the first time the size-dependent impact response of amorphous alloys. We also report the results of molecular dynamics (MD) simulations for the same system but at much smaller scales. Comparing these results, we determined a law for scaling both length and time scales based on dimensional analysis. It connects the time and length scales of the experimental results on the impact resistance of amorphous alloys to that of the MD simulations, providing a method for bridging the gap in comparing the dynamic behavior of amorphous alloys at various scales and a guideline for the fabrication of new amorphous alloy materials with extraordinary impact resistance.

Mechanical metamaterials made of freestanding quasi-BCC nanolattices of gold and copper with ultra-high energy absorption capacity

Nanolattices exhibit attractive mechanical properties such as high strength, high specific strength, and high energy absorption. However, at present, such materials cannot achieve effective fusion of the above properties and scalable production, which hinders their applications in energy conversion and other fields. Herein, we report gold and copper quasi-body centered cubic (quasi-BCC) nanolattices with the diameter of the nanobeams as small as 34 nm. We show that the compressive yield strengths of quasi-BCC nanolattices even exceed those of their bulk counterparts, despite their relative densities below 0.5. Simultaneously, these quasi-BCC nanolattices exhibit ultrahigh energy absorption capacities, i.e., 100 ± 6 MJ m^-3 for gold quasi-BCC nanolattice and 110 ± 10 MJ m^-3 for copper quasi-BCC nanolattice. Finite element simulations and theoretical calculations reveal that the deformation of quasi-BCC nanolattice is dominated by nanobeam bending. And the anomalous energy absorption capacities substantially stem from the synergy of the naturally high mechanical strength and plasticity of metals, the size reduction-induced mechanical enhancement, and the quasi-BCC nanolattice architecture. Since the sample size can be scaled up to macroscale at high efficiency and affordable cost, the quasi-BCC nanolattices with ultrahigh energy absorption capacity reported in this work may find great potentials in heat transfer, electric conduction, catalysis applications.