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Results for “Mechanical Metamaterials”

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At least 19 records

Synthetically non-Hermitian nonlinear wave-like behavior in a topological mechanical metamaterial

Topological mechanical metamaterials have enabled new ways to control stress and deformation propagation. Exemplified by Maxwell lattices, they have been studied extensively using a linearized formalism. Herein, we study a two-dimensional topological Maxwell lattice by exploring its large deformation quasi-static response using geometric numerical simulations and experiments. We observe spatial nonlinear wave-like phenomena such as harmonic generation, localized domain switching, amplification-enhanced frequency conversion, and solitary waves. We further map our linearized, homogenized system to a non-Hermitian, nonreciprocal, one-dimensional wave equation, revealing an equivalence between the deformation fields of two-dimensional topological Maxwell lattices and nonlinear dynamical phenomena in one-dimensional active systems. Our study opens a regime for topological mechanical metamaterials and expands their application potential in areas including adaptive and smart materials and mechanical logic, wherein concepts from nonlinear dynamics may be used to create intricate, tailored spatial deformation and stress fields greatly transcending conventional elasticity.

36 MATERIALS SCIENCE↗

Dependence of the kinetic energy absorption capacity of bistable mechanical metamaterials on impactor mass and velocity

Using an alternative mechanism to dissipation or scattering, bistable structures and mechanical metamaterials have shown promise for mitigating the detrimental effects of impact by reversibly locking energy into strained material. Herein, we extend prior works on impact absorption via bistable metamaterials to computationally explore the dependence of kinetic energy transmission on the velocity and mass of the impactor, with strain rates exceeding 10 2 s –1 . We observe a large dependence on both impactor parameters, ranging from significantly better to worse performance than a comparative linear material. We then correlate the variability in performance to solitary wave formation in the system and give analytical estimates of idealized energy absorption capacity under dynamic loading. In addition, we find a significant dependence on damping accompanied by a qualitative difference in solitary wave propagation within the system. The complex dynamics revealed in this study offer potential future guidance for the application of bistable metamaterials to applications including human and engineered system shock and impact protection devices.

42 ENGINEERING↗

High compressive energy absorption and shape recovery behavior of additively manufactured textile-inspired cylindrical braided metamaterials

Mechanical metamaterials (MMs) are engineered structures with unique mechanical properties that arise from their unique spatial arrangement or lattice-like structure. The most commonly designed MMs such as honeycomb and re-entrant auxetics are prone to failure at the sharp corners and weak joints due to the increased stress concentration under deformation. To mitigate this challenge, braided MM structures involving intertwining threads of nylon—forming curved unit cells—have been studied. These textile-inspired cylindrical braided metamaterials (CBMMs) with contrasting unit cells, namely diamond and regular CBMMs, were fabricated by 3D printing. The layer-by-layer deposited structure built by fused filament fabrication delivered an assembly of overlapped threads that are fused at the contact point. To understand deformation behavior of these MMs, finite element models were developed for various load scenarios including quasi-static compression, cyclic and creep loads at room temperature. Stress distribution, deformation mechanisms, and failure modes were analyzed and validated by experiments to analyze the geometries and associated performance. The diamond CBMMs showed stress softening at 30 % compressive strain, withstanding a load of ∼440 N, whereas the regular CBMMs at 50 % strain experienced ∼250 N. The diamond CBMMs delivered higher creep resistance under sustained load and better energy absorption under cyclic loading than the regular CBMMs. The latter, however, exhibited 94 % shape recovery in contrast to 88 % recovery in former prototype during their first cyclic load. In conclusion, this study helps design mechanical lightweight devices that endure significant sustained load and exhibit enhanced energy absorption and shape recovery characteristics in cyclic loading.

Creep↗

Emergent disorder and mechanical memory in periodic metamaterials

Ordered mechanical systems typically have one or only a few stable rest configurations, and hence are not considered useful for encoding memory. Multistable and history-dependent responses usually emerge from quenched disorder, for example in amorphous solids or crumpled sheets. In contrast, due to geometric frustration, periodic magnetic systems can create their own disorder and espouse an extensive manifold of quasi-degenerate configurations. Inspired by the topological structure of frustrated artificial spin ices, we introduce an approach to design ordered, periodic mechanical metamaterials that exhibit an extensive set of spatially disordered states. While our design exploits the correspondence between frustration in magnetism and incompatibility in meta-mechanics, our mechanical systems encompass continuous degrees of freedom, and thus generalize their magnetic counterparts. We show how such systems exhibit non-Abelian and history-dependent responses, as their state can depend on the order in which external manipulations were applied. We demonstrate how this richness of the dynamics enables to recognize, from a static measurement of the final state, the sequence of operations that an extended system underwent. Thus, multistability and potential to perform computation emerge from geometric frustration in ordered mechanical lattices that create their own disorder.

36 MATERIALS SCIENCE↗

High-strength, lightweight nano-architected silica

Continuous nanolattices are an emerging class of mechanical metamaterials that are highly attractive due to their superior strength-to-weight ratios, which originate from their spatial architectures and nanoscale-sized elements possessing near-theoretical strength. Rational design of frameworks remains challenging below 50 nm because of limited methods to arrange small elements into complex architectures. Here, we fabricate silica frameworks with ~4- to 20-nm-thick elements using self-assembly and silica templating of DNA origami nanolattices and perform in situ micro-compression testing to examine the mechanical properties. We observe strong effects of lattice dimensions on yield strength (σ $\mathcal{y}$ ) and failure mode. Silica nanolattices are found to exhibit yield strengths higher than those of any known engineering materials with similar mass density. The robust coordination of the nanothin and strong silica elements leads to the combination of lightweight and high-strength framework materials offering an effective strategy for the fabrication of nanoarchitected materials with superior mechanical properties.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Multi-objective automatic discovery of optimized metamaterials for varying velocity impact protection

Mechanical metamaterials have demonstrated exceptional impact performance while remaining lightweight. Impact resistance has traditionally been investigated using quasi-static simulations, often with the assumption that performance will translate to high-velocity impact scenarios. However, critical crash protection parameters—such as peak stress and absorbed energy—are highly sensitive to impact velocity, leading to inconsistent performance under dynamic loading. To address this, we introduce a strain-rate-aware, active deep learning framework that enables multi-objective optimization of impact protection metrics across a wide range of impact velocities. Our framework captures the strain-rate sensitivity of architected lattices by learning to control spatial gradation in cellular metamaterials, resulting in over 200 % enhancement in impact protection relative to state-of-the-art designs such as Voronoi and re-entrant lattices. We demonstrate its practical utility by designing next-generation lattice structures for automotive bumper systems that satisfy multiple, velocity-specific safety criteria—capabilities beyond those of conventional designs. More than just a predictive tool, this framework marks the first step towards enabling adaptable impact-resistant structures across dynamic regimes.

Deep learning↗

FAIR Data and Interpretable AI Framework for Architectured Metamaterials

Our interdisciplinary effort successfully generated FAIR (Findable, Accessible, Interoperable, and Reusable) benchmark datasets for mechanical metamaterials while introducing a novel Artificial Intelligence (AI) framework known as Learning Refined Compositional Rules (LRCR). This framework was specifically designed to bridge the gap across varying computational length scales and extract the underlying physical mechanisms that connect a material's structural geometry to its bulk acoustic properties. Historically, the discovery of such structured materials relied heavily on human intuition or opaque, black-box optimization algorithms that were difficult to generalize. By combining interpretable machine learning techniques with rigorous experimental validation, this project established clear, generalizable design guidelines for tuning wave dispersion and controlling vibrations. Ultimately, the public availability of these structured datasets and algorithms will significantly reduce computational costs and accelerate the design of advanced multi-functional acoustic devices, offering broad societal impacts across fields like aerospace engineering, telecommunications, and biomedical implant design.

36 MATERIALS SCIENCE↗

FAIR Data and Interpretable AI Framework for Architectured Metamaterials (Final Report)

This research program established a transformative framework for the discovery and design of mechanical metamaterials, which are architected structures engineered to control physical phenomena like sound and vibration in ways natural materials cannot. To overcome the traditional reliance on trial-and-error, the project developed an interpretable Artificial Intelligence (AI) framework that moves beyond "black box" models to reveal the specific geometric patterns—such as "unit-cell templates"—that govern a material’s performance. A major breakthrough was the development of a hierarchical design method, which allows a single material to block vibrations across multiple frequency ranges simultaneously by layering patterns at different scales without them interfering with one another. This was further expanded to include irregular, graph-based designs that use spanning tree algorithms to ensure structural connectivity while allowing for customized, direction-dependent properties like stiffness and acoustic impedance. Beyond design, the project addressed the practicalities of real-world production by developing uncertainty quantification techniques that account for manufacturing defects and material variability, reducing the need for expensive physical testing by orders of magnitude. To speed up the discovery process, the team implemented Gaussian Process Regression and other surrogate models that provide accurate performance predictions at a fraction of the traditional computational cost. The AI-generated designs were successfully validated through fabrication of physical samples and wave propagation experiments, confirming their ability to accurately guide or reflect waves as predicted. By contributing these tools and high-quality FAIR benchmark datasets to the wider scientific community, this work provides a scalable foundation for advancing technologies in aerospace vibration control, medical imaging, and noise reduction.

36 MATERIALS SCIENCE↗

Micro-architected material design for mechanical response

Rapid advances in additive manufacturing (AM) have enabled the creation of micro-architected materials—also known as mechanical metamaterials—with unprecedented control over fine-scale geometries and arrangements of multiple material constituents. These “materials” can achieve unique and extraordinary effective mechanical properties through their complex architectures rather than composition alone. A key challenge is to design for these bespoke effective mechanical responses within the constraints of available AM techniques (i.e., given a set of desired effective properties), identify a (often nonunique) micro-architecture and selection of material constituents that achieves them. Two main strategies have emerged. Gradient-based methods use sensitivity analysis to iteratively refine candidate designs, while data-driven methods learn micro-architecture-constituent relationships from existing examples to propose new designs. This article reviews these design approaches for micro-architected materials with tailored mechanical responses that can be fabricated by AM as well as their applications.

Spadaccini, Christopher M [Lawrence Livermore Nati↗

Realizing mechanical frustration at the nanoscale using DNA origami

Structural designs inspired by physical and biological systems have been previously utilized to develop mechanical metamaterials with enhanced properties based on clever geometric arrangement of constituent building blocks. Here, we use the DNA origami method to realize a nanoscale metastructure exhibiting mechanical frustration, a counterpart of the well-known phenomenon of magnetic frustration. By selectively actuating reconfigurable struts, it adopts either frustrated or non-frustrated states, each characterized by distinct free energy profiles. While the non-frustrated state distributes the strain homogeneously, the frustrated mode concentrates it at a specific location. Molecular dynamics simulations reconcile the contrasting behaviors and provide insights into underlying mechanics. We explore the design space further by tailoring responses through structural modifications. Our work combines programmable DNA self-assembly with mechanical design principles to overcome engineering limitations encountered at the macroscale to design dynamic, deformable nanostructures with potential applications in elastic energy storage, nanomechanical computation, and allosteric mechanisms in DNA-based nanomachinery.

DNA nanostructures↗

Multi-Scale Design And Advanced Manufacturing Of Seismic Metamaterials (CRADA Final Report)

As part of the Cyclotron Road program, METAseismic sought to investigate a multi-scale approach, both in terms of manufacturing and design, for seismic metamaterials with applications in the energy sector. Specifically, this project explored the feasibility of using nanofabrication to enable the incorporation of 3D nanostructured components into a mechanical metamaterial. These components were explored to increase the seismic resilience of our infrastructure to earthquakes, with the final aim of providing customized levels of protection for its components. This was envisioned as the base of a multi-scale design approach that consisted of using a multiplicity of metamaterial architectures ranging from the nano- to the meso-scale to address the stringent seismic design objectives of electric-power equipment.

36 MATERIALS SCIENCE↗

Strongly nonlinear wave propagation in elasto-plastic metamaterials: Low-order dynamic modeling

Nonlinear elastic metamaterials are known to support a variety of dynamic phenomena that enhance our capacity to manipulate elastic waves. Since these properties stem from complex, subwavelength geometry, full-scale dynamic simulations are often prohibitively expensive at scales of interest. Prior studies have therefore utilized low-order effective medium models, such as discrete mass-spring lattices, to capture essential properties in the long-wavelength limit. While models of this type have been successfully implemented for a wide variety of nonlinear elastic systems, they have predominantly considered dynamics depending only on the instantaneous kinematics of the lattice, neglecting history-dependent effects, such as wear and plasticity. Here, to address this limitation, the present study develops a lattice-based modeling framework for nonlinear elastic metamaterials undergoing plastic deformation. Due to the history- and rate-dependent nature of plasticity, the framework generally yields a system of differential-algebraic equations whose computational cost is significantly greater than an elastic system of comparable size. We demonstrate the method using several models inspired by classical lattice dynamics and continuum plasticity theory and explore means to obtain empirical plasticity models for general geometries, thereby gaining insight into the influence of microstructural plasticity on effective material performance, which can be used to improve the design of nonlinear mechanical metamaterials.

Dynamic simulation↗

Digital and Gradient Refractive Index Planar Optics by Nanoimprinting Mesoporous Silicon

We report the realization of digital and gradient index flat-optics and planar waveguides using the ‘nanoimprinting refractive index’ (NIRI) technique applied to mesoporous silicon. This technique combines the distinct optical and mechanical metamaterial qualities of mesoporous silicon, including its widely tunable effective refractive index and ability to undergo plastic deformation with a near zero Poisson ratio. Nanoimprinting with premastered and reusable stamps containing analog or digital features enables the continuous or discontinuous patterning of refractive index with high contrast Δn ≥ 0.8 and subwavelength resolution. Using NIRI we experimentally demonstrate a wavefront shaping flat microlens array operating in the visible (405–635 nm) and mesoporous silicon and silica waveguides operating near 1310 nm. This study demonstrates the viability of patterning arbitrary refractive index distributions, n(x,y), on the surface of a chip while circumventing the challenges and limitations of top-down lithographic techniques – thus opening a low-cost and scalable approach for the realization of advanced planar optical technologies.

36 MATERIALS SCIENCE↗

In-situ imaging of nucleation and growth of superlattices from nanoscale colloidal nanoparticles

Nanoparticle-based superlattices have attracted extensive research efforts due to their versatile composition and packing-dependent optical, magnetic, electronic, catalytic, mechanical properties. Yet the experimental understanding of the thermodynamics and pathways of the crystallization processes for these systems, which govern their ultimate morphology, size, and packing structure, has for long remained underexplored. Here, this minireview highlights recent integration of liquid-phase transmission electron microscopy, which allows for real-space, real-time direct imaging of the crystallization processes at the single-particle level, with simulation and the conceptual framework established by pioneers such as Dr. A. A. Chernov. Different aspects of superlattice formation were revealed by direct imaging for the first time, such as the existence of prenucleation precursor in nonclassical crystallization, surface energy-dependent growth, and coalescence, allowing for the charting of phase coordinates and thermodynamic quantities at the nanoscale. We discuss the similarities and differences of crystal growth behaviors in atomic and nanoparticle systems, as well as engineering opportunities to fashion, shape, and achieve quality control in superlattice formation from nanoparticles, for next-generation optical and mechanical metamaterials.

36 MATERIALS SCIENCE↗

Vibration mitigation in interlocking metasurfaces

Interlocking metasurfaces (ILMs) are a new class of mechanical metamaterials with patterned surface features that enable joining of two adjacent bodies, serving as an alternative to welds, fasteners, or adhesives. While the strength of ILMs has been explored previously, it is also possible to envision ILMs that possess the ability to dampen vibration or tailor energy transmission across the interface. In this study, we explore the vibration transmission under frequency sweep and random excitation of three ILM designs. This is the first study to characterize the response of ILMs under vibration. We find that ILMs which are tightly coupled (e.g., small interference fit) behave as a linear system and depart only marginally from the behavior of a solid body. However, through strategic manipulation of the ILM topology, and in particular the fit clearances, we show that vibrations can be damped by over an order of magnitude. Design strategies to employ ILMs for vibration mitigation are developed using a first-order model.

Bolmin, O. [Carnegie Mellon Univ., Pittsburgh, PA ↗