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Results for “Architected materials”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Influence of strain-rate on the response of elastomeric architected materials

Architected materials have shown substantial promise in impact mitigation and protective applications, and there has accordingly been great interest in better characterizing their response at elevated strain rates due to impact. There remains ambiguity regarding the contribution of inertial and material responses to strain rate sensitivity, and, in particular, when these effects begin to gain dominance in the impact response of an architected material. The response of soft polymer architected materials as a function of strain rate, in particular, has been little investigated. We characterize the experimental impact response of four soft polymer architected lattice geometries across varying strain rates in the intermediate strain rate regime (∼10 3 s −1 ) using split-Hopkinson pressure bar loading and high speed video characterization of the resulting deformation fields. In conclusion, our results highlight the interplay of influence between constituent material, lattice geometry, length scale, and strain rate in determining the onset of significant inertia effects.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Additive manufacturing and processing of architected materials

Architected materials are a unique and emerging class of materials where performance is fundamentally controlled by geometry at multiple length scales, from the nano- to the macroscale, rather than chemical composition alone. As a result, the realization of these remarkable materials is contingent upon the ability to faithfully reproduce the designed architecture. Furthermore, this presents fundamental challenges in fabrication due to the required three-dimensional complexity, multiple length scales, range of material constituents, possibility of multiple materials in a single architecture, and overall manufacturing throughput. Additive manufacturing (AM) processes can provide solutions to some of these challenges and are discussed in this article. Specifically, light-based and extrusion-based processes and associated materials are presented with an emphasis on recent developments, including volumetric additive manufacturing, and on-the-fly mixing of materials in extrusion-based printing systems. While remarkable advancements have been made in AM for architected materials, bringing these materials and processes to industrial realization remains a significant challenge.

36 MATERIALS SCIENCE↗
DOE OSTI2025

3D polycatenated architected materials

Architected materials derive their properties from the geometric arrangement of their internal structural elements. Their designs rely on continuous networks of members to control the global mechanical behavior of the bulk. Here, in this study, we introduce a class of materials that consist of discrete concatenated rings or cage particles interlocked in three-dimensional networks, forming polycatenated architected materials (PAMs). We propose a general design framework that translates arbitrary crystalline networks into particle concatenations and geometries. In response to small external loads, PAMs behave like non-Newtonian fluids, showing both shear-thinning and shear-thickening responses, which can be controlled by their catenation topologies. At larger strains, PAMs behave like lattices and foams, with a nonlinear stress-strain relation. At microscale, we demonstrate that PAMs can change their shapes in response to applied electrostatic charges. The distinctive properties of PAMs pave the path for developing stimuli-responsive materials, energy-absorbing systems, and morphing architectures.

36 MATERIALS SCIENCE↗
DOE OSTI2026

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↗
DOE OSTI2020

Investigating Porous Media for Relief Printing Using Micro-Architected Materials

Advances in printed electronics are predicated on the integration of sophisticated printing technologies with functional materials. Although scalable manufacturing methods, such as letterpress and flexographic printing, have significant history in graphic arts printing, functional applications require sophisticated control and understanding of nanoscale transfer of fluid inks. In this paper, a versatile platform is introduced to study and engineer printing forms, exploiting a microscale additive manufacturing process to design micro-architected materials with controllable porosity and deformation. Building on this technology, controlled ink transfer for submicron functional films is demonstrated. The design freedom and high-resolution 3D control afforded by this method provide a rich framework for studying mechanics of fluid transfer for advanced manufacturing processes.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Fabric controls on fracture surface roughness of an architected rock material

Fluid flow through fractures is intimately linked to the fracture surfaces that define the void geometry through which fluids flow. Thus, an understanding of what controls fracture surface roughness is essential to the development of models for predicting fluid transport through fractured rock. The difficulty in predicting surface roughness arises from the complexity of rock which is inherently heterogeneous and nonuniform in composition, fabric, and structural components, even when samples are acquired from the same rock mass. Here, a benchmarked-simulation approach motivated from geo-architected 3D printed synthetic gypsum rocks is used to provide insight into the competing contributions from fabric and layering on fracture roughness formation. Simulation results from a discrete element model (Particle Flow Code, Itasca Consulting Group, Inc.) clearly indicate that the relative orientation between mineral layers and in-layer mineral fabric, and the variability in mineral bonding strengths determine whether anisotropic corrugated surfaces or isotropic surfaces are formed. Weak mineral layers oriented perpendicular to the applied load resulted in strong roughness anisotropy. Peak failure loads were found to vary up to 30% depending on the strength of the mineral fabric at the location of fracture initiation, which provides insight into the observed high variability in strength values of natural rock. The uniqueness of induced fracture roughness and peak failure load is intimately linked to layering, mineral fabric, and their distribution in the rock. These findings have important implications for any architected material fabricated through serial printing of layers with local compositional heterogeneity.

3D printed rock↗
DOE OSTI2020

Additive manufacturing of three-dimensional (3D)-architected CoCrFeNiMn high- entropy alloy with great energy absorption

In this study, we developed an approach to additive manufacturing of three-dimensional (3D)-architected CoCrFeNiMn high-entropy alloys by direct ink writing combined with thermal sintering. The 3D-architected CoCrFeNiMn lattices exhibit the outstanding energy absorption capacity that expands the envelope of existing architected materials. Such a high-energy absorption ability originates from the bend-dominated deformation mode of the 3D-architecture as well as the fully-annealed homogeneous microstructure of equiaxed grains, which collectively lead to remarkable strain hardening upon deformation. Our study provides a new avenue for 3D-printing advanced architected materials with extreme mechanical energy absorption for a myriad of structural applications.

mechanical property↗
DOE OSTI2022

Anisotropic yield models for lattice unit cell structures exploiting orthotropic symmetry

We report numerical homogenization enables efficient computational analysis and design of multiscale structures made of micro-architected materials including lattice unit cells. However, predicting yield is nontrivial because it requires accurate and efficient predictions of the maximum stress inside the homogenized unit cells. To address this challenge, we develop a macroscale anisotropic yield function for micro-architected materials. The yield function depends on the three-dimensional macroscale stress state and the parameters describing a family of micro-architectures, such as the radii of the struts in a lattice unit cell. To ensure accuracy, we determine the maximum stress using three-dimensional continuum finite-element analysis. To ensure efficiency, we construct surrogate models from the aforementioned high-fidelity results for yield prediction. To reduce simulation costs and surrogate modeling complexity, we leverage orthotropic symmetry commonly found in lattice unit cells. In this paper, we provide a thorough presentation of group representations and the systematic procedure to exploit orthotropic domain symmetry in homogenization and surrogate modeling. We illustrate the use of linear homogenization results to predict yield in specific unit cells without further simulations. We furthermore show that surrogate modeling presents a viable option for anisotropic yield prediction in a continuously parametrized family of micro-architectures. More specifically, despite the dimensionality and degree of nonlinearity in the maximum micro von Mises stress within the unit cell, the surrogate models can predict it with less than 5% error at least 90% of the time. Moreover, the largest under-prediction error, which is more critical than the over-prediction error, is typically less than 10%.

42 ENGINEERING↗
DOE OSTI2025

Laser‐Powder Melt Pool Solidification Dynamics and Microstructural Engineering of Ti‐5553 Microlattices

The fine geometric and topological control afforded by additive manufacturing technologies has enabled the manufacture of architected materials across length scales, and enabling tunable mechanical performance as a function of local and global design. Progress has been made to tune the mechanical response of architected materials through geometry, but understanding how the geometry and processing conditions will inform the microstructure remains a challenge due to the rapid solidification in laser powder bed fusion. This study uses in situ X-ray imaging and electron backscatter diffraction microscopy to demonstrate that the melt pool size, microstructure morphology, and elastic strain distribution is influenced by a combination of lattice geometry and laser processing conditions. These results indicate that within larger melt pools the local thermal gradients are sufficient to enable a columnar-to-equiaxed transition across the melt pool. Furthermore, the solidification mechanisms producing these microstructures are examined across the first 5 ms of melting and solidification, described via in situ high-speed X-ray imaging and mirrored via multiphysics simulation.

additive manufacturing↗
DOE OSTI2026

U-net architected deep material network training with microstructure local field information

The Deep Material Network (DMN) has recently emerged as a powerful reduced-order modeling framework for simulating the mechanical response of heterogeneous materials such as composites. Unlike most data-driven approaches that directly learn a material’s response under prescribed loading, the DMN acts as a homogenization operator, learning the kinematic constraints and mechanical interactions of the underlying microstructure. However, traditional DMN training relies exclusively on homogenized effective properties derived from Direct Numerical Simulations (DNS), discarding the rich local field data that govern microstructural interactions. In this work, we extend the DMN framework to incorporate such local field information into the offline training process. Utilizing a U-Net architecture, we augment the DMN training objective to include the first and second statistical moments of the local stress fields obtained from linear DNS. This ensures that the learned network topology not only fits the effective stiffness but also accurately reflects the internal local stress and strain partitioning of the microstructure. The results confirm that supervising the localization process during training yields a superior surrogate model, reducing local prediction errors by an order of magnitude and significantly improving generalization to unseen nonlinear constitutive behaviors compared to traditional DMNs.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Designs and Modeling of Architect Multi-material Scintillator System

We present a new conceptual radiation detector, the Architected Multimaterial Scintillator System, that utilizes a scintillator composed of multiple materials arranged in architected structures to enable new capabilities. By structuring differently-dyed materials, the wavelength of the scintillation light encodes additional information in radiation measurements. These structures can be realized through additive manufacture (3D-printing). Two classes of this concept are described and modelled using Monte Carlo simulations to evaluate their performance. The first detector design uses dye microstructures to encode particle tracking information, allowing for directional neutron detection and gamma/neutron discrimination. The second design uses a dye gradient to indicate the position of radiation along the gradient. The simulation results indicate this new concept in radiation detection can achieve strong performance in a variety of capabilities including particle identification, directionality and spectroscopy measurements, and particle position reconstruction.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Knots are not for naught: Design, properties, and topology of hierarchical intertwined microarchitected materials

Lightweight and tough engineered materials are often designed with three-dimensional hierarchy and interconnected structural members whose junctions are detrimental to their performance because they serve as stress concentrations for damage accumulation and lower mechanical resilience. We introduce a previously unexplored class of architected materials, whose components are interwoven and contain no junctions, and incorporate micro-knots as building blocks within these hierarchical networks. Tensile experiments, which show close quantitative agreements with an analytical model for overhand knots, reveal that knot topology allows a new regime of deformation capable of shape retention, leading to a ~92% increase in absorbed energy and an up to ~107% increase in failure strain compared to woven structures, along with an up to ~11% increase in specific energy density compared to topologically similar monolithic lattices. Our exploration unlocks knotting and frictional contact to create highly extensible low-density materials with tunable shape reconfiguration and energy absorption capabilities.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Embedded 3D printing of isotropically enhanced lattice structure with programmable elasticity via three-dimensional fiber alignment

Engineered composites with fiber orientation in a complete three-dimensional (3D) context are highly desired for maximizing structural performance as they mimic the well-organized fiber arrangement in natural composites. However, most fabrication techniques lack the capability for through-plane (z-axis) alignment, limiting the possibility for structural design and performance optimization. In this study, we present an embedded 3D printing approach that enables complete 3D fiber alignment, including region-specific alignment control along the through-plane direction. Our method utilizes the extrusion and suspension of composite inks within a supporting matrix. By regionally adjusting the ink extrusion rate and nozzle translation rate, we locally manipulated the fiber arrangement within the composite 3D architecture. Here, we demonstrate that the 3D alignment of carbon fibers in a structural composite significantly enhances both mechanical properties and thermal conductivity in the in-plane and through-plane directions. Furthermore, by strategically arranging regional fiber orientations within micro-architected materials, we fabricated metamaterial engineered composites with programmable anisotropy ratio and directional moduli.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Three-dimensional hierarchically porous MoS 2 foam as high-rate and stable lithium-ion battery anode

Architected materials that actively respond to external stimuli hold tantalizing prospects for applications in energy storage, wearable electronics, and bioengineering. Molybdenum disulfide, an excellent two-dimensional building block, is a promising candidate for lithium-ion battery anode. However, the stacked and brittle two-dimensional layered structure limits its rate capability and electrochemical stability. Here we report the dewetting-induced manufacturing of two-dimensional molybdenum disulfide nanosheets into a three-dimensional foam with a structural hierarchy across seven orders of magnitude. Our molybdenum disulfide foam provides an interpenetrating network for efficient charge transport, rapid ion diffusion, and mechanically resilient and chemically stable support for electrochemical reactions. These features induce a pseudocapacitive energy storage mechanism involving molybdenum redox reactions, confirmed by in-situ X-ray absorption near edge structure. The extraordinary electrochemical performance of molybdenum disulfide foam outperforms most reported molybdenum disulfide-based Lithium-ion battery anodes and state-of-the-art materials. This work opens promising inroads for various applications where special properties arise from hierarchical architecture.

25 ENERGY STORAGE↗
DOE OSTI2023

Reinforcement learning-based design of shape-changing metamaterials

During the last decade, artificially architected materials have been designed to obtain properties unreachable by naturally occurring materials, whose properties are determined by their atomic structure and chemical composition. In this work, we implement a new reinforcement learning (RL) method able to rationally design unique metamaterial structures at the nano-, micro-, and macroscale, which change shape during operational conditions. As an example, we apply this method to design nanostructured silicon anodes for Li-ion batteries (LIBs). The RL model is designed to apply different actions and predict change during operational conditions. The multi-component reward function comprises an increase in the total storage capacity of the resulting battery electrode and structural parameters, such as the minimum distance between the individual components of the nanostructure. Upon experimental validation using a polymer-based 3D printing technique, we expect that the newly discovered structures improve the current Si-based LIB anodes state-of-the-art by almost three times and almost ten times the current commercial LIB based on a graphitic anode. Furthermore, this RL-based optimization method opens up vast design space for other responsive metamaterials with tailored properties and pre-programmed structural transformation.

25 ENERGY STORAGE↗