Lattice Architectures Research Articles

Context-aware coupler reconfiguration for tunable coupler-based superconducting quantum computers

Abstract Crosstalk, caused by unwanted interactions from the surrounding environment, remains a fundamental challenge in existing superconducting quantum computers (SQCs). We propose a method for qubit placement, connectivity, and logical qubit allocation on tunable-coupler SQCs to eliminate unnecessary qubit connections and optimize resources while reducing crosstalk errors. Existing mitigation methods carry trade-offs, like increasing qubit connectivity or software-based gate scheduling. Our method, the Context-Aware COupler REconfiguration (CA-CORE) compilation method, aligns with application-specific design principles. It optimizes the qubit connections for improved SQC performance, leveraging tunable couplers. Through contextual analysis of qubit correlations, we configure an efficient coupling map considering SQC constraints. We then apply the SWAP-based Bidirectional Heuristic Search (SABRE) qubit mapping method and crosstalk-adaptive scheduling to further optimize the quantum circuit. Our architecture reduces depth by an average of 18% and 27%, and by up to 50% and 60%, compared to lattice and heavy-hex architectures, respectively. With crosstalk optimization through adaptive scheduling, we achieve performance improvements of 35%, 20%, and 160% on fully-enabled grid, lattice, and heavy-hex topologies, respectively.

Programmable heterogeneous lamellar lattice architecture for dual mechanical protection

Shear bands frequently appear in lattice architectures subjected to compression, leading to an unstable stress-strain curve and global deformation. This deformation mechanism reduces their energy absorption and loading-bearing capacity and causes the architectures to prioritize mechanical protection of external components at the expense of the entire structure. Here, we leverage the design freedom offered by additive manufacturing and the geometrical relation of dual-phase nanolamellar crystals to fabricate heterogeneous lamellar lattice architectures consisting of body-centered cubic (BCC) and face-centered cubic (FCC) unit cells in alternating lamella. The lamellar lattice demonstrates more than 10 and 9 times higher specific energy absorption and energy absorption efficiency, respectively, compared to the BCC lattice. The drastic improvement arises as the nucleation of shear bands is inhibited by the discrete energy threshold for plastic buckling of adjacent heterogeneous lattice lamella during loading. Despite its lower density than the FCC lattice, the lamellar lattice exhibits significant enhancement in plateau stress and crushing force efficiency, attributed to the strengthening effect induced by simultaneous deformation of unit cells in the BCC lattice lamella and the resulting cushion shielding effect. The design improves the global mechanical properties, making lamellar lattices compare favorably against numerous materials proposed for mechanical protection. Additionally, it provides opportunities to program the local mechanical response, achieving programmable internal protection alongside overall external protection. This work provides a different route to design lattice architecture by combining internal and external dual mechanical protection, enabling a generation of multiple mechanical protectors in aerospace, automotive, and transportation fields.

High Areal Capacitance and Rate Capability of 3D-Printed Thick Electrodes with Optimized Conductive Networks from the Core-Sheath Structure.

Material extrusion 3D printing has received enormous attention to potentially overcome its limits by tailoring and designing thick electrodes. In this work, we prepared a thick reduced graphene oxide/carbon nanotube-reduced graphene oxide/carbon nanotubes/manganese oxide@carbon nanotubes (rGC-rGCMC) electrode with controlled lattice architectures, core-sheath structure, and hierarchical porosity by material coaxial extrusion 3D printing, freeze-drying, and thermal treatment. The volume ratios of core to sheath, including 100%-0%, 0%-100%, 20%-80%, 30%-70%, 40%-60%, and 50%-50%, were designed to investigate the influences of the core-sheath structure on thick electrodes. The electrodes with a core-sheath volume ratio of 30%-70% electrodes exhibited an enhanced areal specific capacitance of 588.27 mF cm-2 (39.48 F g-1) at a scan rate of 0.5 mA cm-2. All capacitance decays from core-sheath electrodes (20%-80%, 30%-70%, 40%-60%, and 50%-50%) were smaller than those from rGCMC (0%-100%) electrodes, indicating the improved rate capability from the core-sheath structure. On comparison of 30%-70% core-sheath electrodes with electrodes made of a homogeneous 30% rGC and 70% rGCMC mixture (30%+70%), lower capacitance (382.27 mF cm-2 and 25.66 F g-1 at 0.5 mA cm-2) of the 30%+70% mixture electrode without a core-sheath structure suggested less efficiency to harvest electrons from the redox reactions. Electrochemical impedance spectroscopy (EIS) data further supported and explained the resistances of thick electrodes with different volume ratios.

Correction to “Lattice Architectures for Thermoelectric Energy Harvesting”

Correction to “Lattice Architectures for Thermoelectric Energy Harvesting”

Impact behavior of periodic, stochastic, and anisotropic minimal surface-lattice sandwich structures

Recent advancements in 3D printing technologies have made it possible to fabricate intricate lattice architectures with high precision. These lattices can now be utilized to design lightweight sandwich structures that serve multiple functions. To enhance the impact loading performance of these structures, it is crucial to understand how the lattice's topological properties, particularly those with minimal surface attributes like periodic or stochastic Primitive and Gyroid triply periodic minimal surfaces (TPMS) and spinodal-like stochastic cellular materials, associate with the mechanical properties of sandwich structures while keeping the skin thickness fixed. Thus, this paper explores the low-velocity impact behavior of various sheet/shell-based minimal surface-latticed cores of sandwich structures with woven composite skins. The elasto-plastic-damage numerical simulations consider lattice core periodicity, randomness, and anisotropy while keeping the relative density constant. Core lattice randomness and anisotropy are designed using the Gaussian Random Field (GRF) method for spinodal-based stochastic cellular materials and stochastic TPMS. The simulation results showed that the periodic Primitive-lattice core exhibits high out-of-plane shearing strength, enabling the sandwich structure to demonstrate the highest perforation limit. GRF spinodal-based core achieved the highest peak load due to its anisotropic mechanical properties. However, the post-yielding bending of the lattice sheet limited its ability to resist perforation, and absorb and dissipated energy. Interestingly, the stochastic Gyroid TPMS topology, with its inherent densely-distributed microstructure, showed high sensitivity to loading rate, resulting in enhanced energy absorption and dissipation of the sandwich structure. These findings offer valuable insights for optimizing multifunctional sandwich structures with superior impact performance and their design for additive manufacturing.

Lattice Architectures for Thermoelectric Energy Harvesting

Lattice Architectures for Thermoelectric Energy Harvesting

Stiffness, strength, anisotropy, and buckling of lattices derived from TPMS and Platonic and Archimedean solids

Lattice metamaterials have gained considerable attention due to their distinctive topological structures and multifunctional properties. In this work, the effect of topology, loading conditions, and relative density on the effective mechanical properties of various novel lattice architectures is investigated numerically and experimentally. Thirteen strut-based lattices derived from triply periodic minimal surfaces (five lattices) as well as Platonic (three lattices) and Archimedean (five lattices) solids are considered for the first time, and their anisotropic mechanical properties, including uniaxial, shear, and bulk moduli and strengths as well as their total stiffness, buckling strengths, Poisson’s ratio, and anisotropy are investigated as a function of a wide range of relative densities (0.1% to 37%). Finite element analysis is employed to capture the full effective behavior of these lattices using periodic boundary conditions. Bifurcation analysis is performed to predict the threshold relative density governing their buckling vs yielding deformation behavior. Selected lattice structures of various relative densities are 3D printed using polymer selective laser sintering additive manufacturing technique and tested under quasi-static uniaxial compression where the experimental and numerical results are compared. The numerical results indicate that the deformation behavior can be altered between stretching and bending dominated mode of deformation as function of loading. Archimedean lattices are shown to outperform a wide range of strut-based lattices. This work opens the doors for more investigations of the multifunctional properties of these novel types of lattices and their engineering applications. Furthermore, the generated comprehensive data are useful in optimizing latticed structures using topology optimization techniques.

Biomimetic dual-phase ceramic lattice architectures with enhanced mechanical and vibration isolation performances

Ceramic materials have broad application prospects for impact/perforation protection purposes due to their high strength, high hardness, and other characteristics. Nevertheless, the high brittleness, susceptibility to fracture, and difficulty in processing and forming limit the popularization of ceramic components. This paper proposed a novel silica gel-filled dual-phase ceramic lattice meta-structure based on a biomimetic biphasic design method to achieve the improvement of mechanical properties. Two configurations of dual-phase body-centered cubic (BCC) and face-centered cubic (FCC) ceramic lattice structures were designed and fabricated through DLP-based additive manufacturing and simple filling technology. Quasi-static compression and dynamic vibration testing were conducted. Comparisons between single-phase and dual-phase ceramic lattices were performed from the perspective of compression strength, fracture toughness, and vibration level difference. It was demonstrated that the addition of soft silica gel reduced the stress concentration at the connection of the lattice rod and effectively inhibited the crack propagation. The dual-phase BCC lattice structure exhibited a 3 times increase in toughness and a 4.2 times increase in compressive strength relative to the single-phase design. The toughness and compressive strength of the dual-phase FCC ceramic lattice were increased by 1.4 times. The introduction of the soft silica gel achieved a significant vibration isolation in the pre-resonance frequency band between 1000 Hz to 3000 Hz. This study provides a reliable method for constructing biomimetic dual-phase meta-structures with both load-bearing capacity and low-frequency vibration isolation capacity.

Finite element modeling of the free boundary effect on gyroid additively manufactured samples

There is a significant need for models that can capture the mechanical behavior of complex porous lattice architectures produced by 3D printing. The free boundary effect is an experimentally observed behavior of lattice architectures including the gyroid triply periodic minimal surface where the number of unit cell repeats has been shown to influence the mechanical performance of the lattice. The purpose of this study is to use finite element modeling to investigate how architecture porosity, unit cell size, and sample size dictate mechanical behavior. Samples with varying porosity and increasing number of unit cells (relative to sample size) were modeled under an axial compressive load to determine the effective modulus. The finite element model captured the free boundary effect and captured experimental trends in the structure’s modulus. The findings of this study show that samples with higher porosity are more susceptible to the impact of the free boundary effect and in some samples, the modulus can be 20% smaller in samples with smaller numbers of unit cell repeats within a given sample boundary. The outcomes from this study provide a deeper understanding of the gyroid structure and the implications of design choices including porosity, unit cell size, and overall sample size.

Uniformity of Electrodeposited Coatings Onto Additively Manufactured Graphite Lattice Electrodes

The ability to uniformly electrodeposit metallic coatings onto geometrically complex substrates plays a significant role in developing specialized applications from coating detailed RF components to depositing catalytic coatings onto ordered foams electrodes for electrochemical flow reactors. However, there presently lacks guidelines for electrodeposition in porous media due to the problem’s multi-scale complexity. We present a framework for deconvoluting this process through continuum-level modeling and experimental validation of electrodeposited copper onto additively manufactured conductive lattice structures. Through numerical simulations we can predict thickness profiles and validate the model prediction and coating quality through micro-computed tomography. We further devise scaling laws with the aim of facilitating control over deposition uniformities on different lattice architectures and dimensions under fluid flow. In extension, the manufacturing platform for functionalized electrodes is extended to battery applications as use in novel electrode geometries within rechargeable secondary batteries as well as plating thickness evolution in custom redox flow battery cathodes for grid scale energy storage.This work is performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344 within the LDRD program 20-ERD-056. LLNL-ABS-847849.

Predicting buckling resistance of two three-dimensional lattice architectures

Lattice structures are an important class of architected cellular solids and structures with high potential for multifunctional and lightweight applications. Novel technologies such as additive manufacturing have vastly extended the design freedom to develop such architectures. In this work, a reliable theoretical model for optimizing unit cell design against buckling is developed for two different cell architectures: pyramidal and tetrahedral. The model’s accuracy was evaluated through extensive finite element analysis and compared to existing methods available in the literature.

Enhanced Energy Absorption of Additive-Manufactured Ti-6Al-4V Parts via Hybrid Lattice Structures.

In this study, we present the energy absorption capabilities achieved through the application of hybrid lattice structures, emphasizing their potential across various industrial sectors. Utilizing Ti-6Al-4V and powder bed fusion (PBF) techniques, we fabricated distinct octet truss, diamond, and diagonal lattice structures, tailoring each to specific densities such as 10, 30, and 50%. Furthermore, through the innovative layering of diverse lattice types, we introduced hybrid lattice structures that effectively overcome the inherent energy absorption limitations of single-lattice structures. As a result, we conducted a comprehensive comparison between single-lattice structures and hybrid lattice structures of equal density, unequivocally showcasing the latter's superior energy absorption performance in terms of compression. The single-lattice structure, OT, showed an energy absorption of 42.6 J/m3, while the reinforced hybrid lattice structure, OT-DM, represented an energy absorption of 77.8 J/m3. These findings demonstrate the significant potential of hybrid lattice structures, particularly in energy-intensive domains such as shock absorption structures. By adeptly integrating various lattice architectures and leveraging their collective energy dissipation properties, hybrid lattice structures offer a promising avenue for addressing energy absorption challenges across diverse industrial applications.

Accurate computational design of three-dimensional protein crystals.

Protein crystallization plays a central role in structural biology. Despite this, the process of crystallization remains poorly understood and highly empirical, with crystal contacts, lattice packing arrangements and space group preferences being largely unpredictable. Programming protein crystallization through precisely engineered side-chain-side-chain interactions across protein-protein interfaces is an outstanding challenge. Here we develop a general computational approach for designing three-dimensional protein crystals with prespecified lattice architectures at atomic accuracy that hierarchically constrains the overall number of degrees of freedom of the system. We design three pairs of oligomers that can be individually purified, and upon mixing, spontaneously self-assemble into >100 µm three-dimensional crystals. The structures of these crystals are nearly identical to the computational design models, closely corresponding in both overall architecture and the specific protein-protein interactions. The dimensions of the crystal unit cell can be systematically redesigned while retaining the space group symmetry and overall architecture, and the crystals are extremely porous and highly stable. Our approach enables the computational design of protein crystals with high accuracy, and the designed protein crystals, which have both structural and assembly information encoded in their primary sequences, provide a powerful platform for biological materials engineering.

3D‐Printed Inherently Porous Structures with Tetrahedral Lattice Architecture: Experimental and Computational Study of Their Mechanical Behavior

AbstractIncreasing demand in automotive, construction, and medical industries for materials with reduced weight and high mechanical durability has given rise to porous materials and composites. Materials combining nano‐ and microporosity and a well‐defined cellular macroporous architecture offer great potential weight reduction while maintaining mechanical durability. To achieve predictable mechanical performance, it is essential to apply experimental and computational efforts to precisely describe material structure–properties relationships. This study explores polymer structures with polymerization‐inherited porosity and well‐defined macroporous geometry, fabricated via digital light processing (DLP) 3Dprinting. Pore size and relative density are varied by ink composition and printing parameters to track their influence on the structure stiffness. Simulated stiffness values for the base polymer correspond to the experimentally determined elastic properties, showing Young's moduli of 554–722 MPa depending on the cosolvent ratio, which confirms the structure–properties relationship. Macroporosity is introduced in the form of a 3D tetrahedral bending‐dominated architecture with the resulting specific Young's moduli of 79.5 MPa cm3 g−1, comparable to foams. To merge the gap in stiffnesses, further investigation of structure–property relationships of various 3D–printed lattice architectures, as well as its application to other stereolithography methods to eliminate the negative effects from printing artifacts and resolution limit of the DLP 3D‐printing, are envisioned.

Artificial neural network model of the mechanical behaviour of shape memory alloy Schwartz primitive lattice architectures

This work proposes a novel artificial neural network (ANN)-based framework to explore the mechanical behaviour of shape memory alloy (SMA) Schwartz primitive triply periodic minimal surfaces (TPMSs) architectures where a loop with multiple conditions (LMCs) is introduced into the framework to improve its accuracy. Remarkably, it is found that the introduced ANN-based framework comprehends extremely well the example data and then provides a highly accurate prediction for the topology-driven mechanical behaviour of the SMA TPMS lattice architectures, which do not belong to the example. Indeed, the mechanical responses obtained from ANN-based approach excellently agree with that from numerical homogenization, with the maximum percent difference below 2.7% attained when the TPMS is subjected to tension or shear during the loading and unloading processes. More interestingly, the ANN-based approach can perform well with the increment of relative density or temperature 1000 times smaller than that in the homogenization, only requiring a little simulation time or thousands of times faster than that in the homogenization at the same computer setup. Hence, the mechanical behaviour of SMA TPMSs can be accurately characterized by the proposed framework at almost any value of the relative density or the temperature after the training. Subsequently, the ANN-based framework is used to map two-dimensionally the impact of varying relative density, temperature, and deformation on the effective hardness and superelasticity of the SMA TPMS architectures. The results show that the superelasticity of SMA TPMS scaffolds increases with decreased temperature and relative density and with increased deformation, in a nonlinear pattern. This work lays the foundation for further research on using ANN to explore the mechanical response and advanced applications of the complex SMA-based structures, such as smart composite systems, helical springs, and metamaterials at considerably reduced computational and financial costs.

Role of Hydride Formation in Electrocatalysis for Sustainable Chemical Transformations

The electrochemical potential of numerous reduction reactions corresponds to hydrogen pressures that thermodynamically favor the formation of many metal hydrides. Whether a catalyst remains metallic with hydrogen on the surface (Hads) or absorbs hydrogen into its lattice (Habs), forming a metal hydride, results from a balance between not only this thermodynamic driving force but also the kinetics of concurrent surface reactions and equilibrium surface coverage. Drawing parallels with thermal catalytic processes, we provide examples of how hydride formation impacts electrocatalysis in H2 evolution, organic and CO2 reduction, and N2 and NO3– reduction reactions. Hydride formation not only changes catalyst activity and selectivity but also can impact durability. We highlight techniques capable of identifying hydride formation under reaction conditions, imperative for an understanding of electrocatalyst kinetics. Hydrides offer many possibilities in electrocatalysis, including unique reaction mechanisms involving the catalyst lattice and innovative reactor architectures, beneficial for applications in chemical transformations and energy.

Mechanical Properties of AISI 316L Lattice Structures via Laser Powder Bed Fusion as a Function of Unit Cell Features.

The growth of additive manufacturing processes has enabled the production of complex and smart structures. These fabrication techniques have led research efforts to focus on the application of cellular materials, which are known for their thermal and mechanical benefits. Herein, we studied the mechanical behavior of stainless-steel (AISI 316L) lattice structures both experimentally and computationally. The lattice architectures were body-centered cubic, hexagonal vertex centroid, and tetrahedron in two cell sizes and at two different rotation angles. A preliminary computational study assessed the deformation behavior of porous cylindrical samples under compression. After the simulation results, selected samples were manufactured via laser powder bed fusion. The results showed the effects of the pore architecture, unit cell size, and orientation on the reduction in the mechanical properties. The relative densities between 23% and 69% showed a decrease in the bulk material stiffness up to 93%. Furthermore, the different rotation angles resulted in a similar porosity level but different stiffnesses. The simulation analysis and experimental results indicate that the variation in the strut position with respect to the force affected the deformation mechanism. The tetrahedron unit cell showed the smallest variation in the elastic modulus and off-axis displacements due to the cell orientation. This study collected computational and experimental data for tuning the mechanical properties of lattice structures by changing the geometry, size, and orientation of the unit cell.

Three-dimensional printing of mycelium hydrogels into living complex materials.

Biological living materials, such as animal bones and plant stems, are able to self-heal, regenerate, adapt and make decisions under environmental pressures. Despite recent successful efforts to imbue synthetic materials with some of these remarkable functionalities, many emerging properties of complex adaptive systems found in biology remain unexplored in engineered living materials. Here, we describe a three-dimensional printing approach that harnesses the emerging properties of fungal mycelia to create living complex materials that self-repair, regenerate and adapt to the environment while fulfilling an engineering function. Hydrogels loaded with the fungus Ganoderma lucidum are three-dimensionally printed into lattice architectures to enable mycelial growth in a balanced exploration and exploitation pattern that simultaneously promotes colonization of the gel and bridging of air gaps. To illustrate the potential of such mycelium-based living complex materials, we three-dimensionally print a robotic skin that is mechanically robust, self-cleaning and able to autonomously regenerate after damage.

Inverse design of truss lattice materials with superior buckling resistance

Manipulating the architecture of materials to achieve optimal combinations of properties (inverse design) has always been the dream of materials scientists and engineers. Lattices represent an efficient way to obtain lightweight yet strong materials, providing a high degree of tailorability. Despite massive research has been done on lattice architectures, the inverse design problem of complex phenomena (such as structural instability) has remained elusive. Via deep neural network and genetic algorithm, we provide a machine-learning-based approach to inverse-design non-uniformly assembled lattices. Combining basic building blocks, our approach allows us to independently control the geometry and topology of periodic and aperiodic structures. As an example, we inverse-design lattice architectures with superior buckling performance, outperforming traditional reinforced grid-like and bio-inspired lattices by ~30–90% and 10–30%, respectively. Our results provide insights into the buckling behavior of beam-based lattices, opening an avenue for possible applications in modern structures and infrastructures.

Bio-inspired 3D-printed lattice structures for energy absorption applications: A review

The biomimetic approach rapidly evolves for designing novel lightweight structures and has been expanding in engineering design. Additive manufacturing or 3D printing permits three-dimensional parts to be fabricated with an intricacy and quality that might be tough or impossible to appreciate with the present traditional production techniques. With the probabilities and exactitude, 3D printing allows bio-inspired lattice structures from nature that are hypothetically advanced to ingest excellent energy absorption capacity with less material. The combination of additive manufacturing with cellular lattice architectures offers potential design options regarding material utilization, strength, cost, and component weight. A summary of recent advances in the improvement of bio-inspired structures is outlined in this review paper. Specifically, exciting highlights and remarkable mechanical properties of bio-inspired structures of bones, teeth, and dermal layers of creatures might be bio-mimicked to style economical energy absorbers. Researchers and engineers can use this information to create unique designs inspired biologically for the application of absorption energy.