Structural Metamaterials: Session II
Sponsored by: TMS Materials Processing and Manufacturing Division, TMS Structural Materials Division, TMS: Additive Manufacturing Committee, TMS: Mechanical Behavior of Materials Committee
Program Organizers: Amy Wat, Lawrence Livermore National Laboratory; Brad Boyce, Sandia National Laboratories; Xiaoyu Zheng, University of California, Los Angeles; Fabrizio Scarpa, University of Bristol; Robert Ritchie, University of California, Berkeley
Monday 2:00 PM
February 28, 2022
Location: Anaheim Convention Center
Flexibly Tunable Yet Strong Gear-based Mechanical Metamaterials: Peter Gumbsch1; Xin Fang2; Jihong Wen2; Li Cheng3; Dianlong Yu2; Hongjia Zhang2; 1Karlsruhe Institute of Technology KIT; 2NUDT; 3HongKong Polytechnic University
Adaptive robotics and other mission orineted engineering applications often seek materials with tunable elasticity, a property that conventional materials cannot offer. Though possible in reconfigurable metamaterials, continuous tunability in existing designs is plagued by structural instability and plastic failure. Here, we present an innovative metamaterial design using gears with encoded stiffness gradients as the constituent elements, and organizing gear clusters for various functions. The design enables continuous yet tunable elastic properties while preserving stability and robust rotational maneuverability, even under heavy load. Such gear-based metamaterials enable unprecedented properties like the modulation of Young’s modulus by two orders of magnitude, and morphing shape between fluid-like and solid states. This allows customizing metamaterials and brings fully programmable materials and adaptive robots within reach.
A Comparison of Energy Absorption Behavior of Additively Manufactured AlSi10Mg Honeycomb, Lattice and TPMS Cellular Structures under Quasistatic Compression: Mandar Shinde1; Irving Ramirez-Chavez1; Daniel Anderson1; Jason Fait2; Mark Jarrett2; Dhruv Bhate1; 1Arizona State University; 2BAE Systems
Metallic honeycombs and foams have been used for energy absorption due to their ability to reduce transmitted stresses while enabling high specific energy absorption. Additive manufacturing has enabled the evaluation of a wide range of cellular materials in an attempt to further improve performance. In this work, AlSi10Mg honeycombs, auxetic and stochastic lattices, and diamond, gyroid and Schwarz-P Triply TPMS structures were manufactured using the laser powder bed fusion process, and subjected to quasistatic compression. The responses and energy absorption characteristics of the different shapes across three relative densities was compared, with specific emphasis laid on the shape of the load-displacement response. Explicit FEA simulation was validated against, and combined with, experimentally observed deformation patterns in order to relate structure to a range of energy absorption properties. Failure modes were also characterized and found to be a function of cell shape and relative density.
Architectured Bioinspired Alumina with a Metallic Nickel Compliant-phase: Amy Wat1; Claudio Ferraro2; Xu Deng3; Andrew Sweet4; Antoni Tomsia5; Eduardo Saiz2; Robert Ritchie4; 1Lawrence Livermore National Laboratory; 2Imperial College London; 3University of Electronic Science and Technology of China; 4University of California, Berkeley; 5Lawrence Berkeley National Laboratory
Many biological materials are composites comprising hard and soft constituents arranged into multiple-scale, hierarchical architectures that form compelling combinations of mechanical properties. One notable example is the brick-and-mortar structure of nacre, which has resulted in high-toughness ceramics using polymeric mortars as a compliant phase. Theoretical modeling has predicted that metallic mortars could lead to higher damage tolerance in these materials, although it is difficult to melt-infiltrate metals into ceramic scaffolds as they cannot readily wet ceramics. We report an approach to synthesize “nacre-like” structured ceramics containing a thin nickel mortar. These materials were fabricated using nickel-coated alumina platelets that are aligned via slip-casting and rapidly sintered using spark-plasma sintering. The dewetting of the nickel mortar during sintering was prevented using NiO-coated as well as Ni-coated platelets. As a result, we have produced a “nacre-like” alumina displaying a resistance-curve toughness up to ~16 MPa·m˝ with a flexural strength of ~300 MPa.
Interpenetrating Chain Lattices with Tailorable Energy Absorption in Tension: Spencer Taylor1; Zachary Cordero1; 1Massachusetts Institute of Technology
This talk introduces the chain lattice, a hierarchical cellular solid comprising two interpenetrating lattices. One lattice toughens the material and prevents catastrophic localized failure, while the other serves as a porous matrix that densifies to absorb energy during tensile loading. An experimentally validated micromechanics model is developed to predict the effect of chain lattice geometry on strength and energy absorption. Our results demonstrate how chain lattices can transform brittle 3D-printable materials into damage-tolerant, notch-insensitive metamaterials.
3:20 PM Break
Combined Effects of Heterogeneity and Length-scale on Mechanical Properties of Lattice Metamaterials: Mujan Seif1; Matthew Beck1; 1University of Kentucky
Lattice mechanical metamaterials have received a great deal of attention due to their extraordinary mechanical properties. Metamaterials based on bending-dominated structures, particularly BCC metamaterials, have been reported to exhibit high specific energy absorption, but lower stiffness and strength. Here, we report the effect of increasing heterogeneity in BCC lattice materials computed using a stochastic mechanical modeling approach previously applied to open-cell foam structures. Distributions of computed properties also reveal details of the transition from micro- to meso-scale (bulk-like) behavior and the expected variability in observed mechanical responses.
Machine Learning Design of Dynamic/Impact Behaviors: Desheng Yao1; 1University of California, Los Angeles
Recent advancements in architected materials enable their extensive applications in energy absorption and impact dissipation, etc. However, traditional design methodologies, including analytical prediction or numerical optimization, are not capable of capturing and replicating the full dynamic responses, attributed to limitations in multiple design objectives, nonlinear behaviors, and intrinsic trial-and-error design process. Herein, we exploited the artificial intelligence approach and established a machine learning based design framework to inversely create metamaterials that achieve target dynamic responses across a wide range of strain rates. Additionally, we developed a revised Molecular Dynamic simulation procedure to replace precisely evaluate the dynamic response of the lattice, which significantly reduces the time span of simulating each design from hours to minutes. Our work provides a rapid architected material design approach for future product design, targeting optimal performance in diverse application scenarios.