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Register a new userEnhancing the bond strength in meta-crystal lattice of architected materials
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Architected materials produced by powder bed fusion metal additive manufacturing technique offer realization of complex structural hierarchies that mimic the principles of crystal plasticity while still being ultralight-weight, though suffering from deep-rooted multiscale defects including microstructural heterogeneity caused by the complex thermo-mechanical transients in the melt pool. Here we manufacture meta-crystal 316L stainless steel microlattice structures by selective laser melting process for utilizing the strain localization mechanism in bulk structures akin to dislocation slip mediated plasticity. The build angle was observed to be the primary influencer of defects generated and the presence of inherent voids was the major drawback that would undermine their structural performance as mechanical metamaterials. However, other defects in the form of spatially correlated dislocation networks and micro-segregated cellular substructures overcome the strength-ductility trade-off and render the bulk structures comparable to other engineering materials including conventional steels. By exploiting this intrinsic strengthening mechanism, the bond strength of meta-crystals (i.e. strut strength) can be enhanced (or controlled) on top of employing hardening principles of metallurgy to design materials with desired properties.
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Metamaterials achieve unprecedented properties from designed architected structures. However, they are often constructed from a single repeating building block that exhibits monotonic shape changes with single degree of freedom, thereby leading to specific spatial forms and limited reconfigurability. Here we introduce a transformable three-dimensional modular kirigami with multiple degrees of freedom that could reconfigure into versatile distinct daughter building blocks. Consequently, the combinatorial and spatial modular assembly of these building blocks could create a wealth of reconfigurable architected materials with diverse structures and unique properties, including reconfigurable 1D periodic column-like materials with bifurcated states, 2D lattice-like architected materials with phase transition of chirality, as well as 3D quasiperiodic yet frustration-free multilayered architected materials in a long-range order with programmable deformation modes. Our strategy opens an avenue to design a new class of modular reconfigurable metamaterials that are reprogrammable and reusable for potential multifunctionality in architectural, phononic, mechanical, and robotic applications.
Lattice constants such as unit cell edge lengths and plane angles are important parameters of the periodic structures of crystal materials. Predicting crystal lattice constants has wide applications in crystal structure prediction and materials property prediction. Previous work has used machine learning models such as neural networks and support vector machines combined with composition features for lattice constant prediction and has achieved a maximum performance for cubic structures with an average $R^2$ of 0.82. Other models tailored for special materials family of a fixed form such as ABX3 perovskites can achieve much higher performance due to the homogeneity of the structures. However, these models trained with small datasets are usually not applicable to generic lattice parameter prediction of materials with diverse compositions. Herein, we report MLatticeABC, a random forest machine learning model with a new descriptor set for lattice unit cell edge length ($a,b,c$) prediction which achieves an R2 score of 0.979 for lattice parameter $a$ of cubic crystals and significant performance improvement for other crystal systems as well. Source code and trained models can be freely accessed at https://github.com/usccolumbia/MLatticeABC
Kirigami, art of paper cutting, enables two-dimensional sheets transforming into unique shapes which are also hard to reshape once with prescribed cutting patterns. Rare kirigami designs manipulate cuts on three-dimensional objects to compose periodic structures with programmability and/or re-programmability. Here, we propose a new class of three-dimensional modular kirigami by introducing cuts on cuboid-shaped objects, based on which constructing two quasi-three-15 dimensional architected kirigamis with even-flat structural form. We demonstrate the proposed architected kirigamis are with rich mobilities triggered by kinematic bifurcations inherited from their composed modular kirigami, and can undergo living-matter-like metamorphosis evolving into miscellaneous transformable three-dimensional architectures and even a pluripotent platform capable of being re-programmed into curvature different surfaces through inverse design. Such 20 metamorphic structures could find broad applications in reconfigurable metamaterials, transformable robots and architectures.
We study thermoelectric transport at low temperatures in correlated Kondo insulators, motivated by the recent observation of a high thermoelectric figure of merit(ZT) in $FeSb_2$ at $T sim 10 K$. Even at room temperature, correlations have the potential to lead to high ZT, as in $YbAl_3$, one of the most widely used thermoelectric metals. At low temperature correlation effects are especially worthy of study because fixed band structures are unlikely to give rise to the very small energy gaps $E_g sim 5 kT$ necessary for a weakly correlated material to function efficiently at low temperature. We explore the possibility of improving the thermoelectric properties of correlated Kondo insulators through tuning of crystal field and spin-orbit coupling and present a framework to design more efficient low-temperature thermoelectrics based on our results.
As the energy problem becomes more prominent, researches on thermoelectric (TE) materials have deepened over the past few decades. Low thermal conductivity enables thermoelectric materials better thermal conversion performance. In this study, based on the first principles and phonon Boltzmann transport equation, we studied the thermal conductivities of single-layer WSe2 under several defect conditions using density functional theory (DFT) as implemented in the Vienna Ab-initio Simulation Package (VASP). The lattice thermal conductivities of WSe2 under six kinds of defect states, i.e., PS, SS-c, DS-s, SW-c, SS-e, and DS-d, are 66.1, 41.2, 39.4, 8.8, 42.1, and 38.4 W/(m2K), respectively at 300 K. Defect structures can reduce thermal conductivity up to 86.7% (SW-c) compared with perfect structure. The influences of defect content, type, location factors on thermal properties have been discussed in this research. By introducing atom defects, we can reduce and regulate the thermal property of WSe2, which should provide an interesting idea for other thermoelectric materials to gain a lower thermal conductivity.
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