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Abstract Architected materials design across orders of magnitude length scale intrigues exceptional mechanical responses nonexistent in their natural bulk state. However, the so‐termed mechanical metamaterials, when scaling bottom down to the atomistic or microparticle level, remain largely unexplored and conventionally fall out of their coarse‐resolution, ordered‐pattern design space. Here, combining high‐throughput molecular dynamics (MD) simulations and machine learning (ML) strategies, some intriguing atomistic families of disordered mechanical metamaterials are discovered, as fabricated by melt quenching and exemplified herein by lightweight‐yet‐stiff cellular materials featuring a theoretical limit of linear stiffness–density scaling, whose structural disorder—rather than order—is key to reduce the scaling exponent and is simply controlled by the bonding interactions and their directionality that enable flexible tunability experimentally. Importantly, a systematic navigation in the forcefield landscape reveals that, in‐between directional and non‐directional bonding such as covalent and ionic bonds, modest bond directionality is most likely to promotes disordered packing of polyhedral, stretching‐dominated structures responsible for the formation of metamaterials. This work pioneers a bottom‐down atomistic scheme to design mechanical metamaterials formatted disorderly, unlocking a largely untapped field in leveraging structural disorder in devising metamaterials atomistically and, potentially, generic to conventional upscaled designs. 

Abstract Lithium aluminoborate glasses have recently been found to feature high resistance to crack initiation during indentation, but suffer from relatively low hardness and chemical durability. To further understand the mechanical properties of this glass family and their correlation with the network structure, we here study the effect of adding SiO₂to a 25Li₂O–20Al₂O₃–55B₂O₃glass on the structure and mechanical properties. Addition of silica increases the average network rigidity, but meanwhile its open tetrahedral structure decreases the atomic packing density. Consequently, we only observe a minor increase in hardness and glass transition temperature, and a decrease in Poisson's ratio. The addition of SiO₂, and thus removal of Al₂O₃and/or B₂O₃, also makes the network less structurally adaptive to applied stress, since Al and B easily increase their coordination number under pressure, while this is not the case for Si under modest pressures. As such, although the silica‐containing networks have more free volume, they cannot densify more during indentation, which in turn leads to an overall decrease in crack resistance upon SiO₂addition. Our work shows that, although pure silica glass has very high glass transition temperature and relatively high hardness, its addition in oxide glasses does not necessarily lead to significant increase in these properties due to the complex structural interactions in mixed network former glasses and the competitive effects of free volume and network rigidity. 

Abstract Nanoindentation is a widely used method to probe the mechanical properties of glasses. However, interpreting glasses’ response to nanoindentation can be challenging due to the complex nature of the stress field under the indenter tip and the lack ofin situcharacterization techniques. Here, we present a numerical model describing the nanoindentation of an archetypical soda‐lime silicate window glass by means of peridynamic simulations. We show that, although it does not capture shear flow and permanent densification, peridynamics exhibits a good agreement with experimental nanoindentation data and offers a direct access to the stress field forming under the indenter tip. 

Abstract Germanate glasses are of particular interest for their excellent optical properties as well as their abnormal structural changes that appear with the addition of modifiers, giving rise to the so‐calledgermanate anomaly. This anomaly refers to the nonmonotonic compositional scaling of properties exhibited by alkali germanate glasses and has been studied with various spectroscopy techniques. However, it has been difficult to understand its atomic scale origin, especially since the germanium nucleus is not easily observed by nuclear magnetic resonance. To gain insights into the mechanisms of the germanate anomaly, we have constructed a structural model using statistical mechanics and topological constraint theory to provide an accurate prediction of alkali germanate glass properties. The temperature onsets for the rigid bond constraints are deduced from in situ Brillouin light scattering, and the number of constraints is shown to be accurately calculable using statistical methods. The alkali germanate model accurately captures the effect of the germanate anomaly on glass transition temperature, liquid fragility, and Young's modulus. We also reveal that compositional variations in the glass transition temperature and Young's modulus are governed by the O–Ge–O angular constraints, whereas the variations in fragility are governed by the Ge–O radial constraints. 

Abstract Topological constraint theory (TCT) has enabled the prediction of various properties of oxide glasses as a function of their composition and structure. However, the robust application of TCT relies on accurate knowledge of the network structure and topology. Here, based on classical molecular dynamics simulations, we derive a fully analytical model describing the topology of the calcium aluminosilicate [(CaO)_x(Al₂O₃)_y(SiO₂)_1−x−y, CAS] ternary system. This model yields the state of rigidity (flexible, isostatic, or stressed‐rigid) of CAS systems as a function of composition and temperature. These results reveal the existence of correlations between network topology and glass‐forming ability. This study suggests that glass‐forming ability is encoded in the network topology of the liquid state rather than that of the glassy state.