The Crystallization of Disordered Materials under Shock Is Governed by Their Network Topology.

When the shock load is applied, materials experience incredibly high temperature and pressure conditions on picosecond timescales, usually accompanied by remarkable physical or chemical phenomena. Understanding the underlying physics that governs the kinetics of shocked materials is of great importance for both physics and materials science. Here, combining experiment and large-scale molecular dynamics simulation, the ultrafast nanoscale crystal nucleation process in shocked soda-lime silicate glass is investigated. By adopting topological constraints theory, this study finds that the propensity of nucleation is governed by the connectivity of the atomic network. The densification of local networks, which appears once the crystal starts to grow, results in the underconstrained shell around the crystal and prevents further crystallization. These results shed light on the nanoscale crystallization mechanism of shocked materials from the viewpoint of topological constraint theory.

Beyond the Average: Spatial and Temporal Fluctuations in Oxide Glass-Forming Systems.

Atomic structure dictates the performance of all materials systems; the characteristic of disordered materials is the significance of spatial and temporal fluctuations on composition-structure-property-performance relationships. Glass has a disordered atomic arrangement, which induces localized distributions in physical properties that are conventionally defined by average values. Quantifying these statistical distributions (including variances, fluctuations, and heterogeneities) is necessary to describe the complexity of glass-forming systems. Only recently have rigorous theories been developed to predict heterogeneities to manipulate and optimize glass properties. This article provides a comprehensive review of experimental, computational, and theoretical approaches to characterize and demonstrate the effects of short-, medium-, and long-range statistical fluctuations on physical properties (e.g., thermodynamic, kinetic, mechanical, and optical) and processes (e.g., relaxation, crystallization, and phase separation), focusing primarily on commercially relevant oxide glasses. Rigorous investigations of fluctuations enable researchers to improve the fundamental understanding of the chemistry and physics governing glass-forming systems and optimize structure-property-performance relationships for next-generation technological applications of glass, including damage-resistant electronic displays, safer pharmaceutical vials to store and transport vaccines, and lower-attenuation fiber optics. We invite the reader to join us in exploring what can be discovered by going beyond the average.

Predicting Fracture Propensity in Amorphous Alumina from Its Static Structure Using Machine Learning.

Thin films of amorphous alumina (a-Al2O3) have recently been found to deform permanently up to 100% elongation without fracture at room temperature. If the underlying ductile deformation mechanism can be understood at the nanoscale and exploited in bulk samples, it could help to facilitate the design of damage-tolerant glassy materials, the holy grail within glass science. Here, based on atomistic simulations and classification-based machine learning, we reveal that the propensity of a-Al2O3 to exhibit nanoscale ductility is encoded in its static (nonstrained) structure. By considering the fracture response of a series of a-Al2O3 systems quenched under varying pressure, we demonstrate that the degree of nanoductility is correlated with the number of bond switching events, specifically the fraction of 5- and 6-fold coordinated Al atoms, which are able to decrease their coordination numbers under stress. In turn, we find that the tendency for bond switching can be predicted based on a nonintuitive structural descriptor calculated based on the static structure, namely, the recently developed "softness" metric as determined from machine learning. Importantly, the softness metric is here trained from the spontaneous dynamics of the system (i.e., under zero strain) but, interestingly, is able to readily predict the fracture behavior of the glass (i.e., under strain). That is, lower softness facilitates Al bond switching and the local accumulation of high-softness regions leads to rapid crack propagation. These results are helpful for designing glass formulations with improved resistance to fracture.

The energy landscape governs ductility in disordered materials.

Based on their structure, non-crystalline phases can fail in a brittle or ductile fashion. However, the nature of the link between structure and propensity for ductility in disordered materials has remained elusive. Here, based on molecular dynamics simulations of colloidal gels and silica glasses, we investigate how the degree of structural disorder affects the fracture of disordered materials. As expected, we observe that structural disorder results in an increase in ductility. By applying the activation-relaxation technique (an open-ended saddle point search algorithm), we demonstrate that the propensity for ductility is controlled by the topography of the energy landscape. Interestingly, we observe a power-law relationship between the particle non-affine displacement upon fracture and the average local energy barrier. This reveals that the dynamics of the particles upon fracture is encoded in the static energy landscape, i.e., before any load is applied. This relationship is shown to apply to several classes of non-crystalline materials (oxide and metallic glasses, amorphous solid, and colloidal gels), which suggests that it may be a generic feature of disordered materials.

A Mathematical Model of the Expansion Evolution of Magnesium Oxide in Mass Concrete Based on Hydration Characteristics.

The low swelling property of magnesium oxide concrete is a significant feature that can be used to control the cracking of mass concrete. Based on the characteristics of the chemical reaction, this work proposes a coupled hydro-thermo-mechanical model that can be implemented with the finite element method for predicting the autogenous volumetric deformation of magnesium concrete. By introducing the degree of the hydration reaction of magnesia and the degree of the hydration reaction of cementitious materials as intermediate variables of the chemical reaction system, a prediction model of the concrete temperature and chemical fields is established, and using this model, the effect of the temperature on the reaction rate can be considered in real time. In addition, by combining the relationship between the degree of the hydration reaction of magnesium oxide and the comprehensive expansion of concrete, a mathematical model for calculating the expansion stress of magnesia concrete was established. The algorithms were derived by mathematical equations, and the simulation results were compared to the experimental temperature and autogenous volumetric strain curves, which showed that the hydration model provides a relatively high accuracy. The model was also applied to an arch dam, and the coupled thermo-chemical-mechanical responses of mass concrete during construction were investigated. Simulation results show that the increase in temperature (hydration of cementitious material) and expansion volumetric deformation (hydration of MgO) of the concrete on the upstream and downstream surfaces lags obviously behind that of the inner regions. Quantitative analysis for differences of internal and external expansion is worthy of further attention and study on a basis of further experimental data as well as monitored data.

Atomic Dislocations and Bond Rupture Govern Dissolution Enhancement under Acoustic Stimulation.

By focusing the power of sound, acoustic stimulation (i.e., often referred to as sonication) enables numerous "green chemistry" pathways to enhance chemical reaction rates, for instance, of mineral dissolution in aqueous environments. However, a clear understanding of the atomistic mechanism(s) by which acoustic stimulation promotes mineral dissolution remains unclear. Herein, by combining nanoscale observations of dissolving surface topographies using vertical scanning interferometry, quantifications of mineral dissolution rates via analysis of solution compositions using inductively coupled plasma optical emission spectrometry, and classical molecular dynamics simulations, we reveal how acoustic stimulation induces dissolution enhancement. Across a wide range of minerals (Mohs hardness ranging from 3 to 7, surface energy ranging from 0.3 to 7.3 J/m2, and stacking fault energy ranging from 0.8 to 10.0 J/m2), we show that acoustic fields enhance mineral dissolution rates (reactivity) by inducing atomic dislocations and/or atomic bond rupture. The relative contributions of these mechanisms depend on the mineral's underlying mechanical properties. Based on this new understanding, we create a unifying model that comprehensively describes how cavitation and acoustic stimulation processes affect mineral dissolution rates.

Bulk Metallic Glasses' Response to Oscillatory Stress Is Governed by the Topography of the Energy Landscape.

When subjected to cyclic loading, bulk metallic glasses tend to exhibit fatigue-induced damage. Although fatigue is a key limitation of metallic glasses, its atomic origin remains elusive. Here, based on molecular dynamics simulations, we investigate the response of metallic glasses prepared with varying cooling rates to oscillatory stress. We find that fatigue manifests itself as an accumulation of residual strain, which results from some nonaffine displacement of the atoms. Such local reorganizations are promoted under a high cooling rate. Importantly, we demonstrate that the fatigue-induced dynamics of the atoms is encoded in the topography of the static energy landscape, i.e., before any load is applied.

Long-term creep deformations in colloidal calcium-silicate-hydrate gels by accelerated aging simulations.

When subjected to a sustained load, jammed colloidal gels can feature some delayed viscoplastic creep deformations. However, due to the long timescale of creep (up to several years), its modeling and, thereby, prediction has remained challenging. Here, based on mesoscale simulations of calcium-silicate-hydrate gels (CSH, the binding phase of concrete), we present an accelerated simulation method-based on stress perturbations and overaging-to model creep deformations in CSH. Our simulations yield a very good agreement with nanoindentation creep tests, which suggests that concrete creep occurs through the reorganization of CSH grains at the mesoscale. We show that the creep of CSH exhibits a logarithmic dependence on time-in agreement with the free-volume theory of granular physics. Further, we demonstrate the existence of a linear regime, i.e., wherein creep linearly depends on the applied load-which establishes the creep modulus as a material constant. These results could offer a new physics-based basis for nanoengineering colloidal gels featuring minimal creep.