Challenges and opportunities in atomistic simulations of glasses: a review

Atomistic modeling and simulations have been pivotal in our understanding of the glassy state. Indeed, atomistic modeling offers direct access to the structure and dynamics of atoms in glasses—which is typically hidden from conventional experiments. Simulations also offer a more economical, faster alternative to systematic experiments to decode composition-property relationships and accelerate the discovery of new glasses with desirable properties and functionalities. However, the atomistic modeling of glasses remains plagued by a series of challenges, e.g., high computational cost, limited accessible timescale, lack of accurate interatomic forcefields, etc. These challenges often result in the existence of discrepancies between simulation and experimental data, thereby limiting the predictive power of atomistic modeling. Here, we review recent accomplishments and remaining challenges facing the atomistic modeling of glasses. We discuss future opportunities offered by the seamless integration of simulations, knowledge, experiments, and machine learning in advancing glass modeling to a new era

Challenges and opportunities in atomistic simulations of glasses: a review

Atomistic modeling and simulations have been pivotal in our understanding of the glassy state. Indeed, atomistic modeling offers direct access to the structure and dynamics of atoms in glasses—which is typically hidden from conventional experiments. Simulations also offer a more economical, faster alternative to systematic experiments to decode composition-property relationships and accelerate the discovery of new glasses with desirable properties and functionalities. However, the atomistic modeling of glasses remains plagued by a series of challenges, e.g., high computational cost, limited accessible timescale, lack of accurate interatomic forcefields, etc. These challenges often result in the existence of discrepancies between simulation and experimental data, thereby limiting the predictive power of atomistic modeling. Here, we review recent accomplishments and remaining challenges facing the atomistic modeling of glasses. We discuss future opportunities offered by the seamless integration of simulations, knowledge, experiments, and machine learning in advancing glass modeling to a new era

Dissolution Amplification by Resonance and Cavitational Stimulation at Ultrasonic and Megasonic Frequencies

Acoustic stimulation offers a green pathway for the extraction of valuable elements such as Si, Ca, and Mg via solubilization of minerals and industrial waste materials. Prior studies have focused on the use of ultrasonic frequencies (20-40 kHz) to stimulate dissolution, but mega sonic frequencies (≥1 MHz) offer benefits such as matching of the resonance frequencies of solute particles and an increased frequency of cavitation events. Here, based on dissolution tests of a series of minerals, it is found that dissolution under resonance conditions produced dissolution enhancements between 4x-to-6x in Si-rich materials (obsidian, albite, and quartz). Cavitational collapse induced by ultrasonic stimulation was more effective for Ca- and Mg-rich carbonate precursors (calcite and dolomite), exhibiting a significant increase in the dissolution rate as the particle size was reduced (i.e. available surface area was increased), resulting in up to a 70x increase in the dissolution rate of calcite when compared to unstimulated dissolution for particles with d50\u3c 100 μm. Cavitational collapse induced by mega sonic stimulation caused a greater dissolution enhancement than ultrasonic stimulation (1.5x vs 1.3x) for amorphous class F fly ash, despite its higher Si content because the hollow particle structure was susceptible to breakage by the rapid and high number of lower-energy mega sonic cavitation events. These results are consistent with the cavitational collapse energy following a normal distribution of energy release, with more cavitation events possessing sufficient energy to break Ca-O and Mg-O bonds than Si-O bonds, the latter of which has a bond energy approximately double the others. The effectiveness of ultrasonic dissolution enhancement increased exponentially with decreasing stacking fault energy (i.e., resistance to the creation of surface faults such as pits and dislocations), while, in turn, the effectiveness of mega sonic dissolution increased linearly with the stacking fault energy. These results give new insights into the use of acoustic frequency selections for accelerating elemental release from solutes by the use of acoustic perturbation

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

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

The Coupling and Coordinated Development from Urban Land Using Benefits and Urbanization Level: Case Study from Fujian Province (China)

In recent years, urbanization has been developing rapidly. However, it is also accompanied by land management problems, such as low land use efficiency. In this research, we manage to explore the temporal and spatial evolution laws as well as characteristics of the coupling and coordinated development between urbanization and land use benefits. Through this, it is possible for us to provide policy recommendations for the sustainable development of the urbanization in Fujian Province. In this study, we take prefecture-level municipal districts and county-level cities in Fujian as the research subject. We construct an index system, based on data in 2002, 2005, 2010, 2015, and 2017, to evaluate the urban land use benefits and urbanization. Besides, we leverage the Gini coefficient weighting method to give weight to each index and calculate the value of its benefits. Moreover, it is the relative development degree and the coupling coordination degree model that we comprehensively leverage to study the spatiotemporal evolution law of the coupling coordination degree (CCD). The results show that: (1) Urban land use benefits and urbanization level are positively correlated with the regional administrative level and economic development status; (2) The CCD of urban land use benefits and urbanization level in various regions of Fujian is still low. However, the overall development direction is good; (3) From the perspective of spatial distribution, the CCD owns a “center-periphery” pattern that is based on the law of diminishing CCD power from three central cities of Fuzhou, Xiamen, and Sanming. Consequently, it requires governments to take action. Firstly, they should promote the intensive land use in the urbanization process. Meanwhile, they should also pay attention to ecological environment protection. Besides, it is recommendable to give full play to the radiating and leading effect of central cities on surrounding ones. Finally, they are required to provide appropriate policies and resource support to peripheral cities