Structural heterogeneity governing deformability of metallic glass
Not Available
36 MATERIALS SCIENCE↗
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Results for “glass structure”
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Molecular Orientation for Vapor-Deposited Organic Glasses Follows Rate-Temperature Superposition: The Case of Posaconazole
The anisotropic properties of organic glasses produced by physical vapor deposition (PVD) depend upon substrate temperature and deposition rate. In recent work, it was shown for a liquid crystalline system that the anisotropic structure of the glass was controlled by a single combined variable as indicated by the observation of deposition rate-substrate temperature superposition (RTS). Here we test the utility of RTS for posaconazole, a molecule that does not form liquid crystals. We prepare glasses of posaconazole utilizing a range of deposition rates covering 2 orders of magnitude and an 18 K range in substrate temperature. We characterize the glasses using ellipsometry and X-ray scattering. Consistent with RTS, we find that decreasing the deposition rate has the same effect upon molecular orientation as increasing the substrate temperature during deposition. Thus, RTS can be used to predict and control the structure of glasses prepared at a wide range of deposition conditions. We use RTS to infer a characteristic time for molecular reorientation at the surface of posaconazole.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Comparative structural investigations of nuclear waste glass alteration layers and sol-gel synthesized aerogels
Not Available
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Discovering exceptionally hard and wear-resistant metallic glasses by combining machine-learning with high throughput experimentation
Lack of crystalline order in amorphous alloys, commonly called metallic glasses (MGs), tends to make them harder and more wear-resistant than their crystalline counterparts. However, finding inexpensive MGs is daunting; finding one with enhanced wear resistance is a further challenge. Relying on machine learning (ML) predictions of MGs alone requires a highly precise model; however, incorporating high-throughput (HiTp) experiments into the search rapidly leads to higher performing materials even from moderately accurate models. Here, we exploit this synergy between ML predictions and HiTp experimentation to discover new hard and wear-resistant MGs in the Fe–Nb–B ternary material system. Several of the new alloys exhibit hardness greater than 25 GPa, which is over three times harder than hardened stainless steel and only surpassed by diamond and diamond-like carbon. This ability to use less than perfect ML predictions to successfully guide HiTp experiments, demonstrated here, is especially important for searching the vast Multi-Principal-Element-Alloy combinatorial space, which is still poorly understood theoretically and sparsely explored experimentally.
36 MATERIALS SCIENCE↗
Boron Coordination in Multicomponent Glasses: Analytical Models and Machine Learning With Uncertainty
Borosilicate glasses are extensively used in a variety of applications from kitchenware to nuclear waste immobilization due to the strong network formed by the Si-O-B bond that makes it resistant to chemical corrosion and gives it a low thermal expansion. Boron, however, exists in both trigonal BO3 and tetrahedral BO4 bonds in glass systems, which impacts the chemical durability and thermal resistance of the glass, amongst other properties. Boron coordination (N4), or the ratio of the amount of BO4 to BO3 within a glass, may aid in predicting these properties but is difficult to derive without experimental data due to the complexity of impacts from varied glass compositions and processing factors. For this reason, compositional models have been developed to predict boron coordination, but the models typically include a limited number of glass components. To help fill this gap in the models, in this work, a diverse multicomponent glass dataset of 809 glasses is compiled from a literature search, and then a number of analytical and machine learning (ML) models are trained on the dataset. Previously developed modified Bernstein and modified Du Stebbins analytical models were fitted to update parameters with the new dataset. Then, partially Bayesian neural networks, Gaussian process regressor, and heteroskedastic deterministic neural networks were evaluated. The ML models examined all have different strategies to overcome the potential for overfitting as a result of a limited training dataset, and return results that account for model uncertainty, which can be valuable for understanding model reliability. For the first time, cooling rate is introduced as an input parameter for ML models, showing consistent improvements in performance and solidifying the importance of including parameters outside of composition alone for N4 prediction. The machine learning models examined here show promise in accurate predictions of boron coordination in borosilicate glasses, all achieving R2 values of 0.91.
boron coordination↗
Spectroscopical Evaluation of Shear-induced Chemical Changes and Structural Transformations in Bulk Metallic Glass (BMG).
Abstract not provided.
lien, Hsu-Ming↗
Synthesis of Free-Standing Pd-Ni-P Metallic Glass Nanoparticles with Durable Medium-Range Ordered Structure for Enhanced Electrocatalytic Properties
Topologically disordered metallic glass nanoparticles (MGNPs) with highly active and tailorable surface chemistries have immense potential for functional uses. The synthesis of free-standing MGNPs is crucial and intensively pursued because their activity strongly depends on their exposed surfaces. Herein, a novel laser-evaporated inert-gas condensation method is designed and successfully developed for synthesizing free-standing MGNPs without substrates or capping agents, which is implemented via pulse laser-induced atomic vapor deposition under an inert helium atmosphere. In this way, the metallic atoms vaporized from the targets collide with helium atoms and then condense into short-range-order (SRO) clusters, which mutually assemble to form the MGNPs. Using this method, free-standing Pd 40 Ni 40 P 20 MGNPs with a spherical morphology are synthesized, which demonstrates satisfactory electrocatalytic activity and durability in oxygen reduction reactions. Moreover, local structure investigations using synchrotron pair distribution function techniques reveal the transformation of SRO cluster connection motifs of the MGNPs from face-sharing to edge-sharing modes during cyclic voltammetry cycles, which enhances the electrochemical stability by blocking crystallization. Further, this approach provides a general strategy for preparing free-standing MGNPs with high surface activities, which may have widespread functional applications
36 MATERIALS SCIENCE↗
Viscosity-temperature relation based on the evolution of medium-range structures of silica
The viscosity of glass is the most important technological property to glass manufactures and various applications. Practically, finding an accurate equation to express the glass viscosity behavior in the entire glass transition temperature range is tremendously challenge because it spans more than ten orders of magnitude. After a brief review of existing empirical viscosity equations, this work focuses on the correlating silica viscosity behavior with the evolution of glass medium-range structure, based on the recently proposed nanoflake model. From this new model, a new equation is constructed, which correctly describes the Arrhenius-type behavior of silica viscosity η above the melting temperature Tm, and non-Arrhenius-type behavior from Tm to a critical temperature Tc. At temperature lower than Tc, the equation predicts Arrhenius-type behavior again for the viscous flow with increased activation energy. The new equation agrees with experimental data in the entire temperature spanned from extremely high to extremely low. Furthermore, the application of the new equation is shown to extend to sodium silicate glasses as well.
36 MATERIALS SCIENCE↗
Machine learning bridges local static structure with multiple properties in metallic glasses
A long-standing challenge in the metallic glass (MG) community has been how to quantitatively gauge the influence of the intricate local packing environment on the response (such as the propensity for atomic rearrangement) of the atomic configuration to external stimuli. Here we establish this structure–property relation by representing the complex amorphous structure using a single, flexibility-orientated structural quantity. This structural flexibility (SF) couples to a bona fide structural representation, the pair distribution function (PDF) of individual atoms, through a weighting function that reflects what matters in the static atomic configuration to dynamic responses. Machine learning is used, employing microscopic flexibility volume as the supervisory signal, to establish via direct regression an optimized weighting vector, which is proven robust for all quenching rates, deformation conditions, and different compositions in a given (e.g., Cu x Zr 100-x ) alloy system. Additionally, the SF is evaluated solely from the particle positions (PDF), for any structure variation, from the atomic scale up to sample average. Strong correlations are demonstrated between SF and a broad range of properties, including vibrational, diffusional, as well as elastic and plastic relaxation responses.
36 MATERIALS SCIENCE↗
Tailoring Cu-Zr gradient nanoglass structures: Influence of nanoparticle size and cooling rates on glass-glass interfaces
The study of gradient nanoglasses (GNGs) has gained attention due to their unique mechanical properties and potential applications in advanced materials. This study employs molecular dynamics simulations to synthesize a GNG using Cu-Zr metallic glass nanoparticles (NPs) sized from 3 to 15 nm. The NPs were produced by melting and quenching metallic clusters at a relatively slow quench rate of 10 9 K/s. The synthesis of GNG is elucidated along with the characterization of its heterogeneous metallic glass nanostructure. A seamless GNG structure is formed through cold compression of Cu 64 Zr 36 amorphous NPs of varying sizes. The influence of NP size on the GNG structure is investigated, utilizing deeply relaxed NPs, which exhibit a characteristic Cu segregation pattern on their surfaces. The results highlight an increase in structural heterogeneity due to heterogeneous mass transport and the development of local composition and density variations caused by Cu segregation at glass-glass interfaces (GGIs). A reduction in NP size is correlated with decreased Cu atomic displacements and local density at GGIs, suggesting that larger NPs may produce stronger GGIs. This research presents a novel methodology for synthesizing heterogeneous metallic glasses, demonstrating the capacity to control and customize nanostructure heterogeneity through the manipulation of NP sizes and cooling rates. Furthermore, these findings enhance our understanding of structural evolution during nanoglass synthesis and lay the foundation for further exploration in nanomaterial synthesis and characterization.
36 MATERIALS SCIENCE↗
The Origin of Anomalous Density Behavior of Silica Glass
The anomalous density–temperature relationship of vitreous silica with low hydroxyl content is explained by the formation of medium-range ordering structure in the glass transition process. The ordered medium-range structure has the shape of a “nanoflake” and consists of two layers of SiO 4 tetrahedra, bonded by O atoms located in the middle of the structure. The nanoflakes interact with their surrounding structures through both covalent chemical bonds and van der Waals bonds. In the formation of the van der Waals bonds, the orientation of SiO 4 tetrahedra can change, which results in an increase in distance between the nanoflakes and their surrounding structures. Thus, there is a slight volume enlargement associated with the formation of nanoflakes. Since the nanoflakes’ formation starts at a temperature near 1480 °C, and the population of the nanoflakes grows continuously as temperature decreases until about 950 °C, the bulk volume of silica glass increases in the temperature range from about 1480 °C to 950 °C. Therefore, the density anomaly of silica glass can be explained as a byproduct of forming of medium-range ordering structure in the silica glass transition.
36 MATERIALS SCIENCE↗
Anomalously strong viscosity behavior in mixed oxy-sulfide Na 4 P 2 S 7-x O x invert glasses
In this paper, the first observations have been made of anomalously strong viscosity behavior and correspondingly strong bulk glass formation and resistance to crystallization in a melt quenched (MQ) prepared series of invert, modifier content greater than the glass former content, mixed oxy-sulfide Na 4 P 2 S 7-x O x , 0 ≤ x ≤ 5, (NaPSO) glasses. We find that these glasses even with 67 mole % modifier, Na 2 S, and only 33 mole% glass former P 2 S 5-x O x , exhibit a calorimetric fragility index, m cal , as small as 29 compared to typical values of ~ 60 to 80 for alkali silicate glasses with > 50 mole% SiO 2 and the theoretical minimum m cal of ~ 15. The m cal values were converted to kinetic viscosity fragility, m vis , values and used with the measured glass transition temperatures, T g s, to produce viscosity curves for the glasses using the Mauro-Yue-Ellison-Gupta-Allan (MYEGA) model. The viscosity of the glass with a minimum m cal value of x = 2.5 was then shown to exhibit a viscosity that was as strong as, and for some compositions stronger than, the viscosity of alkali aluminosilicate glasses which have three dimensional network structures compared to the one dimensional chain structures observed in these MOS invert glasses. Consistent with these small values of fragility indices and therefore predicted higher viscosity above the glass transition temperature, T g , in the supercooled liquid regime, these glasses are also particularly resistant to crystallization. For example, the x = 2.5 glass composition exhibits a crystallization temperature, T C , more than 150K above its T g . We find that the calorimetric fragility of these glasses varies systematically with the extent of network forming bridging oxygens (BOs) in the glasses. The structural change caused by incrementally replacing sulfur with oxygen has been found to have consistent, large effects on the thermal properties.
36 MATERIALS SCIENCE↗
Hydration and reaction mechanisms on sodium silicate glass surfaces from molecular dynamics simulations with reactive force fields
Recent development of reactive force fields have enabled molecular dynamics simulations of interactions between silicate glasses and water at the atomistic scale. While multicomponent silicate glasses encompass a wide variety of compositions and properties, one common structural feature in these glasses is the combination of the network structure that is made up of silica tetrahedra linked through corner sharing interspersed with network modifiers like alkali and alkaline-earth ions that break up the Si–O–Si linkages by forming nonbridging oxygen. In reactions with water, ion exchange between alkali ions in the glass and proton or hydronium in the solution, as well as hydrolysis reaction of the Si–O–Si linkages and subsequent silanol formation, is observed and well documented. Furthermore, we have used a set of recently developed reactive force field to investigate the reactions between water and the surfaces of silica and sodium silicate glasses of different compositions for reactions up to 8 nanoseconds. Our results indicate sodium leaching into water and diffusion of water molecules up to 25 Å into the glass surface. We examined the structural and compositional changes inside the glass and around the diffused ions and use these to explain the rates of silanol formation at the surface. We also observed proton transport in the glass which has an indirect influence on the silanol formation rates. While the surface of the glass was rough to start with, it undergoes further modification into a hydrated gel-like structure in the glass for up to 5 Å in the higher alkali containing glasses. It was found that the leached sodium ions remain close to the interface and that fragments of silicate network from the surface is capable of dislodging from the bulk glass and enter the aqueous solution. These simulations thus provide insights into the formation and structure of an alteration layers commonly observed in multicomponent silicate glasses corroded in aqueous solutions.
36 MATERIALS SCIENCE↗
Network structure in alteration layer of boroaluminosilicate glass formed by aqueous corrosion
Exogenously-added LiCl has been shown to slightly accelerate the corrosion rate of a boroaluminosilicate glass called International Simple Glass (ISG) in aqueous solutions over forward- and residual-rate regimes, while KCl and CsCl impede. To understand the effect of exogenously added electrolytes on resulting hydrous species and the network structure of alteration layers, infrared spectroscopy was implemented. It was found that the fraction of molecular water relative to the surface-bound hydroxyl species is lower in the KCl and CsCl conditions compared to the LiCl and pure water conditions. An approximation for the spectral features of the thin surface films from an experimentally-obtained specular-reflectance infrared (SR-IR) spectrum was proposed; results indicate no significant difference in the Si-O bonding network of the alteration layers formed in the presence of exogenously added LiCl, KCl and CsCl. Furthermore, the observed change in corrosion rates might be linked to the relative abundance of molecular water species in the porous network, rather than the silicate bonding structure.
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Structure–property relations of sodium iron phosphate nuclear waste glasses: Effects of iron redox ratio and glass composition
Iron phosphate glasses, known for their exceptional chemical durability and potential applicability in nuclear waste management, have gained significant attention over the years. The structures of these glasses are complicated by the coexistence of Fe 3+ and Fe 2+ , which plays a crucial role in determining their structures and properties. Here, this work uses molecular dynamics simulations to study the structural changes in Na 2 O–Fe 2 O 3 –P 2 O 5 glasses with varying glass composition and Fe 2+ /Fe 3+ redox ratio. It was found that the redox ratio and modifier contents significantly affected the short-range and medium-range orders in the glasses. Significant changes in the local environments around P 5+ and Fe 3+ were observed, as reflected by the bond distances and coordination numbers. Na + cations are found to preferentially associate with Fe 3+ (rather than Fe 2+ ), whereas Fe 2+ has stronger association with P 5+ than Na + , confirming the structural role of Fe 2+ as a glass modifier. The disruptions in P–O–P linkages upon increasing FeO suggest that FeO causes glass depolymerization. These glasses achieved higher connectivity with increasing Fe 3+ / (Fe 3+ + Fe 2+ ) ratios, conerting phosphorous Q 2 to Q 3 units and iron Q 5 units to Q 4 units. The decrease of nonbridging oxygen fractions with increasing Fe 3+ / (Fe 3+ + Fe 2+ ) ratios, through creating P–O–Fe linkages, is the main reason of enhanced network connectivity. Quantitative structure–property relationship analyses with different structural descriptors were used to correlate with measured properties. The analyses provided valuable insights into structure–property relationships, emphasizing the importance of choosing relevant energy parameters and defining glass network connectivity, particularly in F net descriptors. It was found the Fe–O–P linkage density exhibits strong correlations to measured dissolution rates, supporting the importance of these linkages in improving the chemical durability in iron phosphate glasses.
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Time-Temperature-Transformation (TTT) Diagram for a Sludge Batch 9 Glass Composition Based on Coupled-Operation with the Salt Waste Processing Facility
The amorphous structure of a glass waste form has the potential to rearrange into crystalline phases at temperatures between the liquidus temperature and the glass transition temperature (Tg). Certain phases that can form will be detrimental to the durability of the glass and it is important to know the conditions that promote devitrification. The canister-centerline-cooling (CCC) profile is used to replicate the area within the center of the Defense Waste Processing Facility (DWPF) canister with the slowest cooling during the initial cool down after pouring, which has the greatest potential for crystallization. Other time-temperature conditions that cause significant changes in either phase structure or phase composition are identified by a time-temperature-transformation (TTT) study. The phase stability of a waste form must be determined as a part of the Waste Acceptance Product Specifications (WAPS) if it is to eventually be stored in a geologic repository. This requires the creation of a TTT diagram and analysis of the Tg, as defined by the Department of Energy (DOE). The previous TTT study for a DWPF glass waste form was completed in 2010 prior to coupled operation with the Salt Waste Processing Facility (SWPF). SWPF transfers two high activity waste streams to DWPF for vitrification: a cesium-containing strip effluent and a stream containing monosodium titanate/sludge solids. These SWPF streams were first transferred to DWPF for vitrification during Sludge Batch 9 (SB9) in 2021. The impact of these SWPF streams on crystallization behavior was not determined in previous studies and the need for data to satisfy WAPS Specification 1.4 for SB9 was identified.
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Using Artificial Microstructures to Understand Microstructure Property Relationship-Toughening Mechanisms in Metallic Glass (Final Report)
Metallic glasses are a new class of structural materials which exhibit exciting mechanical properties including high strength and elasticity. In terms of fracture toughness, the material class of metallic glasses spans a wide range; Some metallic glasses are extremely brittle and exhibit near ideal brittle behavior whereas others can be exceptional tough with values comparable to the toughest metals out there. Such large range of observed fracture toughness within the material class of metallic glasses is surprising as they have seemingly a very similar atomic structure. Therefore, we developed “artificial microstructures” which allows to decouple the various contribution of sample geometry, imperfection and structure. Specifically, we decouple variations in the alloys’ chemical composition and the atomic structure and quantified the resulting fracture toughness. Atomic structure of a metallic glass can be modified by the fictive temperature. The fictive temperature of a glass is the temperature at which the liquid metallic glass falls out of equilibrium upon colling and forms a glass. Upon further cooling the structure is maintained only thermal oscillations decrease due to a lower absolute temperature. We found that the effect of fictive temperature (same chemistry, different structural stages of the glass) is comparable to the variations of fracture toughness when the chemistry is varied. Hence, it appears that the subtle differences in the glass structure are responsible for the large range of fracture toughness’s observed. Our results reveal that fracture toughness within the material class of metallic glasses varies significantly and we found some example alloys with exceptional high resistance to fracture and others that are almost ideally brittle. Significant influences on the fracture toughness have the structure of the glass, its chemistry, and some imperfections in the structure.
36 MATERIALS SCIENCE↗