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Abstract Precise measurements of shear modulus changes and heat effects occurring upon heating of bulk glassy Pd 40 Ni 40 P 20 from room temperature into the supercooled liquid region are performed. It is found the absorbed heat increases linearly with the shear modulus measured near room temperature, in excellent agreement with the prediction of the Interstitialcy theory. [ABSTRACT FROM AUTHOR]

It is well known that structural relaxation below the glass transition and crystallization of metallic glasses are accompanied by the heat release and increase of the shear modulus. In the present work, these effects are studied in detail for sixteen Zr-, Pd- and La-based metallic glasses and analyzed within the framework of the Interstitialcy theory. The obtained results imply that the increase of the shear modulus and heat effects occurring upon structural relaxation and crystallization are conditioned by the same mechanism – a change of the elastic energy related to the system of interstitialcy defects frozen-in upon glass production. In particular, the heat of crystallization constitutes a direct manifestation of the dissipation of the elastic energy related to this defect system, which disappears upon crystallization. [ABSTRACT FROM AUTHOR]

The relation between the temperature dependence of shear modulus G ( T ) and viscosity η ( T ) of Ge x Se 1 − x (0 ≤ x ≤0.30) system across the glass-transition range is investigated using several ideas: the Wachtman equation for G , the shoving model and the bond strength–coordination number fluctuation (BSCNF) model of viscosity. Firstly, the present study shows that the empirical Wachtman equation reproduces reasonably well the shear modulus data. Next, it is shown that the shoving model implemented with the analysis of G describes quite well the high viscosity data in the glass state. Besides, the viscosity in the supercooled liquid side, especially for Ge 3 Se 7 , exhibits a clear change from Arrhenius-like to VFT-like temperature dependence upon heating. From the viscosity analysis for the composition GeSe 4 , GeSe 3 and Ge 3 Se 7 , we obtain a maximum value for the activation energy across the glass-transition range. This result implies that there is an energetic barrier that the structural units need to surmount collectively before the occurrence of the viscous flow. The temperature variation of the activation energy also suggests that in terms of the BSCNF model, the decomposition of network structure upon heating is linked with the collective excitations of the structural units, which gives a viewpoint relevant to the softening of glass. [ABSTRACT FROM AUTHOR]

Changes of the shear modulus and heat effects occurring upon structural relaxation and crystallization of metallic glasses are analysed within the framework of two approaches, the Interstitialcy theory and elastic dipole model. The former approach assumes that elastic and heat effects are determined by dumbbell interstitial defects inherited from the melt. The analysis within this framework is based on the postulate that the internal energy change is proportional to the shear modulus and defect concentration change. The elastic dipole model takes into account that dumbbell interstitials are in fact elastic dipoles and the change of the internal energy is determined by their elastic strain fields, which are considered within the framework of non-linear theory of elasticity. In spite of fully different phenomenology, both approaches lead to very similar theoretical expressions for the elastic and heat effects. The interconnection between these approaches, their advantages and problems are discussed. [ABSTRACT FROM AUTHOR]

• Physics- and chemistry-informed machine learning models were developed for predicting glass properties. • Young's modulus, shear modulus and electrical resistivity were predicted by artificial neural network (ANN), support vector machine (SVM), and random forest (RF) models. • Relationships between glass properties and their first and second important features were revealed. Physics- and chemistry-informed machine learning (ML) models were trained by using descriptors in the element physical and chemical properties domain, which include stoichiometric, elemental-property-based, valance orbital occupation, and ionicity features. Young's modulus, shear modulus and electrical resistivity (ρ) data for a group of oxide glasses were used to train artificial neural network (ANN), support vector machine (SVM), and random forest (RF) models. In comparison with experimental values, the ANN performs the best in predicting elastic moduli, whereas the RF is the best in predicting the temperature dependence of ρ in terms of the coefficient of determination (R2) value. The benefits of the ML models using descriptors in the element physical and chemical properties domain were demonstrated by revealing the relationships between the predicted glass properties and their first and second important features through a grid search. [ABSTRACT FROM AUTHOR]

It has been shown that the changes of the internal energy and elastic moduli occurring upon crystallization of metallic glasses can be explained under the assumption that the initial glassy structure contains “defects” similar to elastic dipoles in crystals. These “defects” define the elastic softening of glass and disappear upon crystallization so that their elastic energy is released as heat. The experimental verification of this model has been performed and characteristic parameters of elastic dipoles in a Zr-based bulk metallic glass have been determined. [ABSTRACT FROM AUTHOR]

Parallel measurements of the enthalpy and high-frequency shear modulus changes occurring upon structural relaxation of five bulk metallic glasses are performed. An analysis showed that there exists a one-to-one correlation between the change of the molar enthalpy and the alteration of the number of defects calculated within the framework of the Interstitialcy theory on the basis of shear modulus relaxation data. The defect formation enthalpy derived using this correlation agrees quite well with this quantity accepted in the Interstitialcy theory. [ABSTRACT FROM AUTHOR]

Abstract: The susceptibility of the shear modulus to the concentration of interstitialcy-like defects in a metallic glass has been determined using calorimetric data and in situ measurements of the shear modulus of glass and parent crystal at different heating rates. The obtained results provide further support for the Interstitialcy theory, which consistently connects equilibrium/supercooled liquid, glassy and crystalline states. [Copyright &y& Elsevier]