A novel view on classification of glass-forming liquids and empirical viscosity model

Galimzyanov, Bulat N.; Мокшин, А. В.

doi:10.1016/j.jnoncrysol.2021.121009

Cited by 18 publications

(13 citation statements)

References 44 publications

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“…It is important to note that these temperature pairs occur in arbitrary combinations, which indirectly indicates the presence of correlations between “critical” temperatures in some way related to the glass transition. Moreover, this fact is directly supported by previous results relating to the description of the temperature dependence of the viscosity and crystallization rate characteristics of supercooled melts by the scale relations [ 3 , 9 , 30 ], where only the melting and glass transition temperatures,

and

, appear as input parameters. Thus, the determination of specific correlation relationships between the “critical” temperatures of the kinetics of viscous melts is an important task, the solution of which will contribute to a deeper understanding of the solidification processes (glass transition and crystallization).…”

Section: Introductionsupporting

confidence: 75%

“…There is increasing evidence that such transformations can be related to the ability of a liquid to form a glassy state [ 4 , 5 , 6 ]. The results of recent studies show that the glass-forming ability of a liquid depends on the specifics of changes in its atomistic structure and collective dynamics near the melting temperature

[ 7 , 8 , 9 ]. The beginning of such the changes in the dynamics of a liquid corresponds to the Arrhenius crossover temperature

[ 10 , 11 , 12 , 13 ].…”

Section: Introductionmentioning

confidence: 99%

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Arrhenius Crossover Temperature of Glass-Forming Liquids Predicted by an Artificial Neural Network

2023

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The Arrhenius crossover temperature, TA, corresponds to a thermodynamic state wherein the atomistic dynamics of a liquid becomes heterogeneous and cooperative; and the activation barrier of diffusion dynamics becomes temperature-dependent at temperatures below TA. The theoretical estimation of this temperature is difficult for some types of materials, especially silicates and borates. In these materials, self-diffusion as a function of the temperature T is reproduced by the Arrhenius law, where the activation barrier practically independent on the temperature T. The purpose of the present work was to establish the relationship between the Arrhenius crossover temperature TA and the physical properties of liquids directly related to their glass-forming ability. Using a machine learning model, the crossover temperature TA was calculated for silicates, borates, organic compounds and metal melts of various compositions. The empirical values of the glass transition temperature Tg, the melting temperature Tm, the ratio of these temperatures Tg/Tm and the fragility index m were applied as input parameters. It has been established that the temperatures Tg and Tm are significant parameters, whereas their ratio Tg/Tm and the fragility index m do not correlate much with the temperature TA. An important result of the present work is the analytical equation relating the temperatures Tg, Tm and TA, and that, from the algebraic point of view, is the equation for a second-order curved surface. It was shown that this equation allows one to correctly estimate the temperature TA for a large class of materials, regardless of their compositions and glass-forming abilities.

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and

Section: Introductionsupporting

confidence: 75%

[ 7 , 8 , 9 ]. The beginning of such the changes in the dynamics of a liquid corresponds to the Arrhenius crossover temperature

[ 10 , 11 , 12 , 13 ].…”

Section: Introductionmentioning

confidence: 99%

Arrhenius Crossover Temperature of Glass-Forming Liquids Predicted by an Artificial Neural Network

2023

Self Cite

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“…Other equations which have a larger number of fitting parameters make a better representation of the entire viscosity plot [ 103 , 104 ]. It was also shown, that it is possible to reproduce the experimental viscosity data using only two fitting parameters [ 105 ].…”

Section: Liquid Fragility Conceptmentioning

confidence: 99%

Structural Changes in Metallic Glass-Forming Liquids on Cooling and Subsequent Vitrification in Relationship with Their Properties

Louzguine‐Luzgin

2022

Materials

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The present review is related to the studies of structural changes observed in metallic glass-forming liquids on cooling and subsequent vitrification in terms of radial distribution function and its analogues. These structural changes are discussed in relationship with liquid’s properties, especially the relaxation time and viscosity. These changes are found to be directly responsible for liquid fragility: deviation of the temperature dependence of viscosity of a supercooled liquid from the Arrhenius equation through modification of the activation energy for viscous flow. Further studies of this phenomenon are necessary to provide direct mathematical correlation between the atomic structure and properties.

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“…Most modern studies of the microscopic structure of Ni62Nb38 alloy cover the temperature range below the liquidus temperature and do not consider ultrahigh temperatures [7][8][9][10]. For the correct processing of this alloy, for example, by ionized gas, it is necessary to know the critical temperatures as the boiling temperature [11].…”

Section: Introductionmentioning

confidence: 99%

Structural transformations in binary Ni₆₂Nb₃₈ alloy at ultrahigh temperatures

Yarullin

Doronina

2022

J. Phys.: Conf. Ser.

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In this study, we performed the molecular dynamics simulation of the binary Ni62Nb38 alloy at heating from 300 K to 9000 K. The temperature dependences of the density and the fraction of liquid atoms were calculated. The boiling temperature of the system is determined. It has been established that near the temperature 7000 K the system undergoes phase transition from liquid to gas phase. It is shown that near the boiling temperature, the molten metal forms a branched structure. The obtained results made it possible to estimate the region of the liquid phase and to determine the probable scenario for the occurrence of structural changes near the boiling point.

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A novel view on classification of glass-forming liquids and empirical viscosity model

Cited by 18 publications

References 44 publications

Arrhenius Crossover Temperature of Glass-Forming Liquids Predicted by an Artificial Neural Network

Arrhenius Crossover Temperature of Glass-Forming Liquids Predicted by an Artificial Neural Network

Structural Changes in Metallic Glass-Forming Liquids on Cooling and Subsequent Vitrification in Relationship with Their Properties

Structural transformations in binary Ni₆₂Nb₃₈ alloy at ultrahigh temperatures

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A novel view on classification of glass-forming liquids and empirical viscosity model

Cited by 18 publications

References 44 publications

Arrhenius Crossover Temperature of Glass-Forming Liquids Predicted by an Artificial Neural Network

Arrhenius Crossover Temperature of Glass-Forming Liquids Predicted by an Artificial Neural Network

Structural Changes in Metallic Glass-Forming Liquids on Cooling and Subsequent Vitrification in Relationship with Their Properties

Structural transformations in binary Ni62Nb38 alloy at ultrahigh temperatures

Contact Info

Product

Resources

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Structural transformations in binary Ni₆₂Nb₃₈ alloy at ultrahigh temperatures