Galimzyanov, Bulat Nailevich

Tsygankov A.A., Galimzyanov B.N., Mokshin A.V.

Galimzyanov B.N., Doronina M.A., Mokshin A.V.

Galimzyanov B.N., Nikiforov G.A., Anikeev S.G., Artyukhova N.V., Mokshin A.V.

The mechanical characteristics of a monolithic (non-porous) crystalline or amorphous material are described by a well-defined set of quantities. It is possible to change the mechanical properties by introducing porosity into this material; as a rule, the strength values decrease with the introduction of porosity. Thus, porosity can be considered an additional degree of freedom that can be used to influence the hardness, strength and plasticity of the material. In the present work, using porous crystalline NiTi as an example, it is shown that the mechanical characteristics such as the Young’s modulus, the yield strength, the ultimate tensile strength, etc., demonstrate a pronounced dependence on the average linear size l¯ of the pores. For the first time, an empirical equation is proposed that correctly reproduces the dependence of the mechanical characteristics on the porosity ϕ and on the average linear size l¯ of the pores in a wide range of sizes: from nano-sized pores to pores of a few hundred microns in size. This equation correctly takes into account the limit case corresponding to the monolithic material. The obtained results can be used directly to solve applied problems associated with the design of materials with the necessary combination of physical and mechanical characteristics, in particular, porous metallic biomaterials.

Galimzyanov B.N., Tsygankov A.A., Suslov A.V., Lad'yanov V.I., Mokshin A.V.

Near the melting temperature, equilibrium bismuth melt is characterized by structural features that are absent in equilibrium monatomic simple liquids. In the present work, the structure of bismuth melt is studied by X-ray diffraction experiments and quantum chemical calculations. The presence of quasi-stable structures in the melt has been found, the lifetime of which exceeds the structural relaxation time of this melt. It is shown that these structures are characterized by a low degree of ordering and spatial localisation. It was found that up to $50$\% of the atoms in the melt can be involved in the formation of these structures. The elementary structural units of these structures are triplets of regular geometry with the characteristic lengths $3.25$ \AA~and $4.7$ \AA~as well as with the characteristic angles $45^{\circ}$ and $90^{\circ}$. The characteristic lengths of these triplets are fully consistent with correlation lengths associated with the short-range order in bismuth melt.

Tsygankov A.A., Galimzyanov B.N., Mokshin A.V.

Liquid antimony near the melting temperature has an unusual structure characterized by a shoulder in the radial distribution function and the static structure factor. There is a point of view that stable structures are realized in antimony melt, which are clusters or dimers. However, the stability of these structures has not been previously studied. In the present study, ab-initio molecular dynamics simulations of liquid antimony were performed at a temperature corresponding to the liquid state near the melting temperature and at atmospheric pressure. The local structure of liquid antimony was investigated and the distribution of neighborhood times of atom pairs on different spatial scales was calculated. It was found that liquid antimony contains structural formations in the form of quasi-stable dimers, whose lifetime is longer than the structural relaxation time of the liquid.

Nikiforov G.A., Galimzyanov B.N., Mokshin A.V.

Porous materials are widely used in many industries. However, their mechanical properties are inferior to those of their homogeneous non-porous analogues. In the present work, on the example of porous titanium nickelide, we studied the effect of the structure of the solid framework on the mechanical properties of the porous material. A method to improve the mechanical properties by achieving a uniform density profile along the strain direction is considered. It is shown that the uniform distribution of the crystalline matrix along the strain axis does not significantly affect on the mechanical properties of the porous system. The mechanism of pore collapse under compression has been investigated.

Galimzyanov B.N., Doronina M.A., Mokshin A.V.

The Young’s modulus E is the key mechanical property that determines the resistance of solids to tension/compression. In the present work, the correlation of the quantity E with such characteristics as the total molar mass M of alloy components, the number of components n forming an alloy, the yield stress σy and the glass transition temperature Tg has been studied in detail based on a large set of empirical data for the Young’s modulus of different amorphous metal alloys. It has been established that the values of the Young’s modulus of metal alloys under normal conditions correlate with such a mechanical characteristic as the yield stress as well as with the glass transition temperature. As found, the specificity of the “chemical formula” of alloy, which is determined by molar mass M and number of components n, does not affect on elasticity of the material. The machine learning algorithm identified both the quantities M and n as insignificant factors in determining E. A simple non-linear regression model is obtained that relates the Young’s modulus with Tg and σy, and this model correctly reproduces the experimental data for metal alloys of different types. This obtained regression model generalizes the previously presented empirical relation E≃49.8σy for amorphous metal alloys.

Galimzyanov B.N., Doronina M.A., Mokshin A.V.

The development and implementation of the methods for designing amorphous metal alloys with desired mechanical properties is one of the most promising areas of modern materials science. Here, the machine learning methods appear to be a suitable complement to empirical methods related to the synthesis and testing of amorphous alloys of various compositions. In the present work, a method is proposed a method to determine amorphous metal alloys with mechanical properties closest to those required. More than 50,000 amorphous alloys of different compositions have been considered, and the Young’s modulus E and the yield strength σy have been evaluated for them by the machine learning model trained on the fundamental physical properties of the chemical elements. Statistical treatment of the obtained results reveals that the fundamental physical properties of the chemical element with the largest mass fraction are the most significant factors, whose values correlate with the values of the mechanical properties of the alloys, in which this element is involved. It is shown that the values of the Young’s modulus E and the yield strength σy are higher for amorphous alloys based on Cr, Fe, Co, Ni, Nb, Mo and W formed by the addition of semimetals (e.g., Be, B, Al, Sn), nonmetals (e.g., Si and P) and lanthanides (e.g., La and Gd) than for alloys of other compositions. Increasing the number of components in alloy from 2 to 7 and changing the mass fraction of chemical elements has no significantly impact on the strength characteristics E and σy. Amorphous metal alloys with the most improved mechanical properties have been identified. In particular, such extremely high-strength alloys include Cr80B20 (among binary), Mo60B20W20 (among ternary) and Cr40B20Nb10Pd10Ta10Si10 (among multicomponent).

Galimzyanov B.N., Doronina M.A., Mokshin A.V.

Large-scale molecular dynamics simulation is used to study the mechanical properties of amorphous Ni62Nb38 at the temperature 300 K determined at uniaxial compression and tensile deformation. The stress–strain curves, Young’s modulus, yield strength, and fracture strength are obtained for this system. A relationship between the Young’s modulus and the yield strength is observed for the first time and obeys the same empirical linear law for metallic glasses of other compositions. It is shown that the mechanical properties of amorphous Ni62Nb38 alloy are higher than those of metallic glasses of other compositions.

Galimzyanov B.N., Doronina M.A., Mokshin A.V.

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.

Galimzyanov B.N., Doronina M.A., Mokshin A.V.

Binary Ni$_{62}$Nb$_{38}$ alloy belongs to the unique class of binary off-eutectic systems, which are able to form a bulk glassy state [L. Xia et al., J. Appl. Phys. 99 (2006) 026103]. In the present work, the ($p$, $T$) phase diagram of Ni$_{62}$Nb$_{38}$ alloy was first determined for a wide thermodynamic range with temperatures from $300$\,K to $6000$\,K and with pressures from $1$\,atm to $1.2\times10^7$\,atm. For this thermodynamic range, elements of the phase diagram such as the liquid-crystal coexistence line and the glass transition line are defined. Our results reveal good agreement between the simulation results and the known experimental values of the liquidus temperature and the glass transition temperature for the isobar $p=1$\,atm. The phase diagram is detailed for pressures greater than $1\times10^{7}$\,atm. For the first time, the phase separation conditions at which the liquid Nb and crystalline Ni phases coexist in the system were determined.

Galimzyanov B.N., Yarullin D.T., Mokshin A.V.

Abstract Crystallization of supercooled liquids is mainly determined by two competing processes associated with the transition of particles (atoms) from liquid phase to crystalline one and, vice versa, with the return of particles from crystalline phase to liquid one. The quantitative characteristics of these processes are the so-called attachment rate g + and the detachment rate g − , which determine how particles change their belonging from one phase to another. In the present study, a correspondence rule between the rates g + and g − as functions of the size N of growing crystalline nuclei is defined for the first time. In contrast to the well-known detailed balance condition, which relates g + ( N ) and g − ( N ) at N = n c (where n c is the critical nucleus size) and is satisfied only at the beginning of the nucleation regime, the found correspondence rule is fulfilled at all the main stages of crystallization kinetics (crystal nucleation, growth and coalescence). On the example of crystallizing supercooled Lennard–Jones liquid, the rate g − was calculated for the first time at different supercooling levels and for the wide range of nucleus sizes N ∈ [ n c ; 40 n c ] . It was found that for the whole range of nucleus sizes, the detachment rate g − is only ≈ 2 % less than the attachment rate g + . This is direct evidence that the role of the processes that counteract crystallization remains significant at all the stages of crystallization. Based on the obtained results, a kinetic equation was formulated for the time-dependent distribution function of the nucleus sizes, that is an alternative to the well-known kinetic Becker–Döring–Zeldovich–Frenkel equation.

Tsygankov A.A., Galimzyanov B.N., Mokshin A.V.

Abstract Porous crystalline nitinol is widely applied in various fields of science and technology due to the unique combination of physical and mechanical properties as well as biocompatibility. Porous amorphous nitinol is characterized by improved mechanical properties compared to its crystalline analogues. Moreover, this material is more promising from the point of view of fundamental study and practical application. The production of porous amorphous nitinol is a difficult task requiring rapid cooling protocol and optimal conditions to form a stable porous structure. In the present work, based on the results of molecular dynamics simulations, we show that porous nitinol with the amorphous matrix can be obtained by injection of argon into a liquid melt followed by rapid cooling of the resulting mixture. We find that the porosity of the system increases exponentially with increasing fraction of injected argon. It has been established that the system should contain about ∼ 18 % –23% argon for obtain an open porous structure, while the system is destroyed by overheated inert gas when the argon fraction is more than ∼ 23 %. It is shown that the method of argon injection makes it possible to obtain a highly porous system with the porosity ∼ 70 % consisting the spongy porous structure similar to aerogels and metallic foams.

Galimzyanov B.N., Mokshin A.V.

Abstract Understanding the cavity formation and cavity growth mechanisms in solids has fundamental and applied importance for the correct determination of their exploitation capabilities and mechanical characteristics. In this work, we present the molecular dynamics simulation results for the process of homogeneous formation of nanosized cavities in a single-component amorphous metallic alloy. To identify cavities of various shapes and sizes, an original method has been developed, which is based on filling cavities by virtual particles (balls) of the same diameter. By means of the mean first-passage time analysis, it was shown that the cavity formation in an amorphous metallic melt is the activation-type process. This process can be described in terms of the classical nucleation theory, which is usually applied to the case of first order phase transitions. Activation energy, critical size and nucleation rate of cavities are calculated, the values of which are comparable with those for the case of crystal nucleation in amorphous systems.

Galimzyanov B.N., Doronina M.A., Mokshin A.V.

Study of condensed matter in certain extreme conditions allows one to better understand the mechanisms of microscopic structural transformations and to develop materials with completely new mechanical properties. In the present work, we study the structure and crystallization kinetics of bulk metallic glass (BMG) Ni$_{62}$Nb$_{38}$. We show that this BMG is rapidly crystallized under the combined effect of shear deformation and ultrahigh pressure. A threshold pressure required to initiate the formation of a stable crystalline phase is revealed. Shear deformation and pressure lead to the phase separation: two high-density inhomogeneous crystal structures are formed. We find that the crystallization of this BMG occurs in two stages due to the significant difference in the growth rates of Ni and Nb crystalline phases. The results of the present study make a significant contribution to understanding the crystallization and amorphization features of Ni-based BMG's.

Yalameha S.

Aniya M., Noguchi K., Ikeda M.

Jiang Z., Zhu X.

Polyzos E.

Wang S., Zhang Q., Wu Z., Sun Y., Li X., Fan Y.

Das S., Priya M.

We study the dynamics of particles in binary mixtures near the freezing transition using molecular dynamics simulations. The particles are considered to interact via a Lennard–Jones potential, and the impact of varying their size-ratio on their dynamics is examined. By calculating the mean-squared displacements and the self-intermediate scattering function of the particles, we find that introducing size disparity in an equimolar mixture at a constant packing fraction hinders particle movement, leading to a decrease in the self-diffusion coefficient. Additionally, as the size disparity increases, the local cage relaxation time becomes longer. Interestingly, the increase in the system’s viscosity does not correspond to an expected decrease in self-diffusion, resulting in an unusual violation of the Stokes–Einstein relation. Unlike typical glass-forming mixtures, where this violation parameter increases as temperature decreases, we observe the opposite behaviour.

Zhang N., Spieckermann F., Yuan X., Şopu D., Jin X., Sun K., Mendez A., Yu P., Wang G., Eckert J.

Fedorov V., Pluzhnikova T., Balybin D., Berezner A., Fedotov D., Boitsova M., Yakovlev A., Perov N., Zubkov S., Shendrikova L.

Fomin Y.D., Brazhkin V.V.

Tsygankov A.A., Galimzyanov B.N., Mokshin A.V.

Beg C., Byeon J., Berman N., Kieffer J.

Zhang Y., Yuan L., Hu Y., Xia R.

Galimzyanov B.N., Doronina M.A., Mokshin A.V.

Amirova L., Andrianova K., Gaifutdinov A., Amirov R.

Chen M., Song W., Lin W., Feng Z.

Alcanfor A.A., da Silva L.P., de Oliveira R.C., Paulo G.A., Sousa C.P., Campos O.S., Dias D.F., Feitosa F.X., de Sant'Ana H.B., Monteiro N.K., Correia A.N., de Lima-Neto P.

Through experimental research and theoretical calculation, it was investigated the effect of water and temperature on the electrodeposition of antimony (Sb) on a platinum (Pt) electrode. The plating solutions were prepared by the addition of 0.05 mol L–1 SbCl3 to the mixtures of choline chloride (ChCl), ethylene glycol (EG) and water (W) in the following molar ratio: 1ChCl:2EG (bath 1), 1ChCl:2EG:0.45 W (bath 2), and 1ChCl:2EG:1.62 W (bath 3). Furthermore, the Sb coatings were electrodeposited at 297 and 338 K. The surface morphologies and crystalline structures of Sb electrodeposits were analysed by scanning electron microscopy (SEM) and X-ray diffraction (XRD), respectively. In addition, to understand the interactions of Sb3+ species with the other components of the plating solution, models were created and calculated using density functional theory (DFT) and quantum theory of atoms in molecules (QTAIM). The results of the voltammetric behaviour of Sb3+ species indicated that the reduction potential was shifted towards more positive values with increasing water content on the electrolyte, indicating that the water catalyses the electrochemical reduction of the Sb3+ species. The values of the diffusion coefficients for the Sb3+ species were calculated by applying the Cottrell equation, which increased with the addition of water and temperature increment. The water content and temperature increase affect the surface morphologies of the Sb electrodeposited coatings, which is attributed to the improvement of Sb electrodeposition rate. Moreover, Sb electrodeposited coatings were successfully obtained without adding a complexing agent, indicating that the procedure adopted for the Sb electrodeposition is environmentally friendly. The XRD results revealed the pure phase Sb films. DFT simulations indicated that the Sb-Cl interaction is stronger, which suggests the formation of Sb-Cl complexes. Adding H2O molecules favours the electron affinity of the systems, and QTAIM results suggested that this additive decreased the electron density of Sb3+ ions.

Ojovan M.I., Louzguine-Luzgin D.V.

An additional crossover of viscous flow in liquids occurs at a temperature Tvm above the known non-Arrhenius to Arrhenius crossover temperature (TA). Tvm is the temperature when the minimum possible viscosity value ηmin is attained, and the flow becomes non-activated with a further increase in temperature. Explicit equations are proposed for the assessments of both Tvm and ηmin, which are shown to provide data that are close to those experimentally measured. Numerical estimations reveal that the new crossover temperature is very high and can barely be achieved in practical uses, although at temperatures close to it, the contribution of the non-activated regime of the flow can be accounted for.

Shi Q.L., Wang X.D., Cao Q.P., Ding S.Q., Zhang D.X., Beyer K.A., Jiang J.Z.

Temperature-induced polymorphic structural crossover in metallic liquid indium (In), tin (Sn), and antimony (Sb) is investigated by in situ high-energy x-ray diffraction and ab initio molecular dynamics simulations. The results demonstrate the existence of a temperature-induced reversible and gradual structural crossover in these three liquids, reflecting from both ``static'' structures, e.g., peak positions of the structure factor and pair distribution function, bond angle distribution, number of tetrahedra, cluster connection, free volume, and dynamical behaviors, including the relaxation time, diffusion coefficient, and non-Gaussian parameter. The main difference from liquid In, Sn, to Sb is that not only the large-sized free volume but also the anharmonicity and the dynamical heterogeneity increase significantly with the appearance of strong covalent bonds. These findings will deepen the understanding of liquid structure and the liquid-liquid transition in metallic liquids.

Liu Z., Zhao X., Tian Y., Tan J.

The properties of crude oil are of great importance for efficient recovery of oil from oil fields. The properties are primarily used in reservoir simulations for prediction of oil recovery in order to save time and obtain the best recovery. Among various crude oil properties, viscosity is the most important one which should be precisely simulated. In this work, a novel approach based on machine learning is developed for estimation of crude oil viscosity as function of input parameters. Multiple distinct tree-based ensemble models are applied on the available dataset in this work to predict heavy-oil viscosity. AdaBoost Decision Trees (ADA-DT), Random Forest (RF), and Extremely Randomized Trees (ERT) are selected tree-based ensembles that used in this work for the simulation of oil viscosity. An Isolation Forest is applied on the dataset to remove outliers and also the earthworm optimization algorithm (EWA) is employed to find the optimum values of models’ hyper-parameters. Optimized models of ADA-DT, ERT, and RF have RMSE error rates of 35.42, 27.02, and 58.71. Thus, ERT is selected as the best model of the dataset used in this work.

Zaccone A.

A microscopic formula for the viscosity of liquids and solids is derived rigorously from a first-principles (microscopically reversible) Hamiltonian for particle-bath atomistic motion. The derivation is done within the framework of nonaffine linear response theory. This formula may lead to a valid alternative to the Green-Kubo approach to describe the viscosity of condensed matter systems from molecular simulations without having to fit long-time tails. Furthermore, it provides a direct link between the viscosity, the vibrational density of states of the system, and the zero-frequency limit of the memory kernel. Finally, it provides a microscopic solution to Maxwell's interpolation problem of viscoelasticity by naturally recovering Newton's law of viscous flow and Hooke's law of elastic solids in two opposite limits.

Galimzyanov B.N., Tsygankov A.A., Suslov A.V., Lad'yanov V.I., Mokshin A.V.

Near the melting temperature, equilibrium bismuth melt is characterized by structural features that are absent in equilibrium monatomic simple liquids. In the present work, the structure of bismuth melt is studied by X-ray diffraction experiments and quantum chemical calculations. The presence of quasi-stable structures in the melt has been found, the lifetime of which exceeds the structural relaxation time of this melt. It is shown that these structures are characterized by a low degree of ordering and spatial localisation. It was found that up to $50$\% of the atoms in the melt can be involved in the formation of these structures. The elementary structural units of these structures are triplets of regular geometry with the characteristic lengths $3.25$ \AA~and $4.7$ \AA~as well as with the characteristic angles $45^{\circ}$ and $90^{\circ}$. The characteristic lengths of these triplets are fully consistent with correlation lengths associated with the short-range order in bismuth melt.

Tsygankov A.A., Galimzyanov B.N., Mokshin A.V.

Liquid antimony near the melting temperature has an unusual structure characterized by a shoulder in the radial distribution function and the static structure factor. There is a point of view that stable structures are realized in antimony melt, which are clusters or dimers. However, the stability of these structures has not been previously studied. In the present study, ab-initio molecular dynamics simulations of liquid antimony were performed at a temperature corresponding to the liquid state near the melting temperature and at atmospheric pressure. The local structure of liquid antimony was investigated and the distribution of neighborhood times of atom pairs on different spatial scales was calculated. It was found that liquid antimony contains structural formations in the form of quasi-stable dimers, whose lifetime is longer than the structural relaxation time of the liquid.

Sun P., Huo S., He T.

Development of predictive models for estimation of reservoir fluids properties as function of temperature, fluid composition, and pressure would be essential for simulation of oil reservoirs. The measurement of the viscosity of heavy crude oil is an essential part of petroleum science which can be done by experimental methods, however computational methods can be integrated to the experimental methods to reduce the effort and save time of measurements. For the purpose of predicting the heavy-oil viscosity, this work applies a number of different models to the dataset that is currently available for correlating viscosity to input parameters. The Gradient Boosting Regression Tree (GBR), the Support Vector Machine (SVM), and the Stochastic Gradient Decent (SGD) are the models that have been utilized in this investigation, and the genetic algorithm (GA) has been applied in order to optimize the hyper-parameters of these models. The RMSE error rates for the completed versions of the GBR, SGD, and SVM models are, in descending order, 26.6, 29.8, and 30.5. For the purposes of this research, the GBR model was determined to be the most suitable option among those available for estimation of crude oil viscosity.

Kelton K.F.

Metallic glasses have the potential to become transformative materials, but this is hindered by the lack of ability to accurately predict which metallic alloys will form good glasses. Current approaches are limited to empirical rules that often rely on parameters that are unknown until the glasses are made, rendering them not predictive. In this Perspective, properties of metallic liquids at elevated temperatures and how these might lead to better predictions for glass formation are explored. A central topic is liquid fragility, which characterizes the different dynamics of the liquids. What fragility is and how it might be connected to the liquid structure is discussed. Since glass formation is ultimately limited by crystallization during cooling, recent advances in crystal growth and nucleation are also reviewed. Finally, some approaches for improving glass stability and glass rejuvenation for improved plasticity are discussed. Building on a summary of results, some key questions are raised and a prospective for future studies is offered.

Galimzyanov B.N., Doronina M.A., Mokshin A.V.

The Young’s modulus E is the key mechanical property that determines the resistance of solids to tension/compression. In the present work, the correlation of the quantity E with such characteristics as the total molar mass M of alloy components, the number of components n forming an alloy, the yield stress σy and the glass transition temperature Tg has been studied in detail based on a large set of empirical data for the Young’s modulus of different amorphous metal alloys. It has been established that the values of the Young’s modulus of metal alloys under normal conditions correlate with such a mechanical characteristic as the yield stress as well as with the glass transition temperature. As found, the specificity of the “chemical formula” of alloy, which is determined by molar mass M and number of components n, does not affect on elasticity of the material. The machine learning algorithm identified both the quantities M and n as insignificant factors in determining E. A simple non-linear regression model is obtained that relates the Young’s modulus with Tg and σy, and this model correctly reproduces the experimental data for metal alloys of different types. This obtained regression model generalizes the previously presented empirical relation E≃49.8σy for amorphous metal alloys.

Galimzyanov B.N., Doronina M.A., Mokshin A.V.

The development and implementation of the methods for designing amorphous metal alloys with desired mechanical properties is one of the most promising areas of modern materials science. Here, the machine learning methods appear to be a suitable complement to empirical methods related to the synthesis and testing of amorphous alloys of various compositions. In the present work, a method is proposed a method to determine amorphous metal alloys with mechanical properties closest to those required. More than 50,000 amorphous alloys of different compositions have been considered, and the Young’s modulus E and the yield strength σy have been evaluated for them by the machine learning model trained on the fundamental physical properties of the chemical elements. Statistical treatment of the obtained results reveals that the fundamental physical properties of the chemical element with the largest mass fraction are the most significant factors, whose values correlate with the values of the mechanical properties of the alloys, in which this element is involved. It is shown that the values of the Young’s modulus E and the yield strength σy are higher for amorphous alloys based on Cr, Fe, Co, Ni, Nb, Mo and W formed by the addition of semimetals (e.g., Be, B, Al, Sn), nonmetals (e.g., Si and P) and lanthanides (e.g., La and Gd) than for alloys of other compositions. Increasing the number of components in alloy from 2 to 7 and changing the mass fraction of chemical elements has no significantly impact on the strength characteristics E and σy. Amorphous metal alloys with the most improved mechanical properties have been identified. In particular, such extremely high-strength alloys include Cr80B20 (among binary), Mo60B20W20 (among ternary) and Cr40B20Nb10Pd10Ta10Si10 (among multicomponent).

Huang L.J., Lin H.J., Wang H., Ouyang L.Z., Zhu M.

Metal hydrides are promising materials for solid-state hydrogen storage, however, their gravimetric hydrogen storage density is generally low. In addition, they may also exhibit poor activity, sluggish de/hydrogenation kinetics and high thermodynamic stability, in particular for metal hydrides with high storage capacity. Because of the long-range disordered atomic structure, the amorphous structure, showing a wider interstitial configuration diversity, can provide hydrogen with more types of occupation sites. Such unique property leads to much larger hydrogen storage capacity, faster de/hydrogenation kinetics, local thermodynamic destabilization and even destruction resistance. Therefore, making use of amorphous structure is one of the attractive strategies for promoting the performance of metal hydrides. To develop amorphous hydrogen storage alloys, composition design is the first issue, and two main factors should be considered. One is the glass forming ability of alloys and the other is hydrogen storage ability of the alloys. Comparing with the crystalline counterparts, the amorphous hydrogen storage alloys exhibit some unique features: (1) the non-Arrhenius hydrogen diffusion; (2) the deviation from the Sieverts’ law; (3) protean hydrogen-induced phase separation/crystallization; (4) plateau-free pressure-composition-isothermal curve; (5) excessed storage capacity; etc. Till now, the developed hydrogen storage amorphous alloys are mainly Ti-based, Zr-based and Mg-based alloys. Some amorphous alloys do show attractive performance. In particular, Mg-based amorphous alloys have been investigated extensively in recent years. The hydrogen storage capacity in Mg-based amorphous alloys can be readily higher than 3.0 wt%-H, and with addition of other elements, one can also obtain reasonable de/hydrogenation rate and temperature during electrochemical or gaseous process. Though the de/hydrogenation capacity and kinetics of the amorphous alloys can be much better than the crystalline counterparts, there are still great challenges, such as amorphous structure stability, long-cycle reversible de/hydrogenation and irreversible hydrogen-induced amorphous phase transformation. With further exploration of alloy composition and material processing, there are great chances in using hydrogen storage amorphous alloys as energy storage material.

Anikeev S.G., Kaftaranova M.I., Hodorenko V.N., Ivanov S.D., Artyukhova N.V., Shabalina A.V., Kulinich S.A., Slizovsky G.V., Mokshin A.V., Gunther V.E.

Alloys based on TiNi are widely used in various fields of technology and medicine. In the present work, we report on the preparation of TiNi-alloy-based wire with the shape-memory effect, which was used for compression clips for surgery. The composition and structure of the wire and its martensitic and physical–chemical properties were studied using SEM, TEM, optic microscopy, profilometry, mechanical tests, etc. The TiNi alloy was found to consist of B2 and B19′ and secondary-phase particles of Ti2Ni, TiNi3 and Ti3Ni4. Its matrix was slightly enriched in Ni (50.3 at.% of Ni). A homogeneous grain structure was revealed (an average grain size of 19 ± 0.3 μm) with equal quantities of grain boundaries of special and general types. The surface oxide layer provides improved biocompatibility and promotes the adhesion of protein molecules. Overall, the obtained TiNi wire was concluded to exhibit martensitic, physical and mechanical properties suitable for its use as an implant material. The wire was then used for manufacturing compression clips with the shape-memory effect and applied in surgery. The medical experiment that involved 46 children demonstrated that the use of such clips in children with double-barreled enterostomies permitted improvement in the results of surgical treatment.

Liu B., Li Z., Li W., Pan Y., Wu W.

Porosity can change the phase transformation behaviors of the NiTi Shape Memory Alloys (SMAs). In this work, the dependence of porosity of nanocrystalline (NC) NiTi SMAs on martensite transformation deformation mechanism is studied by molecular dynamics (MD) simulation. The effects of porosity on martensite transformation deformation mechanism of NC NiTi SMAs are studied under an isothermal condition. The simulation results show that the threshold temperatures of phase transformation and residual strain of NC NiTi SMAs increase with the increasing porosity, while the threshold stresses of phase transformation of NC NiTi SMAs decrease with the increasing porosity. Furthermore, the effects of loading types, peak stresses and initial temperatures on martensite transformation deformation mechanisms of NC porous NiTi SMAs are analyzed. The results show that the threshold stresses of phase transformation of NC porous NiTi SMAs increases with the increase of temperature and peak stress, and residual strain increases with the decrease of temperature or the increases of peak stress. These results are helpful to further understand the phase transformation behavior of NC porous NiTi SMAs at the atomic scale.

Li D., Zhang X., Kang Q.

Measurement of viscosity of crude oil is critical for reservoir simulators. Computational modeling is a useful tool for correlation of crude oil viscosity to reservoir conditions such as pressure, temperature, and fluid compositions. In this work, multiple distinct models are applied to the available dataset to predict heavy-oil viscosity as function of a variety of process parameters and oil properties. The computational techniques utilized in this work are Decision Tree (DT), MLP, and GRNN which were utilized in estimation of heavy crude oil samples collected from middle eastern oil fields. For the estimation of viscosity, the firefly algorithm (FA) was employed to optimize the hyper-parameters of the machine learning models. The RMSE error rates for the final models of DT, MLP, and GRNN are 40.52, 25.08, and 30.83, respectively. Also, the R2-scores are 0.921, 0. 978, and 0.933, respectively. Based on this and other criteria, MLP is chosen as the best model for this study in estimating the values of crude oil viscosity.