Effects of Number of Atoms and Doping Concentration on the Structure, Phase Transition, and Crystallization Process of Fe_1-x-yNi_xCo_y Alloy: A Molecular Dynamic Study

Abstract

In this study, molecular dynamics simulations are employed to study the influencing factors such as doping concentration, number of atoms, and temperature on the structural characteristics, phase transition, and crystallization of Fe_1-x-yNi_xCo_y alloy. The results show that Fe_1-x-yNi_xCo_y alloy always exists with three metals, Fe, Ni, and Cu, which are distributed quite evenly according to the ratio of tap phase concentration. In Fe_1-x-yNi_xCo_y alloy, there are always six types of links, Fe–Fe, Fe–Ni, Fe–Co, Ni–Ni, Ni–Co, and Co–Co. Calculated results showed with the increases in the doping concentration, the length of links (r) has a constant value and the height g(r) of the Radial Distribution Function (RDF) has a modified value. The process of increasing the concentration of Fe doping, and reducing the concentration of Co doping leads to an increase in crystallization, a decrease in the size (l) of the alloy, and the total energy of the system (E_tot) increases and then decreases. Similarly, increasing the number of atoms leads to an increase in crystallization, but with an increase in temperature, the crystallization process decreases (that corresponds to the change in the number of structural units for the Face-centered cubic (FCC), Hexagonal Close-Packed (HCP), Body-centered cubic (BCC), and Amorphous (Amor)). The obtained results serve as a basis for experimental research in developing new magnetic materials in the future.

1. Introduction

In recent decades, a major direction from materials science focuses on understanding and applying the properties of matter to develop new multi-component alloys, with improved physical and chemical properties, based on advanced technological methods. In the literature, there are various studies on multi-component alloys (such as grain growth [1], single-phase high-entropy alloys [2], non-equiatomic high-entropy alloys [3], phase stability of equiatomic high-entropy alloys [4], tensile properties of dual-phase high-entropy alloys [5], and so on). On the other hand, it is known that multi-component alloys are considered good candidates to improve the entropy coefficient. In 2004, for the first time, nanostructured high-entropy alloys with multiple principal elements were proposed by Yeh et al. [6] and Cantor et al. [7], and for the first time, scientists made extensive investigations on the maximum value of a high entropy alloy [8]. A number of studies have suggested that high-entropy alloys have unique properties in a variety of applications [9,10,11]. These new findings prompted researchers to explore medium-entropy alloys (MEAs) such as CoCrNi (three-component alloys), that exhibit superior strength to CoCrFeMnNi alloy [12,13,14,15]. In the literature, there are different studies aimed at the mechanical properties of low entropy alloys [6,8,10,12,14,16]. However, so far, only a few studies have used transition metals, such as Fe [17,18], Ni [19,20], Al [21], and Cu [22], in magnetism, thermal, shape memory, soft elastomers, and electrical materials (such as CoCrFeMnNi that exhibits highly complex low-temperature magnetic properties [23]). Recently, scientists have identified the effects of high entropy of mixing and low mixing temperatures, associated with alloys that can form solid solutions randomly in a structural phase, such as Face-centered cubic (FCC) or Body-centered cubic (BCC). In other studies, extensive experimental investigations on high entropy alloys were conducted [24], (e.g., an integrated electromagnetic inductor with FeNiCo [25], FeNiCoCrMn, and its subset [26,27]). Besides the results of the experimental method, there is also a simulation method that plays a great role in the success of studying the properties of new materials. Among the simulation methods, there is Density Functional Theory (DFT) methods, Monte-Carlo (MC) methods, and Molecular Dynamics (MD) simulation methods. With the specified methods, the MD method plays a key role, because of its simplicity. This method, which has been used by researchers since the 1950s [28], was only developed in 1980 thanks to the first IPM computer system. To this day, this method is strongly developed thanks to supercomputer systems combined with theoretical models of solids [29] and has been proven in various studies [30]. In studies based on the simulation method, researchers are always interested in issues such as the stability of materials, and whether the selection of parameters that will be put into the model is consistent with the experimental results. In addition, scientists are also interested in issues such as the sensitive dependence of the initial conditions leading to chaos, and the accuracy of the integration method for the system of large nonlinear partial differential equations [31]. Scientists have published various studies concerning structural characteristics, phase transition, crystallization process, and mechanical and magnetic properties of 2-component alloys (such as NiFe nanoparticles [32], NiCu [33,34,35], AlNi nanoparticles [36], AgAu alloy [37], AuCu bulk [38,39], NiAu alloy [40] and polymer [41], and Fe₂O₃ [42,43]). In the obtained results, the authors have successfully determined the lengths of links of the Fe–Fe, and Fe–Ni. For example, with the simulation method r_Fe–Fe = 2.55 Å [17,18,44,45,46] for amorphous Fe; r_Ni–Ni = 2.45 Å [19,20] for Ni crystallization; r_Fe–Ni = 2.47 Å [32]; and 2.48 Å [47] with 2-component alloys. The following results were obtained based on the experimental method (r_Fe–Fe = 2.54 Å [48]); with the neutron method (r_Fe–Fe = 2.62 Å [49]); with the X-ray method for amorphous Fe (r_Fe–Fe = 2.57 Å [50]); and with the two-component alloys (r_Fe–Ni = 2.53 Å [51]). Currently, scientists have increased the number of components in the alloy to 3 metals and they used experimental methods to study the structural and magnetic properties of the FeCoNi alloy [52]. However, structural features such as bond lengths, number of structural units, shape and phase transitions, and crystallization have not yet been determined. In this research, we apply the method of molecular dynamics to study the structural characteristics, phase transition, and crystallization of the Fe_1-x-yNi_xCo_y alloy, in order to elucidate the cause of the alloy’s magnetic properties and to facilitate the experimental process.

2. Method of Calculation

Initially, we sow randomly atoms of Fe_1-x-yNi_xCo_y alloy with a ratio into a cube of size (l) determined, and it was applied the following formula (1):

$$\mathrm{l}=\sqrt[3]{\frac{\mathrm{N}}{\mathsf{\rho }} }=\sqrt[3]{\frac{{(\mathrm{m}}_{\mathrm{Fe}}{.\mathrm{n}}_{\mathrm{Fe}}{+\mathrm{m}}_{\mathrm{Ni}}{.\mathrm{n}}_{\mathrm{Ni}}{+\mathrm{m}}_{\mathrm{Co}}{.\mathrm{n}}_{\mathrm{Co}})}{\mathsf{\rho }}}$$

(1)

where: l, N, $\mathsf{\rho }$ is the size, the number of atoms, and the density of atoms, respectively, and ${\mathrm{m}}_{\mathrm{Fe}}{, \mathrm{n}}_{\mathrm{Fe}}$, and ${\mathrm{m}}_{\mathrm{Ni}}{, \mathrm{n}}_{\mathrm{Ni}}$, ${\mathrm{m}}_{\mathrm{Co}}{, \mathrm{n}}_{\mathrm{Co}}$ is molar mass atomic and number of atoms of Fe, Ni, Co metals, respectively.

To study the structural features, phase transitions, and crystallization, we use Lammps open-source software [37,53,54] based on the molecular dynamics simulation (MD) method, suitable for periodic boundary conditions and Sutton–Chen embedded force field (2) [53,54,55,56]:

$${\mathrm{F}}_{\mathrm{i}}\left(\mathsf{\rho }\right){=\mathrm{A}}_{\mathrm{i}}{\mathrm{E}}_{\mathrm{i}}^0\mathsf{\rho }\ln \mathsf{\rho };{\mathsf{\rho }}_{\mathrm{i}}^{\mathrm{a}\left(\mathrm{l}\right)}\left(\mathrm{R}\right){=\mathrm{e}}^{{-\mathrm{b}}^{*}}, {\mathrm{b}}^{*}{=\mathsf{\beta }}_{\mathrm{i}}^{\left(\mathrm{l}\right)}\left(\frac{\mathrm{R}}{{\mathrm{R}}_{\mathrm{i}}^0-1}\right),{\left({ \stackrel{-}{\mathsf{\rho }} }_{\mathrm{i}}\right)}^2={\displaystyle \sum _{\mathrm{l}=0}^3{\mathrm{t}}_{\mathrm{i}}^{\left(\mathrm{l}\right)}}{\left({\mathsf{\rho }}_{\mathrm{i}}^{\left(\mathrm{l}\right)}\right)}^2$$

(2)

This is a high-precision embedded interaction potential field for the study of structural characteristics for Fe, Ni, and Co single-component metals [19,20,57], and 2-component alloys [32,47]. Considering interaction force fields [58,59,60,61,62,63] from the physical system can be investigated comprehensively the energy, phase stability, hole formation, and surface binding energy. It is known that for the metal 1 ingredient (that always has the FCC structure stable, and electron density is associated at equilibrium with the value of 1), the derivative of the interaction function will be always 0 to maximize entropy.

To perform the simulation, we use the parameters of Fe_1-x-yNi_xCo_y alloy (corresponding to the values of the component metals Fe, Ni, and Co in Tables 1–3 of references [56,64]). First, we combined the process of running 2 × 10⁴ step recovery statistics of MD simulation at temperature (T), T = 4500 K so that the atoms are in the initial steady state. Then, it is decreased the temperature from T = 4500 K to T = 1300 K, 1100 K, 900 K, 800 K, 700 K, 600 K, 500 K, 400 K, and 300 K (to increase the crystallization state with 42 × 10⁴ MD steps, heating rate 4 × 10¹¹ K/s, and a heating step of 1 fs). In this way, are studied the influence of Fe, Ni, and Co doping concentrations corresponding to alloys Fe₅Ni₃₂Co₆₃, Fe_33.4Ni_33.3Co_33.3, Fe₆₃Ni₃₂Co₅; associated with number of atoms (N), (N = 2916 atoms, 5324 atoms, 8788 atoms, 13,500 atoms of Fe₆₃Ni₃₂Co₅ alloy), and temperature (T), respectively.

To study the structure characteristics quantities through structure shape, and size (l), the Radial Distribution Function (RDF) formula is applied (3) [65]:

$$\mathrm{g}(\mathrm{r})=\frac{\mathrm{V}}{{\mathrm{N}}^2}\langle \frac{{\displaystyle {\sum }_{\mathrm{i}}{\mathrm{n}}_{\mathrm{i}}\left(\mathrm{r}\right)}}{4{\mathsf{\pi }\mathrm{r}}^2\mathsf{\Delta }\mathrm{r}}\rangle$$

(3)

where: r, n_i(r), V, N, and g(r) are the link length, the coordinates, the volume, the number of atoms, and the radial distribution function, respectively. Moreover, g(r) is noted as the density value of the maximum probability of finding the atoms at the first peak of the RDF [66].

To determine the diffusion mechanism of the atoms, we used the Mean Squared Distance (MSD) method (3) [67]. Furthermore, to visualize the structure, phase transition, and crystallization of the alloy, we used the open source software OVITO [63,68] (to determine the RDF, structure shape, and the number of structural unit positions based on Common Neighbor Analysis (CNA) [69,70,71,72,73,74]). It is known that all alloys are made through phase transitions and the Nosé [75] and Hoover [76] laws can be applied in experimental and computational studies. Finally, to check the accuracy of the results, the Displacement Analysis (DXA) was used [68].

3. Results and Discussion

3.1. Characteristic Quantities

Initially, the Fe_1-x-yNi_xCo_y alloy, x = 0.32, y = 0.05 (Fe₆₃Ni₃₂Co₅) with 13,500 atoms corresponding to 8505 Fe atoms, 4320 Ni atoms, and 675 Co atoms were set at T = 4500 K, P = 0 GPa, for recovery statistics, with 2 × 10⁴ steps, simulation step time is 1 fs, and heating rate 4 × 10¹¹ K/s (to obtain initial stabilization for the studied material). Characteristic quantities, structure, phase transition, and crystallization are shown in Figure 1.

The obtained results show that at temperature (T), T = 300 K, the Fe₆₃Ni₃₂Co₅ alloy has the shape of a cube, composed of 03 metals Fe (green), Ni (violet), Co (black), fairly evenly distributed, arranged in an orderly manner (Figure 1a). In addition, there are structural characteristic quantities such as the structured shape (Figure 1b) composed of 04 structural units: Face-centered cubic (FCC) has a red color, Hexagonal Close-Packed (HCP) is blue, Body-centered cubic (BCC) is black, and Amorphous (Amor) is yellow. The radial distribution function has links Fe–Fe, Fe–Ni, Fe–Co, Ni–Ni, Ni–Co, Co–Co corresponding to the lengths of the links r_Fe–Fe = r_Fe–Ni = r_Fe–Co = r_Ni–Ni = r_Ni–Co = r_Co–Co = 2.475 Å. The obtained results are completely consistent with previous simulation results (such as with bond lengths Fe–Fe, Ni–Ni, Fe–Ni, where the corresponding value is r_Fe–Fe = 2.55 Å [17,18,44,45,46] for amorphous Fe; r_Ni–Ni = 2.45 Å [19,20] for Ni crystallization; and r_Fe–Ni = 2.47 Å [32], 2.48 Å [47] with 2-component alloys). Based on the experimental method r_Fe–Fe = 2.54 Å [48]; r_Fe–Fe = 2.62 Å [49] with the neutron method; r_Fe–Fe = 2.57 Å [50] with X-ray method for amorphous Fe; with two component alloys r_Fe–Ni = 2.53 Å [51]. Our computational results are completely consistent with the bond lengths of crystalline metals and have a smaller value for metals in the amorphous state. Currently, there are no studies about the structural characteristics of 3-component alloys. The authors will compare the lengths of the bonds with the bond lengths of the previous 1-component metal or 2-component alloy. Due to the electronic interaction, the lattice constant values of these three-component alloys are approximately equal and in addition, all are ferromagnetic. Moreover, the height g(r) of the radial distribution function (RDF) is g(r)_Fe–Fe = 8.12, g(r)_Fe–Ni = 7.32, g(r)_Fe–Co = 8.20, g(r)_Ni–Ni = 6.92, g(r)_Ni–Co = 7.34, g(r)_Co–Co = 6.76 (Figure 1c). In which, the height g(r) of the radial distribution function (correlation function) is the probability density function of finding the atom in the coordination number circle [66]. Correspondingly, the number of structural units associated with Fe₆₃Ni₃₂Co₅ alloy is 7290 FCC, 4860 HCP, 364 BCC, and 986 Amor (Figure 1d). In addition, at T = 300 K, P = 0 GPa, the size of the alloy (l) corresponds to l = 5.33 nm, the total energy of the system (E_tot), E_tot = −58,263 eV. The specific results for the structure of the Fe₆₃Ni₃₂Co₅ alloy, allow us to study the influencing factors in the following sections.

3.2. Factors Affecting

In order to determine the factors affecting the structure, phase transition, and crystallization process of materials, the authors focus on studying quantities such as structure shape, radial distribution function, and the number of the structural unit.

3.2.1. Effect of Doping Concentration

The obtained results show that, at temperature (T), T = 300 K, P = 0 GPa, the Fe_1-x-yNi_xCo_y alloy with 13,500 atoms associated with x = 0.32, y = 0.63 (Fe₅Ni₃₂Co₆₃) has 13,500 atoms (corresponding to 8505 Fe atoms, 4320 Ni atoms and 675 Co atoms), and its structure shape is shown in Figure 2a1. For this case, the lengths of the links r = 2.475 Å and the g(r) of RDF is g(r)_Fe–Ni = 7.01, g(r)_Fe–Co = 7.19, and g(r)_Ni–Co = 7.35 (Figure 2b1). The number of the structural unit is 7060 FCC, 4460 HCP, 575 BCC, and 1405 Amor as it is shown in Figure 2c1, the size of the alloy (l) corresponds to l = 5.34 nm, and the total energy of the system (E_tot), E_tot = −58,189 eV. When changes x = y (corresponding to x = y = 0.333) (Fe_33.4Ni_33.3Co_33.3), and x = 0.32, y = 0.05 (Fe₆₃Ni₃₂Co₅), the concentration of doped Fe increases, Co decreases corresponding to the number of atoms. The Fe, Ni, Co, and structural shape change major (Figure 2a1–a3). Similarly, links lengths do not change r = 2.475 Å and the g(r) of RDF varies greatly between g(r)_Fe–Ni = 6.42 to g(r)_Fe–Ni = 7.32, g(r)_Fe–Co = 6.60 to g(r)_Fe–Co = 8.20, g(r)_Ni–Co = 6.97 to g(r)_Ni–Co = 7.35 (Figure 2b1–b3). Furthermore, with the increase of impurities Fe or Co both lead to an increase in g(r), which proves that Fe, Co metal has a smaller lattice constant than Ni metal (making honey larger atoms). In addition, the number of the structural unit varies greatly, corresponding to FCC decreasing and increasing, HCP increasing and decreasing, BCC increasing and decreasing, and Amor increasing and decreasing (Figure 2c1–c3) resulting in a change in the size of the alloy (l) that decreases from l = 5.34 to l = 5.33 nm, and the total energy of the system (E_tot) increases and then decreases from E_tot = −58,189 eV to −57,932 and −58,263 eV. The obtained results show that, when it is changed the doping concentration, the number of FCC, BCC, and Amor structural units increases (in Fe₅Ni₃₂Co₆₃, and Fe₆₃Ni₃₂Co₅), which shows the fact when increasing the concentration of Fe, Co doping leads to Fe_1-x-yNi_xCo_y alloy crystallization increases, but when increases the concentration of Ni doping, crystallization decreases. This is a difficult question for researchers as to why the difference in the crystallization process occurs when these metals are all magnetic metals, with nearly equal lattice constants. After the research process, we found that the root cause of this problem is caused by the electronic interaction between metals. In addition, with Fe₆₃Ni₃₂Co₅, there is the largest crystallization (corresponding to the total binding energy of the system that has the smallest value). The obtained results have an important impact on future experimental studies on the influence of doping concentration with 3-metal alloys. We choose Fe₆₃Ni₃₂Co₅ alloy as the standard material to investigate the influencing factors in the next section.

3.2.2. Effect of Number of Atoms

The obtained results show that, at temperature (T), T = 300 K, P = 0 GPa the Fe₆₃Ni₃₂Co₅ alloy with 2916 atoms has the structure shape (Figure 3a1), the lengths of the links r_Fe–Ni = r_Ni–Co = 2.475 Å, r_Fe–Co = 2.525 Å and the g(r) of RDF is g(r)_Fe–Ni = 8.28, g(r)_Fe–Co = 7.20, g(r)_Ni–Co = 8.25 (Figure 3b1). The number of the structural unit of FCC, HCP, BCC, Amor (Figure 3c1), and the size of the alloy (l) corresponds to l = 3.20 nm, the total energy of the system (E_tot), E_tot = –12,657 eV. When it is increased the number of atoms from N = 2916 atoms to N = 5324, 8788, 13,500 atoms, the shape of the structure changes greatly, corresponding to an increase in the density of structural atoms (Figure 3a1–a4). At the same time, r_Fe–Ni = r_Ni–Co = 2.475 Å, especially for r_Fe–Co when decreases from r_Fe–Co = 2.525 Å to r_Fe–Co = 2.475 Å; also, g(r) of RDF changed, the g(r)_Fe–Ni changed down in the range from g(r)_Fe–Ni = 8.28 to g(r)_Fe–Ni = 7.01; g(r)_Fe–Co changes up from g(r)_Fe–Co = 6.40 to g(r)_Fe–Co = 8.20; g(r)_Ni–Co varies from g(r)_Ni–Co = 8.25 to g(r)_Ni–Co = 5.97 (Figure 3b1–b4) and number of structural unit of FCC increased from 1741 FCC to 7290 FCC, HCP increased from 1063 HCP to 4860 HCP, BCC increased from 18 BCC to 364 BCC, Amor increased from 94 Amor to 986 Amor (Figure 3c1–c4), and the size of the alloy (l) corresponds to an increase from l = 3.20 nm to l = 5.34 nm; the total energy of the system (E_tot) decreases from E_tot = −12,657 eV to E_tot = −58,263 eV. The obtained results show that when increased the number of atoms leads to structural units FCC, HCP, BCC increase, and Amor decreases (the cause of increased crystallization is by the size effect cause). We choose Fe₆₃Ni₃₂Co₅ alloy with 13,500 atoms as the standard material to investigate influencing factors in the next section.

3.2.3. Effect of Temperature

Similarly, to determine the effect of temperature on the structure, through the phase transition and crystallization process of Fe₆₃Ni₃₂Co₅ alloy, we only need to investigate the total energy value of the system and the number of crystal structure units of materials at the respective temperature. The obtained results are shown in

Table 1. Parameters associated with the structure of Fe₆₃Ni₃₂Co₅ alloy with 13,500 atoms at different temperatures.

Temperature (K)	300	500	700	900	1100	1300
Etot (eV)	−58,263	−57,941	−57,610	−57,275	−56,938	−56,630
Number of crystalline structure units	12,514	12,496	12,462	12,389	12,306	12,137

.

The obtained results show that, at temperature (T), T = 300 K, P = 0 GPa, the Fe₆₃Ni₃₂Co₅ alloy with 13,500 atoms have the lengths of the links with a constant value r = 2.475 Å, and the g(r) of RDF changes in a corresponding way. In addition, the number of crystalline structure units (FCC, HCP, BCC) is 12,514 atoms; the size of the alloy (l) corresponds to l = 5.34 nm, the total energy of the system (E_tot), E_tot = −58,263 eV. When increasing the temperature from T = 300 K to T = 500, 700, 900, 1100, 1300 K, the RDF changes correspond separately with the corresponding decrease in the number of crystallographic units from 12,514 atoms to 12,496, 12,462, 12,389, 12,306, 12,137 atoms (Table 1). Moreover, the size of the alloy has a constant value r = 2.475 Å, and the total energy of the system decrease from E_tot = −58,263 eV to E_tot = −57,941, −57,610, −57,275, −56,938, −56,630 eV (Table 1). The obtained results show that, when increased the temperature with Fe₆₃Ni₃₂Co₅ alloy of 13,500 atoms, the number of crystallographic units decreases, and Amor increases, indicating that Fe₆₃Ni₃₂Co₅ alloy of 13,500 atoms decreases, the crystallinity increase, and transfer gradually to the liquid state.

In addition, the relationship between temperature and total energy of the system has a close relationship with each other when increasing temperature leads to increased energy (according to Figure 4).

The results show that the relationship between T, E_tot has almost linear values and is interrupted at the point with the value T = 498 K. This point is called the glass point or glass temperature (T_g), T = T_g = 498 K. Moreover, some studies by the simulation study [22] confirmed that the cause of this phase transition is the size effect (surface effect). The obtained results are completely consistent with the experimental results with T_g = 498 K [77]. Based on these results, a major contribution to future experimental studies is determining the glass temperature of 3-component alloys (Figure 4).

In addition, our computational studies show that, when increasing the concentration of Fe and Co doping, the crystallization process increases, and when increasing Ni, the crystallization process decreases. Similarly, increasing the number of atoms leads to an increase in the crystallization process, and as the temperature increases, the crystallization process decreases. These results show that, with Fe, Ni, and Co 3-metal alloys, the bond lengths are constant, while the energy increases with increasing temperature, and decreases with increasing of the number of atoms. These results can be applied in the manufacturing of magnetic nano-alloy materials.

4. Conclusions

In this work, the structural characteristics, phase transition, and crystallization of Fe_1-x-yNi_xCo_y alloy under the influence of various factors (such as doping concentration, number of atoms, and temperature) were investigated. The obtained results show that in the Fe_1-x-yNi_xCo_y alloy always exist 03 metals Fe, Ni, and Cu (that are distributed quite evenly according to the ratio of tap phase concentration). In Fe_1-x-yNi_xCo_y alloy, there are always six types of links, Fe–Fe, Fe–Ni, Fe–Co, Ni–Ni, Ni–Co, and Co–Co. The structural features such as length (r), height of the radial distribution function g(r) of links Fe–Fe, Fe–Ni, Ni–Co has a constant value such as r = 2.475 Å, and g(r) changes (from g(r)_Fe–Ni = 6.42 to g(r)_Fe–Ni = 7.32, g(r)_Fe–Co = 6.60 to g(r)_Fe–Co = 8.20, g(r)_Ni–Co = 6.97 to g(r)_Ni–Co = 7.35) with a change of doping concentration Fe, Co. The result shows that when the increase of Fe and Co doping concentrations, the crystallization process increases corresponding with Fe₅Ni₃₂Co₆₃, and Fe₆₃Ni₃₂Co₅ alloy. Moreover, with the increase of Ni, the crystallization process decreases corresponding with Fe_33.4Ni_33.3Co_33.3 alloy. These results correspond with the number of structural units: FCC decreases and increases, HCP increases and decreases, BCC increases and decreases, Amor increases and decreases, and l decreases from l = 5.34 nm to l = 5.33 nm, E_tot increases from E_tot = −58,189 eV to −57,932 and −58,263 eV. In particular, Fe₆₃Ni₃₂Co₅ is the alloy with the highest crystallization caused by the interaction between electronic structures. Similarly, an increase in the number of atoms leads to an increase in crystallization, and an increase in temperature leads to a decrease in crystallization. Furthermore, computational results highlighted the glass temperature of Fe₆₃Ni₃₂Co₅ alloy has the value of T_g = 498 K, which is in accordance with experimental results. The obtained results serve as a basis for experimental studies in developing new magnetic materials in the future.