Designing metallic glasses with optimal combinations of glass-forming ability and mechanical properties

doi:10.1016/j.jmst.2020.08.028

Abstract

Abstract:

It is a long-standing challenge to search for metallic glasses (MGs) with optimal combinations of glass-forming ability (GFA), strength and toughness in the vast compositional space. By taking into account both recently developed ellipse criterion and temperature-based GFA criterion, here we established quantitative correlations among compositions, elastic constants, GFA and mechanical properties of MGs, which enable to predict the GFA, fracture strength and fracture surface simultaneously in advance once the compositions of MGs are determined. Experimental data confirm the validity of this approach in prediction. Finally, a strategy for designing MGs with optimal combinations of strength, toughness and GFA is proposed, which allows for high-throughput discovering glass formers with excellent mechanical properties.

Key words: Metallic glass, Composition, Elastic constant, Mechanical property, Glass-forming ability

S.J. Wu, Z.Q. Liu, R.T. Qu, Z.F. Zhang. Designing metallic glasses with optimal combinations of glass-forming ability and mechanical properties[J]. J. Mater. Sci. Technol., 2021, 67: 254-264.

Figures/Tables 11

Fig. 1. Schematic illustration to show the relations among compositions, elastic constants, glass-forming ability (GFA) and mechanical properties in MGs, as well as the strategy to design the large-size, high-strength or high-toughness BMGs.

Table 1 Fitted values for the parameters a, b, c, d, k1 and k2 in different alloy systems of MGs. The values of a, b, c and d were obtained from Ref [40].

Metallic glass	a	b	c	d	k₁	k₂
Zr (f_Be < 15 at. %)	3.1599	0.3435	2.8291	0.2809	0.85	1.00
Zr (f_Be ≥ 15 at. %)	3.2553	0.3340	3.1328	0.3163	0.85	1.00
Cu	2.6686	0.2580	2.4942	0.2296	1.00	1.00
Mg	2.1520	0.2477	2.9517	0.3896	1.00	0.63
Ni	2.2876	0.1875	1.5255	0.0927	0.80	1.00
Ca	2.2215	0.4102	3.0734	0.5972	1.00	1.00
Sr	2.0131	0.3743	2.4093	0.4837	1.00	1.00
La	3.1457	0.5101	1.5232	0.1546	1.00	1.00
Ce	3.0636	0.4870	2.1652	0.3246	0.90	0.95
Pr	3.0492	0.4654	2.7942	0.4196	0.85	0.90
Tm	3.0999	0.3539	2.1500	0.2402	1.00	1.00

Fig. 2. Summarization of the comparisons between the experimental elastic constants [33,41,42] and the predicted elastic constants: (a) shear modulus and (b) bulk modulus. The full lines represent the ideal tendency while the dashed lines represent the error of ± 10%.

Fig. 3. Correlations of the characteristic temperatures with the elastic constants for various different MGs. (a) The relation between glass transition temperature (Tg) and Young’s modulus (E) [33]. (b) The relation between crystallization temperature (Tx) and bulk modulus (K). (c) The relation between liquidus temperature (Tl) and E. The experimental values of elastic constants and characteristic temperatures were obtained from Ref [33,50,52,53]. (a) is adapted with permission from Ref [33].

Fig. 4. Summarization of the comparisons between the experimental data [33,42,45,62] and the predicted properties: (a) parameter $\gamma ={{T}_{\text{x}}}/({{T}_{\text{g}}}+{{T}_{\text{l}}})$, (b) facture strength and (c) Poisson’s ratio (ν). The solid lines and the dashed lines indicate the ideal tendency and ± 10% error, respectively.

Fig. 5. Failure surfaces predicted by the proposed approach and the verification by experimental data [58,64,65]. (a) Failure surface of Zr41Ti14Cu12.5Ni10Be22.5 in ${{\sigma }_{\text{xx}}}$- ${{\sigma }_{\text{yy}}}$ principal stress space. (b) Failure surface of Zr52.5Ni14.6Al10Cu17.9Ti5 in σ - τ stress space. The red solid lines and blue dots represent the predicted failure surfaces and experimental data, respectively. The blue, purple and green dashed lines indicate the Mohr’s circles under compression, shear and tension, respectively.

Fig. 6. Comparisons of composition-property maps between the experimental results [24,52] and the predictions. (a1) The calculated parameter $\gamma ={{T}_{\text{x}}}/({{T}_{\text{g}}}+{{T}_{\text{l}}})$ map of Ca-Mg-Cu alloys. (b1)-(c1) The calculated (b1) strength and (c1) Poisson’s ratio (ν) maps of Cu-Zr-Ag alloys. (a2) The experimental GFA map of Ca-Mg-Cu alloys. (b2)-(c2) The experimental (b2) strength and (c2) plasticity of Cu-Zr-Ag alloys. The measured experimental maximum and minimum values are indicated by arrows.

Fig. 7. Comparisons between the experimental data [24] and the predicted results. (a) The dependence of experimental and calculated compressive fracture strength on Ag content for the (Cu0.5Zr0.5)100-xAgx MGs. (b) The variations of experimental plasticity and calculated Poisson’s ratio with increasing Ag content for the (Cu0.5Zr0.5)100-xAgx MGs.

Fig. 8. Calculated property maps of a new designed Zr-Cu-Mg alloy system: (a) compressive fracture strength, (b) tensile fracture angle, (c) Poisson’s ratio and (d) parameter $\gamma ={{T}_{\text{x}}}/({{T}_{\text{g}}}+{{T}_{\text{l}}})$. The compositions of the highest strength, lowest tensile fracture angle, highest Poisson’s ratio and best γ are indicated by arrows, respectively.

Fig. 9. Relations among compressive fracture strength, tensile fracture angle, Poisson’s ratio and parameter $\gamma ={{T}_{\text{x}}}/({{T}_{\text{g}}}+{{T}_{\text{l}}})$ in a new designed Zr-Cu-Mg alloy system.

Fig. 10. Designing strategy for MGs with optimized size-strength-toughness combination.

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