Generalized stacking fault energies of alloys

Design metastability in high-entropy alloys by tailoring unstable fault energies

Metastable alloys with transformation-/twinning-induced plasticity (TRIP/TWIP) can overcome the strength-ductility trade-off in structural materials. Originated from the development of traditional alloys, the intrinsic stacking fault energy (ISFE) has been applied to tailor TRIP/TWIP in high-entropy alloys (HEAs) but with limited quantitative success. Here, we demonstrate a strategy for designing metastable HEAs and validate its effectiveness by discovering seven alloys with experimentally observed metastability for TRIP/TWIP. We propose unstable fault energies as the more effective design metric and attribute the deformation mechanism of metastable face-centered cubic alloys to unstable martensite fault energy (UMFE)/unstable twin fault energy (UTFE) rather than ISFE. Among the studied HEAs and steels, the traditional ISFE criterion fails in more than half of the cases, while the UMFE/UTFE criterion accurately predicts the deformation mechanisms in all cases. The UMFE/UTFE criterion provides an effective paradigm for developing metastable alloys with TRIP/TWIP for an enhanced strength-ductility synergy.

Effect of Temperature on the Deformation Behavior of Copper Nickel Alloys under Sliding

The microstructural evolution in the near-surface regions of a dry sliding interface has considerable influence on its tribological behavior and is driven mainly by mechanical energy and heat. In this work, we use large-scale molecular dynamics simulations to study the effect of temperature on the deformation response of FCC CuNi alloys of several compositions under various normal pressures. The microstructural evolution below the surface, marked by mechanisms spanning grain refinement, grain coarsening, twinning, and shear layer formation, is discussed in depth. The observed results are complemented by a rigorous analysis of the dislocation activity near the sliding interface. Moreover, we define key quantities corresponding to deformation mechanisms and analyze the time-independent differences between 300 K and 600 K for all simulated compositions and normal pressures. Raising the Ni content or reducing the temperature increases the energy barrier to activate dislocation activity or promote plasticity overall, thus increasing the threshold stress required for the transition to the next deformation regime. Repeated distillation of our quantitative analysis and successive elimination of spatial and time dimensions from the data allows us to produce a 3D map of the dominating deformation mechanism regimes for CuNi alloys as a function of composition, normal pressure, and homologous temperature.

Machine Learning Enabled Prediction of Stacking Fault Energies in Concentrated Alloys

Recent works have revealed a unique combination of high strength and high ductility in certain compositions of high-entropy alloys (HEAs), which is attributed to the low stacking fault energy (SFE). While atomistic calculations have been successful in predicting the SFE of pure metals, large variations up to 200 mJ/m2 have been observed in HEAs. One of the leading causes of such variations is the limited number of atoms that can be modeled in atomistic calculations; as a result, due to random distribution of elements in HEAs, various nearest neighbor environments may not be adequately captured in small supercells resulting in different SFE values. Such variation further increases with the increase in the number of elements in a given composition. In this work, we use machine learning to overcome the limitation of smaller system sizes and provide a methodology to significantly reduce the variation and uncertainty in predicting SFEs. We show that the SFE can be accurately predicted across the composition ranges in binary alloys. This capability then enables us to predict the SFE of multi-elemental alloys by training the model using only binary alloys. Consequently, SFEs of complex alloys can be predicted using a binary alloys database, and the need to perform calculations for every new composition can be circumvented.

Generalized Stacking Fault Energy of Al-Doped CrMnFeCoNi High-Entropy Alloy

Using first-principles methods, we investigate the effect of Al on the generalized stacking fault energy of face-centered cubic (fcc) CrMnFeCoNi high-entropy alloy as a function of temperature. Upon Al addition or temperature increase, the intrinsic and extrinsic stacking fault energies increase, whereas the unstable stacking fault and unstable twinning fault energies decrease monotonously. The thermodynamic expression for the intrinsic stacking fault energy in combination with the theoretical Gibbs energy difference between the hexagonal close packed (hcp) and fcc lattices allows one to determine the so-called hcp-fcc interfacial energy. The results show that the interfacial energy is small and only weakly dependent on temperature and Al content. Two parameters are adopted to measure the nano-twinning ability of the present high-entropy alloys (HEAs). Both measures indicate that the twinability decreases with increasing temperature or Al content. The present study provides systematic theoretical plasticity parameters for modeling and designing high entropy alloys with specific mechanical properties.

Generalized Stacking Fault Energies of Aluminum Alloys–Density Functional Theory Calculations

Generalized stacking fault energies of aluminum alloys were calculated using density functional theory. Stacking fault energy of aluminum alloys was correlated with the d-electrons number of transition metal alloying elements. The tendency to twinning is also modified by the presence of the alloying element in the deformation plane. Our results suggest that Al alloys, with such elements as Zr, Nb, Y, Mo, Ta, and Hf, are expected to exhibit a strong work hardening rate due to emission of the partial dislocations.

Twinning in metastable high-entropy alloys

Twinning is a fundamental mechanism behind the simultaneous increase of strength and ductility in medium- and high-entropy alloys, but its operation is not yet well understood, which limits their exploitation. Since many high-entropy alloys showing outstanding mechanical properties are actually thermodynamically unstable at ambient and cryogenic conditions, the observed twinning challenges the existing phenomenological and theoretical plasticity models. Here, we adopt a transparent approach based on effective energy barriers in combination with first-principle calculations to shed light on the origin of twinning in high-entropy alloys. We demonstrate that twinning can be the primary deformation mode in metastable face-centered cubic alloys with a fraction that surpasses the previously established upper limit. The present advance in plasticity of metals opens opportunities for tailoring the mechanical response in engineering materials by optimizing metastable twinning in high-entropy alloys.

Twinning has been experimentally seen in high-entropy alloys, but understanding how it operates remains a challenge. Here, the authors show that twinning can be a primary deformation mechanism in three well-known medium- and high-entropy alloys that have unstable face-centered cubic lattices.

Step Coalescence by Collective Motion at an Incommensurate Grain Boundary

Using extended time series scanning transmission electron microscopy, we investigate structural fluctuations at an incommensurate grain boundary in Au. Atomic-resolution imaging reveals the coalescence of two interfacial steps, or disconnections, of different height via coordinated motion of atoms along close-packed directions. Numerical simulations uncover a transition pathway that involves constriction and expansion of a characteristic stacking fault often associated with grain boundaries in face-centered cubic materials. It is found that local atomic fluctuations by enhanced point defect diffusion may play a critical role in initiating this transition. Our results offer new insights into the collective motion of atoms underlying the lateral advance of steps that control the migration of faceted grain boundaries.