Tailoring stacking fault energy (SFE) is an effective way for enhancing mechanical properties of certain high entropy alloys (HEAs) such as the prototype Cantor alloy. However, the underlying mechanism, especially the atomistic origins for the enhanced plasticity and strength, is still unclear. In this work, we performed molecular dynamics simulations to investigate the mechanical behavior of CoxNi40−xCr20Fe20Mn20 (x = 10, 20, and 30 at. %) HEAs under tensile loading. The results show that the SFE decreases with the increase in Co concentration and favors the formation of continuous stacking fault networks on which multiple plastic deformation carriers including stacking faults, dislocations, twins, and martensitic transformation were sequentially activated. The activation and complex interaction of these multiple carriers mainly contribute to the improved plasticity, and the increased stair-rod dislocations result in the enhanced strength in Co30Ni10Cr20Fe20Mn20 HEA. The current findings may be important for the understanding of SFE effects at the atomistic scale and also shed light on designing of high-performance HEAs.
Traditional alloy design depends heavily on “trial and error” experiments, which are neither cost-effective nor efficient, particularly for the development of high-entropy alloys (HEAs) using a broad composition space. Herein, we combine a machine learning (ML) model with phase diagram calculations (CALPHAD) to design Ti-Zr-Nb-Ta refractory HEAs with a desirable hardness. The extreme gradient boosting (XGBoost) algorithm is used to train the ML model based on the Ti-Zr-Nb-Ta HEA hardness dataset from CALPHAD-assisted experiments. As a result, the most important features (i.e., the Ta content, melting point, and entropy of mixing) are determined via feature selection and model optimization. Moreover, the high performance of the ML model is validated experimentally, and the prediction accuracy reaches 97.8%. This work provides not only an interpretable ML model that can be used to predict the hardness of Ti-Zr-Nb-Ta HEAs but also feasible guidance for the development of HEAs with desirable hardness.
Effects of Sn doping at Ru site on the structural, magnetic, and transport behavior of polycrystalline SrRu 1−x Sn x O 3 (x ≤ 0.1) have been investigated here. Substitution of Sn 4+ for Ru 4+ remains the same crystal symmetry with that of Sn-free SrRuO 3 , while induces the Ru(Sn)O 6 octahedral distortions. Samples with the low doping concentration (x ≤ 0.08) show a metallic behavior at high temperature, while a metal to insulator transition occurs at low temperature. On the other hand, an insulator behavior is detected for sample with x = 0.1, which follows Arrhenius-type process in the temperature range of 80-140 K and Mott's variable range hopping model in the temperature range of 140-300 K. Further, we find that Sn 4+ has a significant effect on the magnetic behavior of Sn doping in SrRuO 3 where ferromagnetic transition temperature and magnetic moment decrease rapidly due to octahedral distortion and site dilution.
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