Thermodynamic calculation of high zinc-containing Al-Zn-Mg-Cu alloy

Phase fraction and solidification path of high Zn-containing Al-Zn-Mg-Cu series aluminum alloy were calculated by calculation of phase diagram （CALPHAD） method. Microstructure and phases of Al-9.2Zn-1.7Mg-2.3Cu alloy were studied by X-ray diffraction （XRD）, differential scanning calorimetry （DSC） and scanning electron microscopy （SEM）. The calculation results show that η（MgZn2） phase is influenced by Zn and Mg. Mass fractions of η（MgZn2） in Al-xZn-1.7Mg-2.3Cu are 10.0%, 9.8% and 9.2% for x=9.6, 9.4, 8.8 （mass fraction, %）, respectively. The intervals of Mg composition were achieved for θ（Al2Cu）＋η（MgZn2）, S（Al2CuMg）＋η（MgZn2） and θ（Al2Cu）＋S（Al2CuMg）＋η（MgZn2） phase regions. Al3Zr, α（Al）, Al13Fe4, η（MgZn2）, α-AlFeSi, Al7Cu2Fe, θ（Al2Cu）, Al5Cu2MgsSi6 precipitate in sequence by no-equilibrium calculation. The SEM and XRD analyses reveal that α（Al）, η（MgZn2）, Mg（Al,Cu,Zn）2, θ（Al2Cu） and Al7Cu2Fe phases are discovered in Al-9.2Zn-1.7Mg-2.3Cu alloy. The thermodynamic calculation can be used to predict the major phases present in experiment.

Composition design of high yield strength points in single-phase Co-Cr-Fe-Ni-Mo multi-principal element alloys system based on electronegativity,thermodynamic calculations,and machine learning

A method which combines electronegativity difference,CALculation of PHAse Diagrams(CALPHAD) and machine learning has been proposed to efficiently screen the high yield strength regions in Co-Cr-Fe-Ni-Mo multi-component phase diagram.First,the single-phase region at a certain annealing temperature is obtained by combining CALPHAD method and machine learning,to avoid the formation of brittle phases.Then high yield strength points in the single-phase region are selected by electronegativity difference.The yield strength and plastic deformation behavior of the designed Co_(14)Cr_(30)Ni_(50)Mo_(6)alloy are measured to evaluate the proposed method.The validation experiments indicate this method is effective to predict high yield strength points in the whole compositional space.Meanwhile,the interactions between the high density of shear bands and dislocations contribute to the high ductility and good work hardening ability of Co_(14)Cr_(30)Ni_(50)Mo_(6)alloy.The method is helpful and instructive to property-oriented compositional design for multi-principal element alloys.

Experimental investigation and thermodynamic assessment of La-Y-Ni ternary system in Ni-rich corner

La-Y-Ni alloys exhibit high discharge capacity due to the formation of AB_(3-3.8)-type(A=La,Y;B=Ni)intermetallic compounds.However,the stable composition and temperature range for this type of phase are rarely reported,which restrains the development of La-Y-Ni hydrogen storage alloys with stable structure and high capacity.This paper focuses on the phase equilibria of the La-Y-Ni ternary system in Ni-rich corner.The phase constitution,microstructure,and equilibrated composition were experimentally determined at 1273 and 1148 K using X-ray diffraction(XRD),scanning electron microscopy(SEM),and energy-dispersive spectroscopy(EDS).The solubilities of La and Y in the binary compounds were measured.Two ternary compounds,3R-LaY_(2)Ni_(9)with the structure of PuNi3 type and La_(0.5)Y_(0.5)Ni_(5)with the structure of CaCu5 type,existed at both temperatures.Based on the experimental data,the thermodynamic description of LaY-Ni system was assessed by Calculation of Phase Diagram method.The calculated isothermal sections agree with the experimental data.The thermodynamic database is helpful for the design of La-Y-Ni hydrogen storage alloys.

Thermodynamic Modeling of KF-CrF3 Binary System

A comprehensive thermodynamic model of KF-CrF3 system was established. The intermediate phases K2Cr5F17, KCrF4, K2CrF5 and K3CrF6 were described by the stoichiometric compound model and the liquid phase by associated solution model. All the model parameters were optimized by the experimental phase equilibria data as- sisted by the first-principles prediction within the framework of the calculation of phase diagram（CALPHAD） me- thod. It is demonstrated that the calculated results are fairly consistent with the experimental data, thus we obtained a set of self-consistent and reliable thermodynamic parameters which could well describe the phase equilibria and thermodynamic properties of KF-CrF3 system.

Integrating machine learning and CALPHAD method for exploring low-modulus near-β-Ti alloys

Traditional theoretical and empirical calculation methods can guide the design of β-and metastable β-alloys for bio-titanium. However, it is still difficult to obtain novel near-β-Ti alloys with low modulus. This study developed a method that combines machine learning with calculation of phase diagrams(CALPHAD) to facilitate the design of near-β-Ti alloys. An elastic modulus database of Ti–Nb–Zr–Mo–Ta–Sn system was constructed first, and then three features(the electron to atom ratio, mean absolute deviation of atom mass, and mean electronegativity) were selected as the key factors of modulus by performing a three-step feature selection. With these features, a highly accurate model was built for predicting the modulus of near-β-Ti alloys. To further ensure the accuracy of modulus prediction, machine learning with the elastic constants calculated was leveraged by CALPHAD database. The root mean square error of the well-trained model can be as low as 6.75 GPa. Guided by the prediction of machine learning and CALPHAD, three novel near-β-Ti alloys with elastic modulus below 50 GPa were successfully designed in this study. The best candidate alloy(Ti–26Nb–4Zr–4Sn–1Mo–Ta) exhibits an ultra-low modulus(36.6 GPa) after cold rolling with a thickness reduction of 20%. Our method can greatly save time and resources in the development of novel Ti alloys, and experimental verifications have demonstrated the reliability of this method.