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The classification of miscible and immiscible systems of binary alloys plays a critical role in the design of multicomponent alloys. By mining data from hundreds of experimental phase diagrams, and thousands of thermodynamic data sets from experiments and high-throughput first-principles (HTFP) calculations, we have obtained a comprehensive classification of alloying behavior for 813 binary alloy systems consisting of transition and lanthanide metals. Among several physics-based descriptors, the slightly modified Pettifor chemical scale provides a unique two-dimensional map that divides the miscible and immiscible systems into distinctly clustered regions. Based on an artificial neural network algorithm and elemental similarity, the miscibility of the unknown systems is further predicted and a complete miscibility map is thus obtained. Impressively, the classification by the miscibility map yields a robust validation on the capability of the well-known Miedema’s theory (95% agreement) and shows good agreement with the HTFP method (90% agreement). Our results demonstrate that a state-of-the-art physics-guided data mining can provide an efficient pathway for knowledge discovery in the next generation of materials design.

Taking pure Mg, Mg-Al and Mg-Zn as prototypes, the effects of strain on the stacking fault energies (SFEs), dislocation core structure and Peierls stress were systematically investigated by means of density-functional theory and the semidiscrete variational Peierls-Nabarro model. Our results suggest that volumetric strain may significantly influence the values of SFEs of both pure Mg and its alloys, which will eventually modify the dislocation core structure, Peierls stress and preferred slip system, in agreement with recent experimental results. The so-called "strain factor" that was previously proposed for the solute strengthening could be justified as a major contribution to the strain effect on SFEs. Based on multivariate regression analysis, we proposed universal exponential relationships between the dislocation core structure, the Peierls stress and the stable or unstable SFEs. Electronic structure calculations suggest that the variations of these critical parameters controlling strength and ductility under strain can be attributed to the strain-induced electronic polarization and redistribution of valence charge density at hollow sites. These findings provide a fundamental basis for tuning the strain effect to design novel Mg alloys with both high strength and ductility.

Dislocation is one of the most critical and fundamental crystal defects that dominate the mechanical behavior of crystalline solids, however, a quantitative determination of its character and property in experiments is quite challenging and limited so far. In this paper, a fully automated Peierls-Nabarro (P-N) analyzer named PNADIS is presented; a complete set of the character and property of dislocation can be automatically derived, including the dislocation core structure, Peierls energy and stress, pressure field around dislocation core, solute/dislocation interaction energy, as well as the energy barrier and yield stress at 0K for solid solution strengthening. Furthermore, both one-dimensional (1D) and two-dimensional (2D) P-N models are implemented to meet the demand to analyze the character and property of dislocation for not only simple FCC and HCP structures but also complex crystals. The implementation of this code has been critically validated by a lot of evaluations and tests including 1D P-N model for complex crystals, 2D P-N model for FCC and HCP metals, pressure field around dislocation core, and solid solution strengthening for alloys. We expect that the automated feature of this code would provide a high-efficiency solution for determining the character and property of dislocation. Program summary Program title: PNADIS Licensing provisions: GNU General Public License 3Programming language: MATLAB Nature of problem: To determine automatically the character and property of dislocation, including dislocation core structure, Peierls stress, pressure field around dislocation core and solid solution strengthening, for not only FCC and HCP structures but also complex crystals.Solution method: The generalized stacking fault energy is firstly fitted by Fourier expansion, and meanwhile an appropriate trial function of disregistry vector is chosen. Afterwards, a least square minimization of the difference between elastic resistance and restoring force for onedimensional Peierls-Nabarro model, or a global minimization of the total dislocation energy via particle swarm optimization or genetic algorithm for two-dimensional Peierls-Nabarro model, will be performed to determine the dislocation core structure of complex crystals, or FCC and HCP structures. Finally, the Peierls stress, pressure field around dislocation core and solid solute strengthening are derived from the calculated dislocation core structure.For the first category, the atomistic description, e.g. flexible boundary conditions [8][9][10] and dislocation dipole array [11,12], is that the dislocation cores are characterized explicitly in an atom-by-atom manner [7], in which the atomic structure is determined directly by ab initio density functional theory (DFT) calculation or molecular statics/dynamics simulation. Unfortunately, each approach shows some inherent shortcomings: the ab initio DFT calculation are very expensive computationally as several hundreds of atoms are required for dislocation simulation albeit they are accurate; while the molec...