Machine learning prediction of the electronic property of binary transition metal alloys

Machine learning methods have garnered much attention and use in computational catalysis. Previous studies have demonstrated rapid and accurate prediction of a variety of catalytic properties as well as the underlying potential energy landscapes. In particular, d-band center, defined as the first moment of the d-projected density of states, has been widely used as the key descriptor of activity trends for reactions catalyzed by metal surfaces. In this work, we construct a gradient boosting regression (GBR) model for prediction of the d-band center of bulk binary transition metal alloys. An accurate model is obtained using a dataset of over 1200 alloys from the Materials Project database spanning the entire d-block of the periodic table. The d-band centers, periodic groups, and relative compositions of the constituent metals are determined to have the highest feature importance scores, consistent with the underlying physics of the alloy. The regression model presented here offer a promising strategy of rapid property prediction with physical interpretability to aid the optimization and discovery of efficient heterogeneous catalysts.

Achieving strong and stable nanocrystalline Al alloys through compositional design

Al alloys often suffer from low mechanical strength and lack high-temperature microstructural and mechanical robustness. A series of binary and ternary nanocrystalline (NC) Al transition metal alloys with supersaturated solid solution and columnar nanograins have been recently developed by using magnetron sputtering, manifesting a new realm of mechanical properties and thermal stability. Distinct solutes cause evident differences in the phase transformations and efficiencies for grain refinement and crystalline-to-amorphous transition. Certain sputtered Al-TM alloys have shown room-temperature mechanical strengths greater than 2 GPa and outstanding thermal stability up to 400 °C. In addition, the NC Al alloys show mechanical anisotropy and tension–compression asymmetry, revealed by micromechanical tests. Through the process encapsulating various compositionally distinct systems, we attempt to illuminate the solute effects on grain refinement and properties and more importantly, tentatively unravel the design criteria for high-strength and yet thermally stable NC Al alloys. Graphic Abstract

Morphology of the surface of d-transition metal alloys of the IV period after CBN grinding

Studies have been carried out when grinding alloys based on titanium, vanadium, chromium, iron, cobalt and nickel. According to the condition of the neat surface, the alloys are divided into groups. The regularities of changes in the roughness parameters of Ra and Rsm are investigated. The parameter of the average density of the peaks of the grains forming the elements of the surface roughness profile has been introduced, the relationship of the introduced parameter with Ra is shown. It is established that when grinding all alloys, the treated surface is impregnated by the wear products of the abrasive tool. Electronic photographs of objects are given. The possible sizes of embedded crystals are determined.

Applied Trends in Magnetic Rare Earth/Transition Metal Alloys and Multilayers

Ferrimagnetic thin films formerly played a very important role in the development of information storage technology. Now they are again at the forefront of the rising field of spintronics. From new, more efficient magnetic recording media and sensors based on spin valves to the promising technologies envisaged by all-optical switching, ferrimagnets offer singular properties that deserve to be studies both from the point of view of fundamental physics and for applications. In this review, we will focus on ferrimagnetic thin films based on the combination of rare earths (RE) and transition metals (TM).

Magnetic Anisotropy and Damping Constant of Ferrimagnetic GdCo Alloy near Compensation Point

Metallic ferrimagnets with rare earth-transition metal alloys can provide novel properties that cannot be obtained using conventional ferromagnets. Recently, the compensation point of ferrimagnets, where the net magnetization or net angular momentum vanishes, has been considered a key aspect for memory device applications. For such applications, the magnetic anisotropy energy and damping constant are crucial. In this study, we investigate the magnetic anisotropy and damping constant of a GdCo alloy, with a Gd concentration of 12–27%. By analyzing the equilibrium tilting of magnetization as a function of the applied magnetic field, we estimate the uniaxial anisotropy to be 1–3 × 104 J m−3. By analyzing the transient dynamics of magnetization as a function of time, we estimate the damping constant to be 0.08–0.22.