Computational Search for Novel Hard Chromium-Based Materials

Nitrides, carbides, and borides of transition metals are an attractive class of hard materials. Our recent preliminary explorations of the binary chemical compounds indicated that chromium-based materials are among the hardest transition metal compounds. Motivated by this, here we explore in detail the binary Cr–B, Cr–C, and Cr–N systems using global optimization techniques. Calculated enthalpy of formation and hardness of predicted materials were used for Pareto optimization to define the hardest materials with the lowest energy. Our calculations recover all numerous known stable compounds (except Cr₂₃C₆ with its large unit cell) and discover a novel stable phase <i>Pmn</i>2₁-Cr₂C. We resolve the structure of Cr₂N and find it to be of anti-CaCl₂ type (space group <i>Pnnm</i>). Many of these phases possess remarkable hardness, but only CrB₄ is superhard (Vickers hardness 48 GPa). Among chromium compounds, borides generally possess the highest hardnesses and greatest stability. Under pressure, we predict stabilization of a layered TMDC-like phase of Cr₂N, a WC-type phase of CrN, and a new compound CrN₄. Nitrogen-rich chromium nitride CrN₄ is a high-energy-density material featuring polymeric nitrogen chains. In the presence of metal atoms (e.g., Cr), polymerization of nitrogen takes place at much lower pressures; CrN₄ becomes stable at ∼15 GPa (cf. 110 GPa for synthesis of pure polymeric nitrogen)

Computational prediction of new magnetic materials

International audienceThe discovery of new magnetic materials is a big challenge in the field of modern materials science. We report the development of a new extension of the evolutionary algorithm USPEX, enabling the search for half-metals (materials that are metallic only in one spin channel) and hard magnetic materials. First, we enabled the simultaneous optimization of stoichiometries, crystal structures, and magnetic structures of stable phases. Second, we developed a new fitness function for half-metallic materials that can be used for predicting half-metals through an evolutionary algorithm. We used this extended technique to predict new, potentially hard magnets and rediscover known half-metals. In total, we report five promising hard magnets with high energy product (|BH|max), anisotropy field ( Ha), and magnetic hardness (κ) and a few half-metal phases in the Cr-O system. A comparison of our predictions with experimental results, including the synthesis of a newly predicted antiferromagnetic material (WMnB2), shows the robustness of our technique