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arXiv · 2606.30540

Synthesizability and Mechanical Properties of High-Entropy Borides: First-Principles and Machine Learning Studies

Luke Moore·Ethan Fox·Bria Storr·Jayden R. Palomino·Shane A. Catledge·Yogesh K. Vohra·Cheng-Chien Chen
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Abstract

We perform density functional theory (DFT) calculations to investigate five-metal high-entropy borides (HEBs) in the hexagonal AlB$_2$ structure, considering all 126 possible elemental combinations among the nine group 4-6 transition metals (Ti, V, Cr, Zr, Nb, Mo, Hf, Ta, and W). The entropy forming ability (EFA) descriptor is employed to evaluate their single-phase synthesizability, and the resulting EFA predictions show good agreement with the experimental data for selected HEBs. Mechanical properties are computed using special quasi-random structures. Several mechanically unstable compounds -- primarily those containing Cr -- are also predicted to be less synthesizable. Machine learning (ML) models are developed to analyze the results. This combined ab initio and ML study provides a systematic roadmap for identifying mechanically superior single-phase HEBs.

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Luke Moore, Ethan Fox, Bria Storr, Jayden R. Palomino, Shane A. Catledge, Yogesh K. Vohra, Cheng-Chien Chen. 2026-06-29. Synthesizability and Mechanical Properties of High-Entropy Borides: First-Principles and Machine Learning Studies. https://arxiv.org/abs/2606.30540

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