Theoretical predictions of phase stability for orthorhombic and hexagonal ternary MAB phases
文献信息
Adam Carlsson, Johanna Rosen, Martin Dahlqvist
In the quest for finding novel thermodynamically stable, layered, MAB phases promising for synthesis, we herein explore the phase stability of ternary MAB phases by considering both orthorhombic and hexagonal crystal symmetries for various compositions (MAB, M2AB2, M3AB4, M4AB4, and M4AB6 where M = Sc, Y, Ti, Zr, Hf, V, Nb, Ta, Cr, Mo, W, Mn, Fe, and Co, A = Al, Ga, and In, and B is boron). The thermodynamic stability of seven previously synthesized MAB phases is confirmed, three additional phases are predicted to be stable, and 23 phases are found to be close to stable. Furthermore, the crystal symmetry preference for forming orthorhombic or hexagonal crystal structures is investigated where the considered Al-based MAB phases tend to favour orthorhombic structures whereas Ga- and In-based phases in general prefer hexagonal structures. The theoretically predicted stable MAB phases along with the structural preference is intended to both guide experimental efforts and to give an insight into the stability for different crystal symmetries of MAB phases.
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Physical Chemistry Chemical Physics

Physical Chemistry Chemical Physics (PCCP) is an international journal co-owned by 19 physical chemistry and physics societies from around the world. This journal publishes original, cutting-edge research in physical chemistry, chemical physics and biophysical chemistry. To be suitable for publication in PCCP, articles must include significant innovation and/or insight into physical chemistry; this is the most important criterion that reviewers and Editors will judge against when evaluating submissions. The journal has a broad scope and welcomes contributions spanning experiment, theory, computation and data science. Topical coverage includes spectroscopy, dynamics, kinetics, statistical mechanics, thermodynamics, electrochemistry, catalysis, surface science, quantum mechanics, quantum computing and machine learning. Interdisciplinary research areas such as polymers and soft matter, materials, nanoscience, energy, surfaces/interfaces, and biophysical chemistry are welcomed if they demonstrate significant innovation and/or insight into physical chemistry. Joined experimental/theoretical studies are particularly appreciated when complementary and based on up-to-date approaches.












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