Ab initio investigations of a CoBiS monolayer with and without point defects

Literature Information

Publication Date 2022-12-15
DOI 10.1039/D2CP03891A
Impact Factor 3.676
Authors

H. Said, H. Garbouj, M. Debbichi, S. El Hog, S. Lebègue


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Abstract

Through density functional theory (DFT) calculations, a new triclinic monolayer, namely CoBiS, with higher stability than that of penta-CoBiS, is predicted. Our results show that this monolayer is a nonmagnetic metallic compound. To tune its magnetic properties, we systematically investigated the formation and energetics of different point defects in the CoBiS monolayer, such as VBi, VS and VCo. We find that the monolayer becomes magnetic with the different points defects. Our calculated magnetic anisotropy energy (MAE) indicated that VBi and VS exhibit out-of-plane MAE, while the MAE is in-plane for VCo. By solving the Heisenberg model using the Monte Carlo simulation method, we obtain transition temperatures for VS and VCo systems much larger than room temperature, implying potential applications in spintronic devices.

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Source Journal

Physical Chemistry Chemical Physics

Physical Chemistry Chemical Physics
CiteScore: 5.5
Self-citation Rate: 10.3%
Articles per Year: 3036

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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