Janus group V1B-based pnictogen-halide monolayers: a new class of multifunctional quantum materials from first-principles predictions

This study employed density functional theory to discover a new family of 48 two-dimensional Janus monolayers with the formula MXY, where M stands for transition metals (Cr, Mo, or W), X represents a group V element (P, As, Sb, or Bi), and Y denotes a halide (F, Cl, Br, or I). The cohesive energy and phonon dispersion calculations show that most of these materials are energetically and dynamically stable. Subsequently, the thorough investigation into the electrical structure allows the classification of these monolayers as metals (CrPI and WPI) or semiconductors with narrow band gaps ranging from 0.69 to 2.15 eV. Meanwhile, the MoSbBr, MoSbI, and WBiCl monolayers are defined to be able to function as photocatalysts in the water splitting process, and the CrAsCl monolayer exhibits significant potential for valleytronic applications due to its intrinsic valence band splitting of about 90 meV. Finally, significant Rashba splitting was observed near the Γ point in the valence band of Janus MXY monolayers, where the growth in atomic weight (W > Mo > Cr and Bi > Sb > As > P) corresponds to a greater spin-orbit coupling effect on the Rashba parameter. Their Rashba values are comparable to those ofother well-known 2D materials, indicating great potential for spintronic applications. Our findings not only present a broad range of 2D materials, but also highlight their potential for next-generation electrical, photonic, and catalytic technologies.

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Publication Details

Journal
Physical Chemistry Chemical Physics
Published
2025-01-01
DOI
https://doi.org/10.1039/d4cp04036h
Citations
5
Primary Topic
Machine Learning in Materials Science
Type
article
Field-Weighted Citation Impact
2.59

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article

Janus group V1B-based pnictogen-halide monolayers: a new class of multifunctional quantum materials from first-principles predictions

Sergey Gusarov, Chinedu E. Ekuma, Mosayeb Naseri, Gap Soo Chang et al.
5 citations
Physical Chemistry Chemical Physics
Machine Learning in Materials Science
2.59
article

Janus group V1B-based pnictogen-halide monolayers: a new class of multifunctional quantum materials from first-principles predictions

Sergey Gusarov, Chinedu E. Ekuma, Mosayeb Naseri, Gap Soo Chang, Mina Alizade
article en
5 citations

Abstract

This study employed density functional theory to discover a new family of 48 two-dimensional Janus monolayers with the formula MXY, where M stands for transition metals (Cr, Mo, or W), X represents a group V element (P, As, Sb, or Bi), and Y denotes a halide (F, Cl, Br, or I). The cohesive energy and phonon dispersion calculations show that most of these materials are energetically and dynamically stable. Subsequently, the thorough investigation into the electrical structure allows the classification of these monolayers as metals (CrPI and WPI) or semiconductors with narrow band gaps ranging from 0.69 to 2.15 eV. Meanwhile, the MoSbBr, MoSbI, and WBiCl monolayers are defined to be able to function as photocatalysts in the water splitting process, and the CrAsCl monolayer exhibits significant potential for valleytronic applications due to its intrinsic valence band splitting of about 90 meV. Finally, significant Rashba splitting was observed near the Γ point in the valence band of Janus MXY monolayers, where the growth in atomic weight (W > Mo > Cr and Bi > Sb > As > P) corresponds to a greater spin-orbit coupling effect on the Rashba parameter. Their Rashba values are comparable to those ofother well-known 2D materials, indicating great potential for spintronic applications. Our findings not only present a broad range of 2D materials, but also highlight their potential for next-generation electrical, photonic, and catalytic technologies.

Physical Chemistry Chemical PhysicsVol. 27(16)
Islamic Azad University, Science and Research Branch (IR), University of Calgary (CA), Lehigh University (US), University of Saskatchewan (CA), National Research Council Canada (CA)
National Science Foundation, Natural Sciences and Engineering Research Council of Canada, Division of Materials Research
Openalex Percentile: Top 11%
Machine Learning in Materials Science
2.59
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