Anisotropic and outstanding mechanical, thermal conduction, optical, and piezoelectric responses in a novel semiconducting BCN monolayer confirmed by first-principles and machine learning

Research output: Contribution to journalArticleResearchpeer review

Authors

  • Bohayra Mortazavi
  • Fazel Shojaei
  • Mehmet Yagmurcukardes
  • Alexander V. Shapeev
  • Xiaoying Zhuang

External Research Organisations

  • Persian Gulf University
  • İzmir Institute of Technology
  • Skolkovo Institute of Science and Technology
  • Tongji University
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Details

Original languageEnglish
Pages (from-to)500-509
Number of pages10
JournalCARBON
Volume200
Early online date2 Sept 2022
Publication statusPublished - Nov 2022

Abstract

Graphene-like nanomembranes made of the neighboring elements of boron, carbon and nitrogen elements, are well-known of showing outstanding physical properties. Herein, with the aid of density functional theory (DFT) calculations, various atomic configurations of the graphene-like BCN nanosheets are investigated. DFT results reveal that depending on the atomic arrangement, the BCN monolayers may display semimetallic Dirac cone or semiconducting electronic nature. BCN nanosheets are also found to exhibit high piezoelectricity and carrier mobilities with considerable in-plane anisotropy, depending on the atomic arrangement. For the predicted most stable BCN monolayer, thermal and mechanical properties are explored using machine learning interatomic potentials. The room temperature tensile strength and lattice thermal conductivity of the most stable BCN monolayer are estimated to be orientation-dependent and remarkably high, over 78 GPa and 290 W/m.K, respectively. In addition, the thermal expansion coefficient of the monolayer BCN at room temperature is estimated to be −3.2 × 10−6 K−1, which is close to that of the graphene. The piezoelectric response of the herein proposed BCN lattice is also predicted to be close to that of the h-BN monolayer. Presented results highlight outstanding physics of the BCN nanosheets.

Keywords

    h-BCN, Machine-learning, Piezoelectric, Semiconductor, Thermal conductivity

ASJC Scopus subject areas

Cite this

Anisotropic and outstanding mechanical, thermal conduction, optical, and piezoelectric responses in a novel semiconducting BCN monolayer confirmed by first-principles and machine learning. / Mortazavi, Bohayra; Shojaei, Fazel; Yagmurcukardes, Mehmet et al.
In: CARBON, Vol. 200, 11.2022, p. 500-509.

Research output: Contribution to journalArticleResearchpeer review

Mortazavi B, Shojaei F, Yagmurcukardes M, Shapeev AV, Zhuang X. Anisotropic and outstanding mechanical, thermal conduction, optical, and piezoelectric responses in a novel semiconducting BCN monolayer confirmed by first-principles and machine learning. CARBON. 2022 Nov;200:500-509. Epub 2022 Sept 2. doi: 10.1016/j.carbon.2022.08.077
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title = "Anisotropic and outstanding mechanical, thermal conduction, optical, and piezoelectric responses in a novel semiconducting BCN monolayer confirmed by first-principles and machine learning",
abstract = "Graphene-like nanomembranes made of the neighboring elements of boron, carbon and nitrogen elements, are well-known of showing outstanding physical properties. Herein, with the aid of density functional theory (DFT) calculations, various atomic configurations of the graphene-like BCN nanosheets are investigated. DFT results reveal that depending on the atomic arrangement, the BCN monolayers may display semimetallic Dirac cone or semiconducting electronic nature. BCN nanosheets are also found to exhibit high piezoelectricity and carrier mobilities with considerable in-plane anisotropy, depending on the atomic arrangement. For the predicted most stable BCN monolayer, thermal and mechanical properties are explored using machine learning interatomic potentials. The room temperature tensile strength and lattice thermal conductivity of the most stable BCN monolayer are estimated to be orientation-dependent and remarkably high, over 78 GPa and 290 W/m.K, respectively. In addition, the thermal expansion coefficient of the monolayer BCN at room temperature is estimated to be −3.2 × 10−6 K−1, which is close to that of the graphene. The piezoelectric response of the herein proposed BCN lattice is also predicted to be close to that of the h-BN monolayer. Presented results highlight outstanding physics of the BCN nanosheets.",
keywords = "h-BCN, Machine-learning, Piezoelectric, Semiconductor, Thermal conductivity",
author = "Bohayra Mortazavi and Fazel Shojaei and Mehmet Yagmurcukardes and Shapeev, {Alexander V.} and Xiaoying Zhuang",
note = "Funding Information: B. M. appreciates the funding by the Deutsche Forschungsgemeinschaft (DFG, German Reuter Foundation) under Germany's Excellence Strategy within the Cluster of Excellence PhoenixD (EXC 2122 , Project ID 390833453 ). F.S. thanks the Persian Gulf University Research Council, Iran, for the support of this study. B. M is greatly thankful to the VEGAS cluster at Bauhaus University of Weimar for providing the computational resources. A.V.S. is supported by the Russian Science Foundation (Grant No 18-13-00479 , https://rscf.ru/project/18-13-00479/ ). Computational resources were partially provided by TUBITAKULAKBIM, High Performance and Grid Computing Center (TR-Grid e-Infrastructure). This work was partially supported by the BAGEP Award of the Science Academy with funding supplied by Sevinc-Erdal Inonu Foundation. Next, the synthesis feasibility of various BCNs are investigated by calculating their formation energies (Eform) in comparison with graphene and h-BN (as summarized in Table 1). The formation energy for the considered BCN monolayers varies between +0.167 and + 0.868 eV/atom, indicating that they are metastable with respect to the native graphene and h-BN crystals. This finding highlights that from the theoretical point of view, the most energetically stable form of the large-area BCN nanomembranes should in fact comprise covalently bonded graphene and h-BN coplanar heterostructures, which is also consistent with a latest experimental observation [36]. The positive formation energy nonetheless does not question the synthesizability of a material, otherwise bulk diamond and graphdiyne layered materials both show positive formation energies with respect to the graphite. For instance, in a combined experimental and computational study [37], the most matched graphene-like BCN monolayer, synthesized through dehydrogenation polymerization of BN cyclohexane, is found to show a formation energy of +0.440 eV/atom with respect to the graphene and h-BN. Taking this value as a criterion for the synthesizability of the BCNs, the BCN-1 and BCN-2 lattices with smaller formation energies as that of the synthesized BCN [37], are also probable candidates for the experimental realization. On the other hand, being the most stable configuration of a chemical composition also does not always guarantee an easier chemical synthesis. For instance, in the above mentioned experimental-computational work [37], herein so called BCN-3 has been computationally predicted to be the global minimum structure of the polymerization process, however, a different configuration was consistent to their crystallographic data. In our previous study [6], it was also found that the recently fabricated BC2N lattice via a rapid quenching strategy [5], is not also the global minimum structure. In Fig. 1 the ELF results are also included, which is a topological function defined between 0 and 1 [34]. Large ELF values over 0.8 appearing around the center of bonds, indicate the formation of strong covalent interactions throughout these graphene-like networks. Because of larger electronegativity of N atoms than the C and B counterparts, they tend to attract electrons from them, resulting in the formation of polar covalent bonding along the hetero bonds. In the supporting information document, the energy minimized BCN monolayers are included.B. M. appreciates the funding by the Deutsche Forschungsgemeinschaft (DFG, German Reuter Foundation) under Germany's Excellence Strategy within the Cluster of Excellence PhoenixD (EXC 2122, Project ID 390833453). F.S. thanks the Persian Gulf University Research Council, Iran, for the support of this study. B. M is greatly thankful to the VEGAS cluster at Bauhaus University of Weimar for providing the computational resources. A.V.S. is supported by the Russian Science Foundation (Grant No 18-13-00479, https://rscf.ru/project/18-13-00479/). Computational resources were partially provided by TUBITAKULAKBIM, High Performance and Grid Computing Center (TR-Grid e-Infrastructure). This work was partially supported by the BAGEP Award of the Science Academy with funding supplied by Sevinc-Erdal Inonu Foundation.",
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language = "English",
volume = "200",
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Download

TY - JOUR

T1 - Anisotropic and outstanding mechanical, thermal conduction, optical, and piezoelectric responses in a novel semiconducting BCN monolayer confirmed by first-principles and machine learning

AU - Mortazavi, Bohayra

AU - Shojaei, Fazel

AU - Yagmurcukardes, Mehmet

AU - Shapeev, Alexander V.

AU - Zhuang, Xiaoying

N1 - Funding Information: B. M. appreciates the funding by the Deutsche Forschungsgemeinschaft (DFG, German Reuter Foundation) under Germany's Excellence Strategy within the Cluster of Excellence PhoenixD (EXC 2122 , Project ID 390833453 ). F.S. thanks the Persian Gulf University Research Council, Iran, for the support of this study. B. M is greatly thankful to the VEGAS cluster at Bauhaus University of Weimar for providing the computational resources. A.V.S. is supported by the Russian Science Foundation (Grant No 18-13-00479 , https://rscf.ru/project/18-13-00479/ ). Computational resources were partially provided by TUBITAKULAKBIM, High Performance and Grid Computing Center (TR-Grid e-Infrastructure). This work was partially supported by the BAGEP Award of the Science Academy with funding supplied by Sevinc-Erdal Inonu Foundation. Next, the synthesis feasibility of various BCNs are investigated by calculating their formation energies (Eform) in comparison with graphene and h-BN (as summarized in Table 1). The formation energy for the considered BCN monolayers varies between +0.167 and + 0.868 eV/atom, indicating that they are metastable with respect to the native graphene and h-BN crystals. This finding highlights that from the theoretical point of view, the most energetically stable form of the large-area BCN nanomembranes should in fact comprise covalently bonded graphene and h-BN coplanar heterostructures, which is also consistent with a latest experimental observation [36]. The positive formation energy nonetheless does not question the synthesizability of a material, otherwise bulk diamond and graphdiyne layered materials both show positive formation energies with respect to the graphite. For instance, in a combined experimental and computational study [37], the most matched graphene-like BCN monolayer, synthesized through dehydrogenation polymerization of BN cyclohexane, is found to show a formation energy of +0.440 eV/atom with respect to the graphene and h-BN. Taking this value as a criterion for the synthesizability of the BCNs, the BCN-1 and BCN-2 lattices with smaller formation energies as that of the synthesized BCN [37], are also probable candidates for the experimental realization. On the other hand, being the most stable configuration of a chemical composition also does not always guarantee an easier chemical synthesis. For instance, in the above mentioned experimental-computational work [37], herein so called BCN-3 has been computationally predicted to be the global minimum structure of the polymerization process, however, a different configuration was consistent to their crystallographic data. In our previous study [6], it was also found that the recently fabricated BC2N lattice via a rapid quenching strategy [5], is not also the global minimum structure. In Fig. 1 the ELF results are also included, which is a topological function defined between 0 and 1 [34]. Large ELF values over 0.8 appearing around the center of bonds, indicate the formation of strong covalent interactions throughout these graphene-like networks. Because of larger electronegativity of N atoms than the C and B counterparts, they tend to attract electrons from them, resulting in the formation of polar covalent bonding along the hetero bonds. In the supporting information document, the energy minimized BCN monolayers are included.B. M. appreciates the funding by the Deutsche Forschungsgemeinschaft (DFG, German Reuter Foundation) under Germany's Excellence Strategy within the Cluster of Excellence PhoenixD (EXC 2122, Project ID 390833453). F.S. thanks the Persian Gulf University Research Council, Iran, for the support of this study. B. M is greatly thankful to the VEGAS cluster at Bauhaus University of Weimar for providing the computational resources. A.V.S. is supported by the Russian Science Foundation (Grant No 18-13-00479, https://rscf.ru/project/18-13-00479/). Computational resources were partially provided by TUBITAKULAKBIM, High Performance and Grid Computing Center (TR-Grid e-Infrastructure). This work was partially supported by the BAGEP Award of the Science Academy with funding supplied by Sevinc-Erdal Inonu Foundation.

PY - 2022/11

Y1 - 2022/11

N2 - Graphene-like nanomembranes made of the neighboring elements of boron, carbon and nitrogen elements, are well-known of showing outstanding physical properties. Herein, with the aid of density functional theory (DFT) calculations, various atomic configurations of the graphene-like BCN nanosheets are investigated. DFT results reveal that depending on the atomic arrangement, the BCN monolayers may display semimetallic Dirac cone or semiconducting electronic nature. BCN nanosheets are also found to exhibit high piezoelectricity and carrier mobilities with considerable in-plane anisotropy, depending on the atomic arrangement. For the predicted most stable BCN monolayer, thermal and mechanical properties are explored using machine learning interatomic potentials. The room temperature tensile strength and lattice thermal conductivity of the most stable BCN monolayer are estimated to be orientation-dependent and remarkably high, over 78 GPa and 290 W/m.K, respectively. In addition, the thermal expansion coefficient of the monolayer BCN at room temperature is estimated to be −3.2 × 10−6 K−1, which is close to that of the graphene. The piezoelectric response of the herein proposed BCN lattice is also predicted to be close to that of the h-BN monolayer. Presented results highlight outstanding physics of the BCN nanosheets.

AB - Graphene-like nanomembranes made of the neighboring elements of boron, carbon and nitrogen elements, are well-known of showing outstanding physical properties. Herein, with the aid of density functional theory (DFT) calculations, various atomic configurations of the graphene-like BCN nanosheets are investigated. DFT results reveal that depending on the atomic arrangement, the BCN monolayers may display semimetallic Dirac cone or semiconducting electronic nature. BCN nanosheets are also found to exhibit high piezoelectricity and carrier mobilities with considerable in-plane anisotropy, depending on the atomic arrangement. For the predicted most stable BCN monolayer, thermal and mechanical properties are explored using machine learning interatomic potentials. The room temperature tensile strength and lattice thermal conductivity of the most stable BCN monolayer are estimated to be orientation-dependent and remarkably high, over 78 GPa and 290 W/m.K, respectively. In addition, the thermal expansion coefficient of the monolayer BCN at room temperature is estimated to be −3.2 × 10−6 K−1, which is close to that of the graphene. The piezoelectric response of the herein proposed BCN lattice is also predicted to be close to that of the h-BN monolayer. Presented results highlight outstanding physics of the BCN nanosheets.

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KW - Machine-learning

KW - Piezoelectric

KW - Semiconductor

KW - Thermal conductivity

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U2 - 10.1016/j.carbon.2022.08.077

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