Now showing 1 - 3 of 3
  • Publication
    Optoelectronic behavior of ZnS compound and its alloy: A first principle approach
    ( 2021-06-01)
    Akeem Adekunle Adewale
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    ; ;
    Joshua Tolulope Majekodunmi
    ;
    Durowoju M.O.
    First principles calculations were employed to study the structural, electronic and optical properties of pristine ZnS and its alloy compounds; Zn0.75Cr0.25S, Zn0.75Ti0.25S & Zn0.50Cr0.25Ti0.25S. To investigate these, full potential linear augmented plane wave (FPLAPW) based on density functional theory (DFT) was adopted as implement in WIEN2K code by employing generalized gradient approximation (GGA) of the revised Perdew-Burke Erzenhoff (PBE) as exchange correlation function. Lattice constant, volume, bulk modulus and other physical parameters were calculated for structural properties. Variation in these parameters in crystal structure is related to difference in ionic radius of host and replaced atom. The results of band structure and density of states were determined for electronic properties. The pristine ZnS and Zn0.75Ti0.25S compounds are semiconductor in nature while Zn0.75Cr0.25S and Zn0.50Cr0.25Ti0.25S displayed metallic character. Optical parameters including absorption coefficient, energy loss function, complex refractive index; refractive index and extinction coefficient, and optical conductivity have been computed from the dielectric function at energy range of 0–25 eV. Static dielectric constant for ε1(ω) are found to be 6.61, 1811.89, 155.46 and 1446.14 in ZnS, Zn0.75Cr0.25S, Zn0.75Ti0.25S and Zn0.50Cr0.25Ti0.25S respectively. The mean peaks of absorption are found at energy range of ∼5–10.5 eV for all studied compounds. We obtained noble performance of optical conductivity of doped at 0–7 eV which is due to presence of 3d – orbitals in the doped compounds. Our results are compared with available theoretical calculations and the experimental data.
      4  1
  • Publication
    Recent advances in density functional theory approach for optoelectronics properties of graphene
    ( 2023-03-01)
    Olatomiwa A.L.
    ;
    ;
    Edet C.O.
    ;
    Adewale A.A.
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    ;
    Mohammed M.
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    ;
    Graphene has received tremendous attention among diverse 2D materials because of its remarkable properties. Its emergence over the last two decades gave a new and distinct dynamic to the study of materials, with several research projects focusing on exploiting its intrinsic properties for optoelectronic devices. This review provides a comprehensive overview of several published articles based on density functional theory and recently introduced machine learning approaches applied to study the electronic and optical properties of graphene. A comprehensive catalogue of the bond lengths, band gaps, and formation energies of various doped graphene systems that determine thermodynamic stability was reported in the literature. In these studies, the peculiarity of the obtained results reported is consequent on the nature and type of the dopants, the choice of the XC functionals, the basis set, and the wrong input parameters. The different density functional theory models, as well as the strengths and uncertainties of the ML potentials employed in the machine learning approach to enhance the prediction models for graphene, were elucidated. Lastly, the thermal properties, modelling of graphene heterostructures, the superconducting behaviour of graphene, and optimization of the DFT models are grey areas that future studies should explore in enhancing its unique potential. Therefore, the identified future trends and knowledge gaps have a prospect in both academia and industry to design future and reliable optoelectronic devices.
      2
  • Publication
    Recent advances in density functional theory approach for optoelectronics properties of graphene
    ( 2023-03-01)
    Olatomiwa A.L.
    ;
    ;
    Edet C.O.
    ;
    Adewale A.A.
    ;
    ;
    Mohammed M.
    ;
    ;
    Graphene has received tremendous attention among diverse 2D materials because of its remarkable properties. Its emergence over the last two decades gave a new and distinct dynamic to the study of materials, with several research projects focusing on exploiting its intrinsic properties for optoelectronic devices. This review provides a comprehensive overview of several published articles based on density functional theory and recently introduced machine learning approaches applied to study the electronic and optical properties of graphene. A comprehensive catalogue of the bond lengths, band gaps, and formation energies of various doped graphene systems that determine thermodynamic stability was reported in the literature. In these studies, the peculiarity of the obtained results reported is consequent on the nature and type of the dopants, the choice of the XC functionals, the basis set, and the wrong input parameters. The different density functional theory models, as well as the strengths and uncertainties of the ML potentials employed in the machine learning approach to enhance the prediction models for graphene, were elucidated. Lastly, the thermal properties, modelling of graphene heterostructures, the superconducting behaviour of graphene, and optimization of the DFT models are grey areas that future studies should explore in enhancing its unique potential. Therefore, the identified future trends and knowledge gaps have a prospect in both academia and industry to design future and reliable optoelectronic devices.
      2  5