Abdullah Chik
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Preferred name
Abdullah Chik
Official Name
Abdullah, Chik
Alternative Name
Chik, Abdullah
Chik, A
Chik, Abdullah bin
Main Affiliation
Scopus Author ID
15768692100
Researcher ID
EPX-6197-2022

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Recent advances in density functional theory approach for optoelectronics properties of graphene

2023-03-01 , Olatomiwa A.L. , Tijjani Adam , Edet C.O. , Adewale A.A. , Abdullah Chik , Mohammed M. , Subash Chandra Bose Gopinath , Uda Hashim

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.

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Publication

Recent advances in density functional theory approach for optoelectronics properties of graphene

2023-03-01 , Olatomiwa A.L. , Tijjani Adam , Edet C.O. , Adewale A.A. , Abdullah Chik , Mohammed M. , Subash Chandra Bose Gopinath , Uda Hashim

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.

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First principles calculations of structural, electronic, mechanical and thermoelectric properties of cubic ATiO3 (A= Be, Mg, Ca, Sr and Ba) perovskite oxide

2021-09-01 , Adewale A.A. , Abdullah Chik , Tijjani Adam , Yusuff O.K. , Ayinde S.A. , Sanusi Y.K.

First principle calculation was performed to investigate material properties such as structural, electronic, mechanical and thermoelectric of ATiO3 (Be, Mg, Ca, Sr or Ba) a perovskite based oxide within density functional theory. Calculations were performed using PBEsol exchange correlation functional within generalized gradient approximation (GGA). Structural and electronic properties were elaborated since their effect gives information about the thermoelectric performance. The underestimate of band gap from DFT calculation were corrected by using DFT with Modified Becke and Johnson (mBJ). It was observed that compound with small band gap have higher electrical conductivity and at the same time, high performance of thermoelectric power factors. BeTiO3 was found to possess very low power factor due to its low value of Seebeck coefficient and electrical conductivity. Highest thermoelectric power factor was obtained in BaTiO3 at 1200 K. Elastic constant were used to explain the mechanical properties such as anisotropic, brittle characteristics, stiffness and many others.

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A DFT study of the optoelectronic properties of B and Be-doped Graphene

2024-02-01 , Agbolade L.O. , Dafhalla A.K.Y. , Zayan D.M.I. , Tijjani Adam , Abdullah Chik , Adewale A.A. , Subash Chandra Bose Gopinath , Uda Hashim

The electronic and optical properties of Boron (B) and Beryllium (Be)-doped graphene were determined using the ab initio approach based on the generalized gradient approximations within the Full potential linearized Augmented Plane wave formalism (FP-LAPW). Our findings demonstrated that doping at the edges of graphene is notably stable. In both systems, Be- doped graphene proves more efficient in manipulating the band gap of graphene. Both B and Be, induce P-type doping in graphene. B-doped graphene exhibits a negligible magnetic moment of 0.000742, suggesting its suitability for catalytic semiconductor devices. Conversely, Be-doped graphene displays a large magnetic moment of 1.045 μB, indicating its potential in spintronics. Additionally, this study elucidates the influence of the dopant atoms on the optical properties of graphene. These findings underscore a stable and controllable method for modelling graphene at its edges with B and Be atoms, opening new avenues in the design of these devices.

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