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Machine learning approach to constructing tight binding models for solids with application to BiTeCl”. Nakhaee M, Ketabi SA, Peeters FM, Journal Of Applied Physics 128, 215107 (2020). http://doi.org/10.1063/5.0023980
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Tight-binding studio : a technical software package to find the parameters of tight-binding Hamiltonian”. Nakhaee M, Ketabi SA, Peeters FM, Computer Physics Communications 254, 107379 (2020). http://doi.org/10.1016/J.CPC.2020.107379
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Single-layer structures of a100- and b010-Gallenene : a tight-binding approach”. Nakhaee M, Yagmurcukardes M, Ketabi SA, Peeters FM, Physical chemistry, chemical physics 21, 15798 (2019). http://doi.org/10.1039/C9CP02515D
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Dirac nodal line in bilayer borophene : tight-binding model and low-energy effective Hamiltonian”. Nakhaee M, Ketabi SA, Peeters FM, Physical review B 98, 115413 (2018). http://doi.org/10.1103/PHYSREVB.98.115413
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Tight-binding model for borophene and borophane”. Nakhaee M, Ketabi SA, Peeters FM, Physical review B 97, 125424 (2018). http://doi.org/10.1103/PHYSREVB.97.125424
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Landau levels in biased graphene structures with monolayer-bilayer interfaces”. Mirzakhani M, Zarenia M, Vasilopoulos P, Ketabi SA, Peeters FM, Physical review B 96, 125430 (2017). http://doi.org/10.1103/PHYSREVB.96.125430
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Energy levels of ABC-stacked trilayer graphene quantum dots with infinite-mass boundary conditions”. Mirzakhani M, Zarenia M, da Costa DR, Ketabi SA, Peeters FM, Physical review B 94, 165423 (2016). http://doi.org/10.1103/PHYSREVB.94.165423
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Energy levels of hybrid monolayer-bilayer graphene quantum dots”. Mirzakhani M, Zarenia M, Ketabi SA, da Costa DR, Peeters FM, Physical review B 93, 165410 (2016). http://doi.org/10.1103/PhysRevB.93.165410
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