Spintronics: Study of Zigzag Silicine Nanoribbons (ZSiNR)
POSTER
Abstract
The main aim of this paper would be to summarise the results of the two main journals [1,2] and distinguish between the two main cases of Silicine (2D layered sheets of Graphene) and Manganese passivated Silicine.
INTRODUCTION:
Spintronics (Spin electronics) mainly aims at exploiting spin degree of freedom instead of/or in addition to charge degree of freedom for information storage and logic devices. Ground state of ZSiNRs have the 2 edges anti-ferromagnetically (AFM) coupled which is slightly lower in energy than the ferromagnetic (FM) state as a result of edge magnetic states coupling. Due to the spin degeneracy of the AFM state, spin-polarized transport could not be realized in pristine ZSiNRs. Various approaches were utilised to break the spin degeneracy in ZSiNRs.
CALCULATIONS:
1) Half-metallicity by application of Transverse Electric Field & Asymmetric Edge Modification:
This method could be induced by an in-plane homogeneous field in the hydrogen-terminal ZSiNRs. The zero field α-spin and β-spin orbitals in the conduction and valence bands are localised at the opposite edges of the nano-ribbon and in a given edge the spin orientations in the conduction and valence bands are opposite. It is another way to transform ZSiNRs to half metals. Here we investigate the methods of edge hydrogenation (H2-ZSiNR-H). We repeat the calculations by inducing Mn as a passivating element.
2) Spin-Filter and Spin-FET:
A ZSiNR spin-filter under a transverse electric field is used for Transportation properties are stimulated by using density functional theory (DFT) coupled with the non-equilibrium Green’s function (NEGF) formalism. Besides the proposed spin-filter, ZSiNR could also serve as the channel of an effective spin FET with quadruple gate.
COMPUTATIONAL DETAILS:
We perform the first principle calculations using density functional theory (DFT) based on the functional method and ultrasoft pseudo potentials. We use Quantum Espresso (Simulation and Library packages) and MATLAB to calculate and re-calculate the data.
REFERENCES:
1) W. Yang-Yang, Q. Ru-Ge, Y. Da-Peng, and L.-u Jin, Chin. Phys. B Vol. 24, No. 8 087201 (2015).
2) C. Chen, Z. Zhu, D. Zha, M. Qi, J. Wu, Chemical Physics Letters, Volume 646 148-152 (2016).
INTRODUCTION:
Spintronics (Spin electronics) mainly aims at exploiting spin degree of freedom instead of/or in addition to charge degree of freedom for information storage and logic devices. Ground state of ZSiNRs have the 2 edges anti-ferromagnetically (AFM) coupled which is slightly lower in energy than the ferromagnetic (FM) state as a result of edge magnetic states coupling. Due to the spin degeneracy of the AFM state, spin-polarized transport could not be realized in pristine ZSiNRs. Various approaches were utilised to break the spin degeneracy in ZSiNRs.
CALCULATIONS:
1) Half-metallicity by application of Transverse Electric Field & Asymmetric Edge Modification:
This method could be induced by an in-plane homogeneous field in the hydrogen-terminal ZSiNRs. The zero field α-spin and β-spin orbitals in the conduction and valence bands are localised at the opposite edges of the nano-ribbon and in a given edge the spin orientations in the conduction and valence bands are opposite. It is another way to transform ZSiNRs to half metals. Here we investigate the methods of edge hydrogenation (H2-ZSiNR-H). We repeat the calculations by inducing Mn as a passivating element.
2) Spin-Filter and Spin-FET:
A ZSiNR spin-filter under a transverse electric field is used for Transportation properties are stimulated by using density functional theory (DFT) coupled with the non-equilibrium Green’s function (NEGF) formalism. Besides the proposed spin-filter, ZSiNR could also serve as the channel of an effective spin FET with quadruple gate.
COMPUTATIONAL DETAILS:
We perform the first principle calculations using density functional theory (DFT) based on the functional method and ultrasoft pseudo potentials. We use Quantum Espresso (Simulation and Library packages) and MATLAB to calculate and re-calculate the data.
REFERENCES:
1) W. Yang-Yang, Q. Ru-Ge, Y. Da-Peng, and L.-u Jin, Chin. Phys. B Vol. 24, No. 8 087201 (2015).
2) C. Chen, Z. Zhu, D. Zha, M. Qi, J. Wu, Chemical Physics Letters, Volume 646 148-152 (2016).
Publication: Planned Paper in IEEE (Institute of Electrical and Electronics Engineers). First preprint to be published in arxiv.org (by August 2021-September 2021)
Presenters
-
Soumita Mondal
Keio University
Authors
-
Soumita Mondal
Keio University
-
Soubhik Mondal
Indian Institute of Information Technology Senapati, Manipur