Tight Binding Hamiltonian Parameter Extraction and I-V Characteristics of 13 AGNR using Machine Learning Method

The Hamiltonian of a unit cell, coupling matrices and the device can be used to find electronic properties like the band structure of a material and the I-V characteristics of the device. As new materials are emerging all the time, it is essential to know the electronic properties of these materials with the help of a unit cell or device Hamiltonian. In this paper we have used a machine learning method to generate the Hamiltonian matrix and the coupling matrices of the unit cell of 13 Armchair Graphene Nanoribbon (AGNR) from the energy band data found from Density Functional Theory. This machine learning generated Hamiltonian of 13-AGNR has been used to find the I-V characteristics of a Nano-FET device and this I-V characteristics has been compared with the already existing results.