An efficient tunable thermoelectric device based on n and p doped graphene superlattice heterostructures. (June 2020)

• Record Type: Journal Article
• Authors: Mishra, Shakti Kumar; Kumar, Amar; Kaushik, Chetan Prakash; Dikshit, Biswaranjan
• Is Part Of: Superlattices and microstructures. Volume 142(2020)
• Publication Date: 2020-06
• Subjects: Superlattices as materials -- Periodicals; Microstructure -- Periodicals; Semiconductors -- Periodicals; Superréseaux -- Périodiques; Microstructure (Physique) -- Périodiques; Semiconducteurs -- Périodiques; 621.38152
• DOI: 10.1016/j.spmi.2020.106520
• Languages: English
• ISSNs: 0749-6036

Abstract

Abstract: This paper theoretically predicts a large Seebeck coefficient in p and n doped graphene superlattice heterostructures based thermoelectric device, by tuning the electrical and structural parameters. By introducing a single graphene layer doped to a different extent compared to other layers in between the symmetric p & n structure, a resonant tunneling state occurs inside the forbidden gap of the electron transmittance in respect of electron energy and this creates a giant thermoelectric effect. The tunneling state and the corresponding maximum value of the Seebeck coefficient can be modulated by changing the doping concentration and width of the graphene layers. The doping concentration and the type of graphene layer p or n are controlled by the magnitude and polarity of the electric potential applied to the electrodes placed over the graphene. The modulation of the Seebeck coefficient by doping concentration, period number, electron incidence angle and width of the graphene layers can lead to an electron wave filter and efficient tunable thermoelectric device for application in the field of non-conventional energy sources. This paper describes the effect of electrical and structural parameters on the Seebeck coefficient and assortment of these parameters for design an efficient graphene-based thermoelectric device. Highlights: Tunable Thermoelectric Device. Graphene Superlattice Heterostructures. Seebeck coefficient. p doped Graphene Layer. n doped Graphene Layer.