Significant improvement of infrared graphene nanoribbon phototransistor performance: A quantum simulation study

Graphical illustration of GNR Phototransistor [Display omitted] •A new class of very sensitive graphene phototransistor GNR-PT is presented and numerically demonstrated via a mode-space NEGF approach.•The investigated phototransistor uses Graphene not only as channel for photogenerated carriers but also as active area.•A simplified model that considers the textured graphene morphology is built and is implemented into the simulation.•The developed model constitutes the fitness function for a genetic algorithm approach to improve the phototransistor’s sensing capability.•The optimized design outperforms considerably the conventional designs. In this paper, we investigate an optimized design of textured graphene nanoribbon phototransistor via quantum simulations. The graphene layer with textured morphology performs dual role, notably as the carrier conduction channel and also as an absorber of light. The proposed design characteristics are numerically investigated via a non-equilibrium Green’s function (NEGF) mode-space formulism in the ballistic edge. The method suggested was tailored to the modern carrier transport model, Electron-photon and Electron-phonon interactions. Besides, a simple analytical model that considers graphene light trapping morphology is developed and introduced into the simulation. This model is regarded as a fitness function for Multi-Objective Genetic Algorithm (MOGA) optimization technique to improve the GNR phototransistor sensing capability. Simulations results show that, compared to a conventional phototransistor, the proposed design has higher responsivity (47.55 mA/W), good sensitivity (2.41 × 103), higher detectivity (6.09 × 1010 Jones), better Photocurrent to Dark Current Ratio (PDCR) (24.15) and keeping better scaling capability.