In this paper, new sensors based on a double-gate (DG) graphene nanoribbon field-effect transistor (GNRFET), for high-performance DNA and gas detection, are proposed through a simulation-based study. The proposed sensors are simulated by solving the Schrödinger equation using the mode space non-equilibrium Green’s function formalism coupled self-consistently with a 2D Poisson equation under the ballistic limits. The dielectric and work function modulation techniques are used for the electrical detection of DNA and gas molecules, respectively. The behaviors of both the sensors have been investigated, and the impacts of variation in geometrical and electrical parameters on the sensitivity of sensors have also been studied. In comparison to other FET-based sensors, the proposed sensors provide not only higher sensitivity but also better electrical and scaling performances. The obtained results make the proposed DG-GNRFET-based sensors as promising candidates for ultra-sensitive, small-size, low-power and reliable CMOS-based DNA, and gas sensors.

In this paper, new sensors based on a double-gate (DG) graphene nanoribbon field-effect transistor (GNRFET), for high-performance DNA and gas detection, are proposed through a simulation-based study. The proposed sensors are simulated by solving the Schrödinger equation using the mode space non-equilibrium Green’s function formalism coupled self-consistently with a 2D Poisson equation under the ballistic limits. The dielectric and work function modulation techniques are used for the electrical detection of DNA and gas molecules, respectively. The behaviors of both the sensors have been investigated, and the impacts of variation in geometrical and electrical parameters on the sensitivity of sensors have also been studied. In comparison to other FET-based sensors, the proposed sensors provide not only higher sensitivity but also better electrical and scaling performances. The obtained results make the proposed DG-GNRFET-based sensors as promising candidates for ultra-sensitive, small-size, low-power and reliable CMOS-based DNA, and gas sensors.

An improved dynamic hysteresis model is proposed for the prediction of hysteresis loop of electrical steel up to mean frequencies, taking into account the skin effect. In previous works, the analytical solution of the diffusion equation for low frequency (DELF) was coupled with the inverse static Jiles-Atherton (JA) model in order to represent the hysteresis behavior for a lamination. In the present paper, this approach is improved to ensure the reproducibility of measured hysteresis loops at mean frequency. The results of simulation are compared with the experimental ones. The selected results for frequencies 50 Hz, 100 Hz, 200 Hz and 400 Hz are presented and discussed.

An improved dynamic hysteresis model is proposed for the prediction of hysteresis loop of electrical steel up to mean frequencies, taking into account the skin effect. In previous works, the analytical solution of the diffusion equation for low frequency (DELF) was coupled with the inverse static Jiles-Atherton (JA) model in order to represent the hysteresis behavior for a lamination. In the present paper, this approach is improved to ensure the reproducibility of measured hysteresis loops at mean frequency. The results of simulation are compared with the experimental ones. The selected results for frequencies 50 Hz, 100 Hz, 200 Hz and 400 Hz are presented and discussed.