An accurate analytical model for tunnel FET output characteristics

The analytical models for the output characteristics of tunnel FETs (TFETs) based on Maxwell–Boltzmann (MB) statistics have some accuracy issues, especially in linear region of operation, when compared with more sophisticated numerical approaches. In this letter, by exploiting the thermal injection method (TIM), an accurate analytical model for the TFET potential profile is proposed. Although the approach is initially envisaged for heterojunction TFETs (H-TFETs), it could be straightforwardly adopted for homojunction TFETs. After an accurate description of the potential profile is obtained, then, the current is computed by means of a Landauer-like expression. Comparison with the numerical simulations at different bias conditions show that the predicted output characteristics qualitatively improve, leading to a significant enhancement in accuracy at a much less-computational cost

Impact of the Figures of Merit (FoMs) definitions on the variability in nanowire TFET: NEGF simulation study

In this article, we investigate the effect of variability in p-type nanowire tunnel FET (TFET) using quantum mechanical transport simulations. The simulations have been carried out using the Nano Electronics Simulation Software (NESS) from the University of Glasgow. Random discrete dopants (RDDs) and work-function variations (WFV) have been investigated in the simulations. Our statistical simulations reveal that key figures of merit (FoMs) such as the current variability generally decrease as the gate voltage decreases, the threshold voltage variability increases as the threshold current increases, and the dependences of these FoM variabilities on criteria become stronger with the switch characteristic ameliorated. Furthermore, it is interesting to find that the band offset in heterostructure can more or less alleviate the current variability, especially around the OFF-state

Finite-Time Adaptive Neural Control Scheme for Uncertain High-Order Systems with Input Nonlinearities and Unmodeled Dynamics

This paper proposes a novel finite-time adaptive neural control method for a class of high-order nonlinear systems with high powers in the presence of dead zone input nonlinearities and unmodeled dynamics. By utilizing prescribed performance functions and radial basis function neural networks, the tracking error and state errors are limited within the preassigned range in a finite time, which can be specified by the designer in advance according to the chosen the parameters of the novel prescribed performance functions. Nonlinear transformed error surfaces are designed to counteract the effects of dead zone input nonlinearities in nonlinear high-order systems with unknown system nonlinearities and unmodeled dynamics. Based on the Lyapunov theorem, the tracking errors are proven to converge into a preassigned set in a finite time previously specified by the novel prescribed performance function. Finally, simulation results demonstrate the effectiveness of the proposed method

Decentralized Learning and Model Averaging Based Automatic Modulation Classification in Drone Communication Systems

Automatic modulation classification (AMC) is a promising technology to identify the modulation mode of the received signal in drone communication systems. Recently, benefiting from the outstanding classification performance of deep learning (DL), various deep neural networks (DNNs) have been introduced into AMC methods. Most current AMC methods are based on a local framework (LocalAMC) where there is only one device, or a centralized framework (CentAMC) where multiple local devices (LDs) upload their data to only one central server (CS). LocalAMC may not achieve ideal results due to insufficient data and finite computational power. CentAMC carries a significant risk of privacy leakage and the final data for training model in CS are quite massive. In this paper, we propose a practical and light AMC method based on decentralized learning with residual network (ResNet) in drone communication systems. Simulation results show that the ResNet-based decentralized AMC (DecentAMC) method achieves similar classification performance to CentAMC while improving training efficiency and protecting data privacy

Preparation and dielectric properties of sulfonated poly(aryl ether ketone)/acidified graphite nanosheet composites

Percolative dielectric composites of sulfonated poly(aryl ether ketone) (SPAEK) and acidified graphite nanosheets (AGSs) were fabricated by a solution method. The dielectric constant of the as-prepared composite with 4.01 vol % AGSs was found to be 330 at 1000 Hz; this was a significant increase compared to that of pure SPAEK. Through the calculation, a low percolation threshold of the AGS/SPAEK composite was confirmed at 3.18 vol % (0.0318 volume fraction) AGSs; this was attributed to the large surface area and high conductivity of the AGSs. Additionally, our percolative dielectric composites also exhibited good mechanical performances and good thermostability, with a tensile strength of 71.7 MPa, a tensile modulus of 1.91 GPa, a breaking elongation of 16.4%, and a mass loss temperature at 5% of 336°C

Numerical simulations of ultra-low-Re flow around two tandem airfoils in ground effect: isothermal and heated conditions

The advent of pico-aerial vehicles (PAVs) for thermal surveillance has necessitated a better understanding of the flow field around airfoils at ultra-low Reynolds numbers (102 to 103). Previous studies have shown that two airfoils arranged in a tandem configuration can exhibit better aerodynamic performance than two identical airfoils in isolation, but this improvement has only been confirmed at relatively high Reynolds numbers (105 and above). In this parametric study, we numerically simulate the two-dimensional flow field around two tandem NACA 0012 airfoils in ground effect, at a Reynolds number low enough to be relevant to PAVs (Re = 500). With the angle of attack fixed at α = 5° on both airfoils, we investigate the effects of three control parameters, namely the stagger distance, the gap height and the ground clearance, for both isothermal airfoils and fore-heated airfoils. Results show that consistent with previous studies at higher Re, two tandem airfoils are more aerodynamically efficient than two identical airfoils in isolation, especially when the gap height is positive, i.e., when the fore airfoil is higher than the aft airfoil. The aerodynamics of the tandem-airfoil system are strongly influenced by the airfoil-to-airfoil interference arising from the downwash generated by the fore airfoil. The presence of a laminar separation bubble on the suction surface of both airfoils is found to alter the lift and drag coefficients as well as the overall lift-to-drag ratio. The wake of the fore airfoil is often seen impinging on the aft airfoil, which is a key mechanism by which the lift and drag forces are altered. The gains in aerodynamic efficiency achieved by the tandem airfoils become smaller as the stagger distance increases owing to weakened airfoil-to-airfoil interference. The effect of ground clearance on the tandem airfoils is found to be similar to that on two isolated airfoils, with both the lift and drag coefficients increasing with decreasing ground clearance. Heating the fore airfoil of a tandem-airfoil system in ground effect is found to decrease the lift coefficient without much affecting the drag coefficient, resulting in a drop in the lift-to-drag ratio. Overall these results lend new insight into the ultra-low-Re aerodynamics of tandem airfoils under both isothermal and heated conditions, advancing the development of the next generation of PAVs for thermal surveillance and other assorted applications

Quantum simulation investigation of work-function variation in nanowire tunnel FETs

The variability induced by the work-function variation (WFV) in p-type ultra-scaled nanowire tunnel FET (TFET) has been studied by using the Non-Equilibrium Green's Function module implemented in University of Glasgow quantum transport simulator called NESS. To provide a thorough insight into the influence of WFV, we have simulated 250 atomistically different nanowire TFETs and the obtained results are compared to nanowire MOSFETs first. Our statistical simulations reveal that the threshold voltage (Vth) variations of MOSFETs and TFETs are comparable, whereas the on-current (Ion) and off-current (Ioff) variations of TFETs are smaller and higher, respectively in comparison to the MOSFET. Based on the results of the simulations, we have provided a physical insight into the variations of the Ion and Ioff currents. Then, we compared the nanowire and Fin TFETs structures with different oxide thickness in terms of the WFV-induced variability. The results show that WFV has a strongest impact on the Ioff, and moderate effect on the Ion and Vth in nanowire TFET with smaller oxide thickness. Lastly, it is found that compared with the random discrete dopants, WFV is a relatively weaker variability source in ultra-scaled nanowire TFETs, especially from the point of view of Ion variation