This paper has presented a physics–based model which replicates the failure of SiC MOSFET under short–circuit (SC) case. The model is constructed on the base of the traditional circuit model of SiC MOSFET by introducing two leakage current mechanisms, one is the leakage current between the drain and the source, and another is the gate leakage current. Furthermore, the carrier mobility characterized with trapped charges at the interface of SiC/SiO2 is adopted. The failure model had been validated against the experimental results. With the developed failure model, the failure mechanism of SiC MOSFET under a short–circuit event is analyzed, the impact of interface trapped charges on the short–circuit performances of SiC MOSFET is exploited. Moreover, the short–circuit failure for SiC MOSFET with different off–state gate voltages has been addressed, the behavior of interface trapped charges has been analyzed.

The computational methods of protein-protein interaction sites prediction can effectively avoid the shortcomings of high cost and time in traditional experimental approaches. However, the serious class imbalance between interface and non-interface residues on the protein sequences limits the prediction performance of these methods. This work therefore proposed a new strategy, NearMiss-based under-sampling for unbalancing datasets and Random Forest classification (NM-RF), to predict protein interaction sites. Herein, the residues on protein sequences were represented by the PSSM-derived features, hydropathy index (HI) and relative solvent accessibility (RSA). In order to resolve the class imbalance problem, an under-sampling method based on NearMiss algorithm is adopted to remove some non-interface residues, and then the random forest algorithm is used to perform binary classification on the balanced feature datasets. Experiments show that the accuracy of NM-RF model reaches 87.6% and 84.3% on Dtestset72 and PDBtestset164 respectively, which demonstrate the effectiveness of the proposed NM-RF method in differentiating the interface or non-interface residues.

Although plasmas commonly present as electrical neutrality, for plasma jet plume at atmospheric gas pressure, it might appear nonneutral polarity due to plasma bullet being consisted of a large amount of electron avalanches. In this paper, the polarity transition and the ionization enhancement of atmospheric argon plasma jet plumes generated by the repetitive microwave pulses are studied. Three interesting phenomena have been found despite of discharges either with or without the hairpin metal wire, including: 1) a potential voltage pulse with positive polarity invariably arises steeply at each moment of power on; 2) high-speed photograph images show that there are ionization enhancements happened twice in each pulsed periods; and 3) ahead of the confluence point, the polarity transits from negative to positive while behind of this point, its positive polarity changes into the negative one. Moreover, the experiment results and electromagnetic simulations suggest that the theories of guided negative ionization wave and microwave resonant discharge excited by surface plasma polaritons should be used to interpret the spatial-temporal discharge process of the proposed microwave plasma jets.

We analyze the electromagnetic interaction between local surface plasmon polaritons (SPPs) and an atmospheric surface wave plasma jet (ASWPJ) in combination with our designed discharge device. Before discharge, the excitation of the SPPs and the spatial distribution of the enhanced electric field are analyzed. During discharge, the critical breakdown electric field of the gases at atmospheric gas pressure and the surface wave of the SPPs converted into electron plasma waves at resonant points are studied. After discharge, the ionization development process of the ASWPJ is simulated using a two-dimensional fluid model. Our results suggest that the local enhanced electric field of SPPs is merely the precondition of gas breakdown, and the key mechanism in maintaining the discharge development of a low-power ASWPJ is the wave-mode conversion of the local enhanced electric field at the resonant point.

It is critical to measure the electron density and its transient variation in an atmospheric-pressure plasma jet. In the present study, the transient electron density of a pulsed microwave argon plasma jet at atmospheric gas pressure is measured using a homemade microwave Rayleigh scattering device. First, the high-speed photographs of the plasma jet are captured by an intensified charge-coupled device camera. Then, the radius and length of the plasma jet are determined from the high-speed photographs. Finally, the temporal scattering signal measurement is performed and the time-varying electron density is obtained. The electron density increases to a peak value of 4.55 × 10²⁰ m⁻³ at 45 μs. Then, it decays monotonically until it reaches the detection limit. It is worth pointing out that there is no input microwave power after 40 μs, but the electron density still presents a sharp peak. This indicates that there is a change in the ionization process that further induces a variation in the discharge morphology. In addition, an electromagnetic simulation model is modulated to simulate the scattered electric field distributions produced by two different scatterers (air and plasma). The simulation results indicate that a higher electron density of scatterer leads to the acquisition of more intense scattering signals, which indicate that the microwave scattering process is similar to that associated with dipole radiation. These results verify the accuracy of the transient electron density measured using microwave Rayleigh scattering.