Transport mechanism of reverse surface leakage current in AlGaN/GaN high-electron mobility transistor with SiN passivation

The transport mechanism of reverse surface leakage current in the AlGaN/GaN high-electron mobility transistor（HEMT） becomes one of the most important reliability issues with the downscaling of feature size.In this paper,the research results show that the reverse surface leakage current in AlGaN/GaN HEMT with SiN passivation increases with the enhancement of temperature in the range from 298 K to 423 K.Three possible transport mechanisms are proposed and examined to explain the generation of reverse surface leakage current.By comparing the experimental data with the numerical transport models,it is found that neither Fowler-Nordheim tunneling nor Frenkel-Poole emission can describe the transport of reverse surface leakage current.However,good agreement is found between the experimental data and the two-dimensional variable range hopping（2D-VRH） model.Therefore,it is concluded that the reverse surface leakage current is dominated by the electron hopping through the surface states at the barrier layer.Moreover,the activation energy of surface leakage current is extracted,which is around 0.083 eV.Finally,the SiN passivated HEMT with a high Al composition and a thin AlGaN barrier layer is also studied.It is observed that 2D-VRH still dominates the reverse surface leakage current and the activation energy is around 0.10 eV,which demonstrates that the alteration of the AlGaN barrier layer does not affect the transport mechanism of reverse surface leakage current in this paper.

METHOD TO EXTRACT BLEND SURFACE FEATURE IN REVERSE ENGINEERING

A new method of extraction of blend surface feature is presented. It contains two steps: segmentation and recovery of parametric representation of the blend. The segmentation separates the points in the blend region from the rest of the input point cloud with the processes of sampling point data, estimation of local surface curvature properties and comparison of maximum curvature values. The recovery of parametric representation generates a set of profile curves by marching throughout the blend and fitting cylinders. Compared with the existing approaches of blend surface feature extraction, the proposed method reduces the requirement of user interaction and is capable of extracting blend surface with either constant radius or variable radius. Application examples are presented to verify the proposed method.

PDGI-BASED REGULAR SWEPT SURFACE EXTRACTION FROM POINT CLOUD

A principal direction Gaussian image （PDGI）-based algorithm is proposed to extract the regular swept surface from point cloud. Firstly, the PDGI of the regular swept surface is constructed from point cloud, then the bounding box of the Gaussian sphere is uniformly partitioned into a number of small cubes （3D grids） and the PDGI points on the Gaussian sphere are associated with the corresponding 3D grids. Secondly, cluster analysis technique is used to sort out a group of 3D grids containing more PDGI points among the 3D grids. By the connected-region growing algorithm, the congregation point or the great circle is detected from the 3D grids. Thus the translational direction is determined by the congregation point and the direction of the rotational axis is determined by the great circle. In addition, the positional point of the rotational axis is obtained by the intersection of all the projected normal lines of the rotational surface on the plane being perpendicular to the estimated direction of the rotational axis. Finally, a pattem search method is applied to optimize the translational direction and the rotational axis. Some experiments are used to illustrate the feasibility of the above algorithm.

Research on ultrasonic detection of complex surfaces

Parts of complex surface are widely used now in many fields, and their detection has caused much concern. In China many manufactories still carry on the traditional way of manual detection, which requires highly skilled personnel and efficiency is low. Some large manufactories have imported auto-detecting equipments, which require CAD data on the parts, or just divide the surface into several approximate planes for automatic detection. Phased-array system is seldom used, and the cost is high. Besides, most of the systems have not considered the automatic sensitivity compensation of parts with varying thickness. To improve the detection quality and efficiency of nondestructive test (NDT) of parts of complex surface, this paper puts forward an integrated ultrasonic NDT system characterized by: (1) Use of ultrasonic measurement and reverse of curved surface to solve the CAD data problem; (2) Use of an automatic sensitivity compensation algorithm (based on the part’s modelling information obtained in surface reverse) to fit the variety of the thickness; (3) Use of template matching and pseudo-color imaging to improve the quality of detection results. The system features integration of low cost mature technologies, and is suitable for detection of various parts of different complex surfaces in medium-and-small enterprises. The test results showed that the system can automatically detect parts of complex surface successfully, and that the inspection result is good and reliable.

PHYSICS-BASED ILLUMINATION MODEL FOR METAL SURFACE RECONSTRUCTION IN RE

Representation of roughness is introduced and the rationality of applying thephysics-based model in RE is analyzed at first. Then the scattering theory of electromagnetic waveis simplified and deduced to a physics-based model according to the characteristics of the surfaceto be reconstructed in RE. At last, the intensity diagrams of reflected field distribution areprovided to prove the feasibility of the presented model and some spheres are rendered with thismodel.

REVERSE MODELING FOR CONIC BLENDING FEATURE

A novel method to extract conic blending feature in reverse engineering is presented. Different from the methods to recover constant and variable radius blends from unorganized points, it contains not only novel segmentation and feature recognition techniques, but also bias corrected technique to capture more reliable distribution of feature parameters along the spine curve. The segmentation depending on point classification separates the points in the conic blend region from the input point cloud. The available feature parameters of the cross-sectional curves are extracted with the processes of slicing point clouds with planes, conic curve fitting, and parameters estimation and compensation, The extracted parameters and its distribution laws are refined according to statistic theory such as regression analysis and hypothesis test. The proposed method can accurately capture the original design intentions and conveniently guide the reverse modeling process. Application examples are presented to verify the high precision and stability of the proposed method.

Bi-Cubic B-Spline Fitting-Based Local Volatility Model with Mean Reversion Process

This paper studies the traditional local volatility model and proposes:A novel local volatility model with mean-reversion process.The larger is the gap between local volatility and its mean level,the higher will be the rate at which local volatility will revert to the mean.Then,a B-spline method with proper knot control is applied to interpolate the local volatility matrix.The bi-cubic B-spline is used to recover the local volatility surface from this local volatility matrix.Finally,empirical tests show that the proposed mean-reversion local volatility model offers better prediction performance than the traditional local volatility model.