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Ion implantation process is a critical step in the microfabrication of thin film transistors. Defects due to the implantation process not only seriously degrade the performance of the devices, but also are hardly detected via traditional electron microscopic techniques alone, including scanning electron microscopy (SEM), Transmission Electron Microscopy (TEM) and focused ion beam (FIB), etc. Wet chemical stain technique, such as junction stain, is an effective method to identify the defect area because of the different etching rates caused by ion implantation concentration. In this paper, a photoresist related implantation issue was reported, and a planar staining technique was developed to directly identify the defects from the suspected failure area by combining the junction stain and SEM techniques. More importantly, the planar staining technique for the photoresist related implantation issues is convenient, time-saving, and effective, as there is no need to prepare cross-section samples for SEM observation.

the Scandium (Sc) diffusion in silicon oxide (SiO2) from ScAlN thin film was investigated using Secondary Ion Mass Spectrometry (SIMS) instead of using the X-Ray Diffraction (XRD) and Transmission Electron Microscope (TEM) techniques. Sc, Al, and Si elements depth profiles were performed from sample front side and back side. Al and Sc performance at ScAlN/SiO2 interface and in SiO2 layer was compared for two conditions, annealed and non-annealed. To obtain precise test result, an effective sample preparation was implemented, which will be discussed in the paper.

In this paper, we present a study on protective coating techniques for thin film X-TEM sample preparation. The study shows that proper choice of the protective layer before FIB cross section is a crucial step to maintain the film profile and make sure the accuracy of the thickness measurement. Silicon native oxide is used as the target sample. We have investigated PECS metal sputtering followed by ink coating, e-beam Pt and sputter Pt followed by ink coating. The granular feature of e-beam Pt coating is unwanted during native oxide thickness measurement. The PECS metal sputtering will create a damaged layer on top of the silicon substrate due to its high sputter energy. The damaged layer disguises the original substrate/oxide interface and leads the oxide thickness more difficult. The sputter Pt is the proper coating method based on this study. It provides a relative flat interface with high contrast at top of the oxide layer and does little damage to the substrate due to the low sputter energy.

Flow regime identification is very practical and academic significance for cavity research in cooling pump of engine but it is very complicated. A novel classification model that combined the particle swarm optimization (PSO) with support vector Machine (SVM) was put forward for flow regime identification in this study. This hybrid model seeks for SVM's optimal parameters in whole field and isn't prone to get in local minimization. It is easy to realize and tune SVM's parameters and has stronger ability to resolve nonlinear, non-differential and multimode problem. This identification model was validated by the test based on empirical mode decomposition (EMD), which extracted flow regime feature from differential pressure fluctuation. The result showed that this method has superiority of rapider training, better generality and higher accuracy of flow regime identification.

The large time-delay objects widely exist in industry process and they are difficult to be controlled especially when control coefficient is bigger than 0.5, a hybrid control method with on-line parameters adjustment is adopted to maintain the pressed air pressure of a coal mine at a const value. The Fuzzy-PID controller discussed here has a one-order feedback loop which can decrease lag time, for the more, it can adjust PID parameters online with Fuzzy logic according to the pressure value and its changing rate. simulation and practical running indicate that its tracking precision and converging speed are high, ability of coping with model uncertainty is strong and its realization is easy.

Grade estimation is one of the most complicated aspects in mining. Its complexity originates from scientific uncertainty. In this paper, a fuzzy wavelet neural network (FWNN) is proposed for grade estimation. This fuzzy neural network uses wavelet basis function as membership function whose shape can be adjusted on line so that the networks have better learning and adaptive ability. The new FWNN method combing the properties of the fuzzy computing and the advantages of wavelet neural networks provide fast and reliable ore grade estimation, with minimum assumptions and minimum requirements for modeling skills. The FWNN grade estimation method has been tested on a number of real deposits. The result shows that the FWNN has advantages of rapid training, generality and accuracy grade estimation approach. It can provide with a very fast and robust alternative to the existing time-consuming methodologies for ore grade estimation.

A novel and more effective algorithm used for segmenting pulmonary nodules in thoracic spiral CT images was presented. The algorithm is based on mean shift clustering method and CI (Convergence Index) features, which can represent the multiple Gaussian model of pulmonary nodules both for solid and sub-solid, substantially. The algorithm has the following steps: (1) calculating the CI features of all pixels in the region of interest (ROI), (2) combining the CI features with the intensity range and the spatial position of the pixels to form a feature vector set, (3) grouping the feature vector set to clusters with mean shift clustering algorithm. Owing to our algorithm can represent the multiple Gaussian model both for solid and sub-solid nodules, it can be used in any user interested nodule regions, especially suitable for the segmentation of sub-solid nodules. Experiments demonstrated that our algorithm can figure out the outline of pulmonary nodules of different forms more precisely.

We propose a new dual transmission gate adiabatic logic (DTGAL) for ultra-low-power design, which is driven by three-phase AC power supply. DTGAL has more efficient energy transfer and recovery, because it hasn't the non-adiabatic energy loss. We also discuss the design of adiabatic sequential circuits. For the energy-efficient design, we explained how to design an adiabatic D flip-flops with DTGAL. A practical sequential system was designed and demonstrated using MOSIS 0.25mm CMOS process parameters. SPICE simulation results show that the adiabatic flip-flop based on DTGAL is 3 to 4.5 times more energy efficient than 2N-2N2P for clock rates ranging from 50 to 200MHz. In conclusion, DTGAL has better energy saving advantage, and adiabatic D flip-flop based on DTGAL is suitable for the applications in the low-power sequential system.