Pressure drop and optimization meta-models for arbitrary low-height pleated filter shapes and flowrates

Journal of Mechanical Science and Technology - This study delivers equations useful for low-height pleated fibrous filter design: two pressure drop equations and one set of optimum design equations...     

Output Feedback Regulation of a Class of Lower Triangular Nonlinear Systems with Arbitrary Unknown Measurement Sensitivity

International Journal of Control, Automation and Systems - In this paper, a regulation problem for a class of lower triangular nonlinear systems under unknown measurement sensitivity by output...     

Sparse field level set method for non-convex Hamiltonians in 3D plasma etching profile simulations

Level set method [S. Osher, J. Sethian, J. Comput. Phys. 79 (1988) 12] is a highly robust and accurate computational technique for tracking moving interfaces in various application domains. It originates from the idea to view the moving front as a particular level set of a higher dimensional function, so the topological merging and breaking, sharp gradients and cusps can form naturally, and the effects of curvature can be easily incorporated. The resulting equations, describing interface surface evolution, are of Hamilton-Jacobi type and they are solved using techniques developed for hyperbolic equations. In this paper we describe an extension of the sparse field method for solving level set equations in the case of non-convex Hamiltonians, which are common in the simulations of the profile surface evolution during plasma etching and deposition processes. Sparse field method itself, developed by Whitaker [R. Whitaker, Internat. J. Comput. Vision 29 (3) (1998) 203] and broadly used in image processing community, is an alternative to the usual combination of narrow band and fast marching procedures for the computationally effective solving of level set equations. The developed procedure is applied to the simulations of 3D feature profile surface evolution during plasma etching process, that include the effects of ion enhanced chemical etching and physical sputtering, which are the primary causes of the Hamiltonian non-convexity.     

High-performance MIM capacitor using ALD high-k HfO/sub 2/-Al/sub 2/O/sub 3/ laminate dielectrics

For the first time, we successfully fabricated and demonstrated high performance metal-insulator-metal (MIM) capacitors with HfO/sub 2/-Al/sub 2/O/sub 3/ laminate dielectric using atomic layer deposition (ALD) technique. Our data indicates that the laminate MIM capacitor can provide high capacitance density of 12.8 fF//spl mu/m/sup 2/ from 10 kHz up to 20 GHz, very low leakage current of 3.2 /spl times/ 10/sup -8/ A/cm/sup 2/ at 3.3 V, small linear voltage coefficient of capacitance of 240 ppm/V together with quadratic one of 1830 ppm/V/sup 2/, temperature coefficient of capacitance of 182 ppm//spl deg/C, and high breakdown field of /spl sim/6 MV/cm as well as promising reliability. As a result, the HfO/sub 2/-Al/sub 2/O/sub 3/ laminate is a very promising candidate for next generation MIM capacitor for radio frequency and mixed signal integrated circuit applications.     

Enhanced thermal stability of a sputtered titanium-nitride film as a diffusion barrier for capacitor-bottom electrodes

The effect of a thin RuO_x layer formed on the Ru/TiN/doped poly-Si/Si stack structure was compared with that on the RuO_x/TiN/doped poly-Si/Si stack structure over the post-deposition annealing temperature ranges of 450–600°C. The Ru/TiN/poly-Si/Si contact system exhibited linear behavior at forward bias with a small increase in the total resistance up to 600°C. The RuO_x/TiN/poly-Si/Si contact system exhibited nonlinear characteristics under forward bias at 450°C, which is attributed to no formation of a thin RuO_x layer at the RuO_x surface and porous-amorphous microstructure. In the former case, the addition of oxygen at the surface layer of the Ru film by pre-annealing leads to the formation of a thin RuO_x layer and chemically strong Ru-O bonds. This results from the retardation of oxygen diffusion caused by the discontinuity of diffusion paths. In particular, the RuO_x layer in a nonstoichiometric state is changed to the RuO₂-crystalline phase in a stoichiometric state after post-deposition annealing; this phase can act as an oxygen-capture layer. Therefore, it appears that the electrical properties of the Ru/TiN/poly-Si/Si contact system are better than those of the RuO_x/TiN/poly-Si/Si contact system.     

Wireless-adaptive fair scheduling for multimedia stream

As packet cellular networks are expected to support multimedia services, the authors incorporate the multimedia QoS requirements into the design of a new scheduling algorithm. The proposed wireless-adaptive fair scheduling tries to allocate time slots for each user with fair share by considering the varying channel condition while reflecting the stream requirements and achieving high throughput.     

Fixed-order H∞ compensator design

A method is presented for the construction of fixed-order compensators to provide H_∞ norm constraint for linear control systems with exogenous disturbances. The method is based on the celebrated bounded-real lemma that predicates the H_∞ norm constraint via a Riccati inequality. The synthesis of fixed-order controllers whose dimensions are less than the order of a given plant, is demonstrated by a set of sufficient conditions along with a numerical algorithm.     

Selection of network and learning parameters for an adaptive neural robotic control scheme

This paper presents the results of a study in the design of a neural network based adaptive robotic control scheme. The neural network used here is a two hidden layer feedforward network and the learning scheme is the well-known backpropagation algorithm. The neural network essentially provides the inverse of the plant and acts in conjunction with a standard PD controller in the feedback loop. The objective of the controller is to accurately control the end position of a single link manipulator in the presence of large payload variations, variations in the link length and also variations in the damping constant. Based on results of this study, guidelines are presented in selecting the number of neurons in the hidden layers and also the parameters for the learning scheme used for training the network. Results also indicate that increasing the number of neurons in the hidden layer will improve the convergence speed of learning scheme up to a certain limit beyond which the addition of neurons will cause oscillations and instability. Guidelines for selecting the proper learning rate, momentum and fast backpropagation constant that ensure stability and convergence are presented. Also, a relationship between the r.m.s. error and the number of iterations used in training the neural network is established.     

Reverse short channel effects in high-k gated nMOSFETs

Anomalous threshold voltage roll-up behavior, commonly referred as reverse short channel effect (RSCE), has been observed in high-k (HfO₂ on SiON buffer, Al₂O₃ on SiON buffer) gated submicron nMOSFETs, while the SiO₂ or SiON control samples show normal short channel effect (SCE) behavior. The possible causes such as inhomogeneous channel doping profile and gate oxide thickness variation near S/D ends have been ruled out. The results indicate that interface trap density that dependents on channel length is the main cause of the RSCE observed here. In addition, oxide charge also plays a role.     

Prediction and quality control of the melt index during production of high-density polyethylene

In polyolefin processes the melt index (MI) is the most important control variable indicating product quality. Because of the difficulty in the on-line measurement of MI, a lot of MI estimation and correlation methods have been proposed. In this work a new dynamic MI estimation scheme is developed based on system identification techniques. The empirical MI estimation equation proposed in the present study is derived from the 1 ^st -order dynamic models. Effectiveness of the present estimation scheme was illustrated by numerical simulations based on plant operation data including grade change operations in high density polyethylene (HDPE) processes. From the comparisons with other estimation methods it was found that the proposed estimation scheme showed better performance in MI predictions. The virtual sensor model developed based on the estimation scheme was combined with the virtual on-line analyzer (VOA) to give a quality control system to be implemented in the actual HDPE plant. From the application of the present control system, significant reduction of transition time and the amount of off-spec during grade changes was achieved