Systematic characterization of Cl2 reactive ion etchingfor improved ohmics in AlGaN/GaN HEMTs

Pre-metal-deposition reactive ion etching (RIE) was performed on an Al_0.3Ga_0.7N/AlN/GaN heterostructure in order to improve the metal-to-semiconductor contact resistance. An optimum AlGaN thickness for minimizing contact resistance was determined. An initial decrease in contact resistance with etching time was explained in terms of removal of an oxide surface layer and/or by an increase in tunnelling current with the decrease of the AlGaN thickness. The presence of a dissimilar surface layer was confirmed by an initial nonuniform etch depth rate. An increase in contact resistance for deeper etches was experienced. The increase was related to depletion of the two-dimensional (2-D) electron gas (2-DEG) under the ohmics. Etch depths were measured by atomic force microscopy (AFM). The contact resistance decreased from about 0.45 Ωmm for unetched ohmics to a minimum of 0.27 Ωmm for 70 Å etched ohmics. The initial thickness of the AlGaN layer was 250 Å. The decrease in contact resistance, without excessive complications on device processing, supports RIE etching as a viable solution to improve ohmic contact resistance in AlGaN/GaN HEMTs     

A robust adaptive pole‐placement controller without strictly positive real condition

This paper considers the adaptive pole‐placement control problem for system (1) with unmodelled dynamics η_n dominated by a small constant ε multiplied by a quantity independent of ε but tending to infinity as the past input, output, and noise grow. Using bounded external excitation and randomly varying truncation techniques, we give a design method of adaptive pole‐placement controller. It is shown that the closed‐loop system is globally stable, the estimation error for the parameter contained in the modelled part is of order ε, and the closed‐loop system under the adaptive pole‐placement control law is suboptimal in the sense of $$\mathop{\lim\sup}\limits_{{n\to\infty }}{1\over n}\mathop{\sum}\limits_{i=0}^n{\left({A^{*}(z)y_{n}‐L(z)C(z)w_{n}‐B(z)R(z)y_{n}^{*}}\right)^{2}{\leq}O({\varepsilon}^{2})+\gamma^{2}\mathop{\sum}\limits_{j=1}^q{b_{j}^{2}}}$$\nopagenumbers\end while the SPR condition used usually in other papers is replaced by a stability condition. Copyright © 2001 John Wiley & Sons, Ltd.     

Preparation of flexible polyhedral particles via concentrated emulsion templating polymerization

This paper presents recent efforts on the preparation of flexible polyhedral particles via concentrated emulsion templating polymerization in which the hydrophilic monomer (acrylamide) and hydrophobic monomer (butyl acrylate) are polymerized simultaneously in the continuous and dispersed phase, respectively. Such templating polymerization has been enhanced in our systems owing to the introduction of acrylamide monomer and their higher polymerization rate in continuous phase as compared with butyl acrylate in dispersed phase. Diffusion between the different phases was also inhibited. Furthermore, the stability of the concentrated emulsion and the molecular weight of the produced poly(butyl acrylate) were found to be significantly affected by the amount of redox initiator. The morphology of the particles could be controlled by varying the volume fraction of the dispersed phase and the polyhedral particles were achieved at higher volume fraction. Copyright © 2005 Society of Chemical Industry     

Ring‐opening polymerization of D,L‐lactide by rare earth 2,6‐dimethylaryloxide

Ring‐opening polymerization of D,L ‐lactide (LA) has been successfully carried out by using rare earth 2,6‐dimethylaryloxide (Ln(ODMP)₃) as single component catalyst or initiator for the first time. The effects of different rare earth elements, solvents, monomers and catalyst concentration as well as polymerization temperature and time on the polymerization were investigated. The results show that La(ODMP)₃ exhibits higher activity to prepare poly(D,L ‐lactide) (PLA) with a viscosity molecular weight of 4.5 × 10⁴ g mol^?1 and the conversion of 97 % at 100 °C in 45 min. The catalytic activity of Ln(ODMP)₃ has following sequence: La > Nd > Sm > Gd > Er > Y. A kinetic study has indicated that the polymerization is first order with respect to both monomer and catalyst concentration. The apparent activation energy of the polymerization of LA with La(ODMP)₃ is 69.6 kJ mol^?1. The analyses of polymer ends indicate that the LA polymerization proceeds according to ‘coordination–insertion’ mechanism with selective cleavage of the acyl–oxygen bond of the monomer. Copyright © 2004 Society of Chemical Industry     

Optimal transfer trees and distinguishing trees for testing observable nondeterministic finite-state machines

The fault-state detection approach for blackbox testing consists of two phases. The first is to bring the system under test (SUT) from its initial state to a targeted state t and the second is to check various specified properties of the SUT at t. This paper investigates the first phase for testing systems specified as observable nondeterministic finite-state machines with probabilistic and weighted transitions. This phase involves two steps. The first step transfers the SUT to some state t' and the second step identifies whether t' is indeed the targeted state t or not. State transfer is achieved by moving the SUT along one of the paths of a transfer tree (TT) and state identification is realized by using diagnosis trees (DT). A theoretical foundation for the existence and characterization of TT and DT with minimum weighted height or minimum average weight is presented. Algorithms for their computation are proposed.     

Domain-Driven, Actionable Knowledge Discovery

Data mining increasingly faces complex challenges in the real-life world of business problems and needs. The gap between business expectations and R&D results in this area involves key aspects of the field, such as methodologies, targeted problems, pattern interestingness, and infrastructure support. Both researchers and practitioners are realizing the importance of domain knowledge to close this gap and develop actionable knowledge for real user needs.