Using photoluminescence as optimization criterion to achieve high-quality InGaAs/AlGaAs pHEMT structure

The single delta -doped InGaAs/AlGaAs pseudomorphic HEMT structure materials were grown by molecular beam epitaxy. The photoluminescence spectra of the materials were studied. There are two peaks in the photoluminescence spectra of the materials, corresponding to two sub energy levels of InGaAs quantum well. The ratio of the two peak's intensity was used as criterion to optimize the layer structures of the materials. The material with optimized layer ;tructures exhibits the 77 It mobility and two-dimensional electron gas density of 16 500 cm(2)/Vs and 2.58 x 10(12) cm(-2) respectively, and the 300 K mobility and two-dimensional electron gas density of 6800 cm(2)/Vs and 2.55 x 10(12) cm(-2) respectively. The pseudomorphic HEMT devices with gate length of 0.2 mum were fabricated using this material. The maximum transconductance of 650 mS/mm and the cut-off frequency of 81 GHz were achieved. (C) 2001 Elsevier Science B.V. All rights reserved.

Modeling and optimization of semiconductor manufacturing process with neural networks

A neural network-based process model is proposed to optimize the semiconductor manufacturing process. Being different from some works in several research groups which developed neural network-based models to predict process quality with a set of process variables of only single manufacturing step, we applied this model to wafer fabrication parameters control and wafer lot yield optimization. The original data are collected from a wafer fabrication line, including technological parameters and wafer test results. The wafer lot yield is taken as the optimization target. Learning from historical technological records and wafer test results, the model can predict the wafer yield. To eliminate the "bad" or noisy samples from the sample set, an experimental method was used to determine the number of hidden units so that both good learning ability and prediction capability can be obtained.

Operational Optimization of GaN Thin Film Growth Employing Numerical Simulation in a Showerhead MOCVD Reactor

A detailed reaction-tran sport model was studied in a showerhead reactor for metal organic chemical vapor deposition of GaN film by using computational fluid dynamics simulation. It was found that flat flow lines without swirl are crucial to improve the uniformity of the film growth, and thin temperature gradient above the suscptor can increase the film deposition rate. By above-mentioned research, we can employ higher h (the distance from the susceptor to the inlet), P (operational pressure) and the rate of susceptor rotation to improve the film growth.

Optimization of VI/II pressure ratio in ZnTe growth on GaAs(001) by molecular beam epitaxy

ZnTe epilayers were grown on GaAs(0 0 1) substrates by molecular beam epitaxy (MBE) at different VI/II beam equivalent pressure (BEP) ratios (R-VI/II) in a wide range of 0.96-11 with constant Zn flux. Based on in situ reflection high-energy electron diffraction (RHEED) observation, two-dimensional (2D) growth mode can be formed by increasing the R-VI/II to 2.8. The Te/Zn pressure ratios lower than 4.0 correspond to Zn-rich growth state, while the ratios over 6.4 correspond to Te-rich one. The Zn sticking coefficient at various VI/II ratios are derived by the growth rate measurement. The ZnTe epilayer grown at a R-VI/II of 6.4 displays the narrowest full-width at half-maximum (FWHM) of double-crystal X-ray rocking curve (DCXRC) for (0 0 4) reflection. Atomic force microscopy (AFM) characterization shows that the grain size enlarges drastically with the R-VI/II. The surface root-mean-square (RMS) roughness decreases firstly, attains a minimum of 1.14 nm at a R-VI/II of 4.0 and then increases at higher ratios. It is suggested that the most suitable R-VI/II be controlled between 4.0 and 6.4 in order to grow high-quality ZnTe epitaxial thin films.

An Enhanced Particle Swarm Optimization Algorithm

Particle Swarm Optimization (PSO) algorithm is often used for finding optimal solution, but it easily entraps into the local extremum in later evolution period. Based on improved chaos searching strategy, an enhanced particle swarm optimization algorithm is proposed in this study. When particles get into the local extremum, they are activated by chaos search strategy, where the chaos search area is controlled in the neighborhood of current optimal solution by reducing search area of variables. The new algorithm not only gets rid of the local extremum effectively but also enhances the precision of convergence significantly. Experiment results show that the proposed algorithm is better than standard PSO algorithm in both precision and stability.

Optimization of biodiesel production from trap grease via acid catalysis

As a kind of waste collected from restaurants, trap grease is a chemically challenging feedstock for biodiesel production for its high free fatty acid (FFA) content. A central composite design was used to evaluate the effect of methanol quantity, acid concentration and reaction time on the synthesis of biodiesel from the trap grease with 50% free fatty acid, while the reaction temperature was selected at 95 degrees C. Using response surface methodology, a quadratic polynomial equation was obtained for ester content by multiple regression analysis. Verification experiments confirmed the validity of the predicted model. To achieve the highest ester content of crude biodiesel (89.67%), the critical values of the three variables were 35.00 (methanol-to-oil molar ratio), 11.27 wt% (catalyst concentration based on trap grease) and 4.59 h (reaction time). The crude biodiesel could be purified by a second distillation to meet the requirement of biodiesel specification of Korea.

Optimization and comparison of single- and dual-pump fiber-optical parametric amplifiers with dispersion fluctuations

Solutions for fiber-optical parametric amplifiers (FOPAs) with dispersion fluctuations are derived using matrix operators. On the basis of the propagation matrix product and the hybrid genetic algorithm, we have optimized and compared single- and dual-pump FOPAs with zero-dispersion-wavelength variations. The simulations prove that the design of FOPAs involves multimodal function optimization problems. The numerical results show that dual-pump FOPAs are highly sensitive to dispersion fluctuations whereas dispersion variations have less impact on the gain of single-pump FOPAs. To increase signal gain and reduce ripple, dual-pump FOPAs, instead of single-pump FOPAs, have to be carefully optimized with a suitable multisegment fiber structure rather than a one-segment fiber structure. The different combinations of multisegment fibers can provide highly different gain properties. The increase in gain is at the cost of the ripple.

Optimization of multiple filamentation of femtosecond laser pulses in air using a pinhole

The robustness and prolongation of multiple filamentation (MF) for femtosecond laser propagation in air are investigated experimentally and numerically. It is shown that the number, pattern, propagation distance, and spatial stability of MF can be controlled by a variable-aperture on-axis pinhole. The random MF pattern can be optimized to a deterministic pattern. In our numerical simulations, we configured double filaments to principlly simulate the experimental MF interactions. It is experimentally and numerically demonstrated that the pinhole can reduce the modulational instability of MF and is favorable for a more stable MF evolution. (c) 2007 Optical Society of America.

Distortion management of SBS slow light in a single-mode optical fiber by optimization of broadband SBS gain spectrum

SPIE

Composition Optimization of Tellurite Glass for Low-Loss and Robust Fiber Fabrication

低损耗高强度碲酸盐玻璃光纤用光学材料的优化方案