Accurately determining numerical values for key model parameters for any semiconductor devices is extremely important for analyzing the device characteristics and model-based device design optimization. However, their experimental determination can be very difficult since measurement results involve interaction of many parameters and isolating the influence of a single parameter is often not possible. One of the ways to solve this issue is deep learning. We achieve accurate determination of key laser diode model parameters such as internal loss, Auger coefficient, and free-carrier absorption coefficient of a fabricated ridge-waveguide 850 nm GaAs/AlGaAs laser diode(LD) applying the trained deep neural network (DNN). We use a LD TCAD simulator, PICS3D, for producing training and testing data. The accuracy of our approach is confirmed by comparing the simulation result with the actual measurement result for the LD L-I characteristics using extracted model parameters by DNN.
975-nm laser diodes (LDs) are of great demand as pumping sources for Yb-doped fiber lasers. They should provide high output power with high efficiency and good beam quality. In order to satisfy these requirements, the LD structure should be carefully designed. In this paper, we report the results of our investigation in which the influence of the LD emitter width on the maximum output power, power-conversion efficiency (PCE) and beam parameter product (BPP) are analyzed with self-consistent electro-thermal-optical simulation of LDs. In order to establish the accuracy of our simulation, we carefully determine the numerical values of key LD parameters by fitting the simulation results to the measured results for a fabricated 975-nm LD. The device has 15-nm-thick tensile-strained InGaAsP single quantum well with asymmetric AlGaAs separate confinement heterostructure layers, 90-μm wide ridge, and 4-mm long cavity. With the parameter values obtained, LDs having various emitter widths are simulated and their maximum output powers, PCEs, and BPPs are determined as well as the temperature profiles inside the device. The results show that the device with the smaller emitter width has both of thermal roll-over, thermal blooming at the lower output power, mostly due to higher series resistance. However, it provides better BPP. These results are useful for optimizing LD array structures so that the optimal structure for each array element can be determined that can provide the highest possible output power with the best BPP.
The characteristics of high-power broad-area laser diodes with the improved heat sinking structure are numerically analyzed by a technology computer-aided design based self-consistent electro-thermal-optical simulation. The high-power laser diodes consist of a separate confinement heterostructure of a compressively strained InGaAsP quantum well and GaInP optical cavity layers, and a 100-μm-wide rib and a 2000-μm long cavity. In order to overcome the performance deteriorations of high-power laser diodes caused by self-heating such as thermal rollover and thermal blooming, we propose the high-power broad-area laser diode with improved heat-sinking structure, which another effective heat-sinking path toward the substrate side is added by removing a bulk substrate. It is possible to obtain by removing a 400-μm-thick GaAs substrate with an AlAs sacrificial layer utilizing well-known epitaxial liftoff techniques. In this study, we present the performance improvement of the high-power laser diode with the heat-sinking structure by suppressing thermal effects. It is found that the lateral far-field angle as well as quantum well temperature is expected to be improved by the proposed heat-sinking structure which is required for high beam quality and optical output power, respectively.
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