Metalorganic chemical vapor deposition-grown In 0.4 Ga 0.6 As 0.995 N 0.005 quantum well ͑QW͒ lasers have been realized, at an emission wavelength of 1.295 m, with threshold and transparency current densities as low as 211 A/cm 2 ͑for Lϭ2000 m͒ and 75 A/cm 2 , respectively. The utilization of a tensile-strained GaAs 0.67 P 0.33 buffer layer and GaAs 0.85 P 0.15 barrier layers allows a highly-compressively-strained In 0.4 Ga 0.6 As 0.995 N 0.005 QW to be grown on a high-Al-content lower cladding layer, resulting in devices with high current injection efficiency ( inj ϳ97%͒. © 2002 American Institute of Physics. ͓DOI: 10.1063/1.1511290͔The dilute-nitride quantum well ͑QW͒ on GaAs substrate, to achieve 1300-nm wavelength emission, has been a very promising choice active region in realizing highperformance long-wavelength GaAs-based vertical cavity surface emitting lasers ͑VCSELs͒. 1-12 Less temperature sensitivity in InGaAsN QW lasers, at ϭ1300 nm, has also been demonstrated in many of the published results. [1][2][3][4][5][6][7][8][9][10][11][12] Although the area of temperature sensitivity in InGaAsN QW lasers is still under extensive investigation, 13,14 promising results of both low threshold-current-density (J th ) and high T 0 values ͓1/T 0 ϭ(1/J th )dJ th /dT͔ have been demonstrated. 3,6,12 Recently, efforts to achieve high performance InGaAsN QW lasers by metalorganic chemical vapor deposition ͑MOCVD͒ 3-7 have been pursued. The advantage of the MOCVD-grown InGaAsN QW lasers is the ease in growing high quality AlAs/GaAs distributed Bragg reflectors by MOCVD, compared to molecular beam epitaxy ͑MBE͒ techniques, for realizing low-cost VCSELs. Only recently, MOCVD-grown InGaAsN QW lasers, 3-7 at ϭ1300 nm, have demonstrated comparable performances with the MBEgrown InGaAsN QW lasers. [8][9][10][11][12] As shown in our earlier studies, 3 tensile-strained buffer layers ͑InGaPϩGaAsP͒ are crucial for achieving highly strained InGaAs͑N͒ QW lasers grown on thick, highAl-content ͑75%-85%͒ AlGaAs lower cladding layers. In the present work, we report very low threshold (J th )-and transparency (J th )-current-density, strain-compensated In 0.4 Ga 0.6 As 0.995 N 0.005 QW lasers with high current injection efficiency ( inj ) by utilizing strain compensation from GaAsP tensile-strained barriers and a thin GaAsP tensilestrained buffer layer.The lasers structures utilized here were all grown by low-pressure MOCVD. Trimethylgallium, trimethylaluminium, and trimethylindium are used as the group III sources and AsH 3 , PH 3 , and U-dimethylhydrazine ͑U-DMHy͒ are used as the group V sources. The dopant sources are SiH 4 and dielthylzinc for the n-and p-dopants, respectively. The laser structure, shown in Fig. 1, utilizes min. This annealing condition does not represent the optimized annealing temperature and duration for the InGaAsN QW, yet this condition is sufficient for achieving strong luminescence from the QW. The InGaAsN QW is surrounded by tensile-strain barriers of GaAs 0.85 P 0.15 (⌬a/aϭ0.6%͒, which are spaced 100 Å on ...

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Detecting marine mammal vocalizations in underwater acoustic environments and classifying them to species level is typically an arduous manual analysis task for skilled bioacousticians. In recent years, machine learning and other automated algorithms have been explored for quickly detecting and classifying all sound sources in an ambient acoustic environment, but many of these still require a large training dataset compiled through time-intensive manual pre-processing. Here, an application of the signal decomposition technique Empirical Mode Decomposition (EMD) is presented, which does not require a priori knowledge and quickly detects all sound sources in a given recording. The EMD detection process extracts the possible signals in a dataset for minimal quality control post-processing before moving onto the second phase: the EMD classification process. The EMD classification process uniquely identifies and labels most sound sources in a given environment. Thirty-five recordings containing different marine mammal species and mooring hardware noises were tested with the new EMD detection and classification processes. Ultimately, these processes can be applied to acoustic index development and refinement.