High-power AlGaInP laser diodes with current-injection-free region near the laser facet

A high-power AlGaInP laser diode with current-injection-free region near the facet is successfully fabricated by metaorganic chemical vapor deposition (MOCVD) using the (100) direction n-GaAs substrates with a misorientation of 15 deg toward the (011) direction. The maximum continuous wave output power is about 90 mW for the traditional structure. In comparison, the maximum output power is enhanced by about 67%, and achieves 150 mW for LDs with current-infection-free regions. The fundamental transverse-mode operation is obtained up to 70 mW. Output characteristics at high temperatures are also improved greatly for an LD with a current-injection-free region, and the highest operation temperature is 70 C at 50 mW without kink. The threshold current is about 33 mA, the operation current and the slope efficiency at 100 mW are 120 mA and 0.9 mW/mA, respectively. The lasing wavelength is 658.4 nm at room-temperature 50 mW. (c) 2006 Society of Photo-Optical Instrumentation Engineers.

Intense room temperature near infrared emission from Al (3+) and Yb3+ ions

Intense near infrared emission was observed from Al3+ and Yb3+ ions co-implanted SiO2 film on silicon. It was found that the addition of Al3+ ions could remarkably improve the photoluminescence efficiency of Yb3+-implanted SiO2 film. No excitation power saturation was observed and trivial temperature quenching factor of 2 was achieved.

Fast Discrimination of Commerical Corn Varieties Based on Near Infrared Spectra

The existing methods for the discrimination of varieties of commodity corn seed are unable to process batch data and speed up identification, and very time consuming and costly. The present paper developed a new approach to the fast discrimination of varieties of commodity corn by means of near infrared spectral data. Firstly, the experiment obtained spectral data of 37 varieties of commodity corn seed with the Fourier transform near infrared spectrometer in the wavenurnber range from 4 000 to 12 000 cm (1). Secondly, the original data were pretreated using statistics method of normalization in order to eliminate noise and improve the efficiency of models. Thirdly, a new way based on sample standard deviation was used to select the characteristic spectral regions, and it can search very different wavenumbers among all wavenumbers and reduce the amount of data in part. Fourthly, principal component analysis (PCA) was used to compress spectral data into several variables, and the cumulate reliabilities of the first ten components were more than 99.98%. Finally, according to the first ten components, recognition models were established based on BPR. For every 25 samples in each variety, 15 samples were randomly selected as the training set. The remaining 10 samples of the same variety were used as the first testing set, and all the 900 samples of the other varieties were used as the second testing set. Calculation results showed that the average correctness recognition rate of the 37 varieties of corn seed was 94.3%. Testing results indicate that the discrimination method had higher precision than the discrimination of various kinds of commodity corn seed. In short, it is feasible to discriminate various varieties of commodity corn seed based on near infrared spectroscopy and BPR.

A New Discrimination Method of Maize Seed Varieties Based on Near-Infrared Spectroscopy

A new discrimination method for the maize seed varieties based on the near-infrared spectroscopy was proposed. The reflectance spectra of maize seeds were obtained by a FT-NIR spectrometer (12 000-4 000 cm(-1)). The original spectra data were preprocessed by first derivative method. Then the principal component analysis (PCA) was used to compress the spectra data. The principal components with the cumulate reliabilities more than 80% were used to build the discrimination models. The model was established by Psi-3 neuron based on biomimetic pattern recognition (BPR). Especially, the parameter of the covering index was proposed to assist to discriminating the variety of a seed sample. The authors tested the discrimination capability of the model through four groups of experiments. There were 10, 18, 26 and 34 varieties training the discrimination models in these experiments, respectively. Additionally, another seven maize varieties and nine wheat varieties were used to test the capability of the models to reject the varieties not participating in training the models. Each group of the experiment was repeated three times by selecting different training samples at random. The correct classification rates of the models in the four-group experiments were above 91. 8%. The correct rejection rates for the varieties not participating in training the models all attained above 95%. Furthermore, the performance of the discrimination models did not change obviously when using the different training samples. The results showed that this discrimination method can not only effectively recognize the maize seed varieties, but also reject the varieties not participating in training the model. It may be practical in the discrimination of maize seed varieties.

Laser irradiation cell photothermal therapy assisted by gold nanoparticles

The strong absorption of gold nanoparticles in the visible spectral range allows the localized generation of heat in a volume of only a few tens of nanometer. The efficient conversion of strongly absorbed light by plasmonic gold nanoparticles to heat energy and their easy bioconjugation suggest that the gold nanoparticles can be used as selective photothermal agents in molecular cell targeting. The selective destruction of alkaline phosphatase, the permeabilization of the cell membrane and the selective killing of cells by laser irradiating gold nanoparticles were demonstrated. The potential of using this selective technique in molecularly targeted photothermal therapy and transfection is discussed.