178 resultados para Near-infrared emission


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Infrared (1.2-1.6 mum) luminescence in a yttrium aluminium garnet (YAG) crystal, co-doped with Yb (10 at.%) and Cr (0.05 at.%) ions, was investigated under CW laser diode pumping (lambda = 940 nm). The Cr4+ emission band was observed with its peak at 1.35 mum and measured to be about 6% with respect to Yb3+ IR luminescence (lambda = 1.03 mum). Analysis of the crystal absorption and luminescence spectra allows one to conclude that Yb3+-Cr4+ energy transfer is a mechanism responsible for the B-3(2)(T-3(2))-B-3(1)((3)A(2)) emission of Cr4+ ions. This crystal is promising as an efficient source of the near infrared emission. (C) 2004 Elsevier B.V. All rights reserved.

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Er/Bi codoped SiO2 thin films were prepared by sol-gel method and spin-on technology with subsequent annealing process. The bismuth silicate crystal phase appeared at low annealing temperature while vanished as annealing temperature exceeded 1000 degrees C, characterized by X-ray diffraction, and Rutherford backscattering measurements well explained the structure change of the films, which was due to the decrease of bismuth concentration. Fine structures of the Er3+-related 1.54 mu m light emission (line width less than 7 nm) at room temperature was observed by photoluminescence (PL) measurement. The PL intensity at 1.54 gm reached maximum at 800 degrees C and decreased dramatically at 1000 degrees C. The PL dependent annealing temperature was studied and suggested a clear link with bismuth silicate phase. Excitation spectrum measurements further reveal the role of Bi3+ ions for Er3+ ions near infrared light emission. Through sol-gel method and thermal treatment, Bi3+ ions can provide a perfect environment for Er3+ ion light emission by forming Er-Bi-Si-O complex. Furthermore, energy transfer from Bi3+ ions to Er3+ ions is evidenced and found to be a more efficient way for Er3+ ions near infrared emission. This makes the Bi3+ ions doped material a promising application for future erbium-doped waveguide amplifier and infrared LED

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A two dimensional silicon-on-insulator based photonic crystal structure is used to enhance the emission from colloidal HgTe nanocrystal quantum dots embedded in a thin polymer film. The enhancement is resonant to the leaky eigenmodes of the photonic crystals due to coherent scattering effects. Transmittance and photoluminescence experiments are presented to map the leaky mode dispersion and the angle dependence of the emission enhancement factor, which reaches values up to 80 (650) for vertical (oblique) emission in the telecommunication wavelength range.

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The admixture of linear and circular photogalvanic effects and (CPGEs) in AlxGa1-xN/GaN heterostructures has been investigated quantitatively by near-infrared irradiation at room temperature. The spin-based photocurrent that the authors have observed solidly indicates the sizable spin-orbital interaction of the two-dimensional electron gas in the heterostructures. Further analysis shows consistency between studies by optical and magnetic (Shubnikov de-Haas) measurements on the spin-orbital coupling effects among different AlxGa1-xN/GaN heterostructures, indicating that the CPGE measurement is a good way to investigate the spin splitting and the spin polarization in semiconductors. (C) 2007 American Institute of Physics.

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A two-dimensional (2D) photonic crystal waveguide in the Gamma-K direction with triangular lattice on a silicon-on insulator (SOI) substrate in the near-infrared band is fabricated by the combination of electron beam lithography and inductively coupled plasma etching. Its transmission characteristics are analysed from the stimulated band diagram by the effective index and the 2D plane wave expansion (PWE) methods. In the experiment, the transmission band edge in a longer wavelength of the photonic crystal waveguide is about 1590 nm, which is in good qualitative agreement with the simulated value. However, there is a disagreement between the experimental and the simulated results when the wavelength ranges from 1607 to 1630 nm, which can be considered as due to the unpolarized source used in the transmission measurement.

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Enhanced near-infrared photoluminescence (PL) from sulfur-related isoelectronic luminescent centers in silicon was observed from thermally quenched sulfur-implanted silicon in which additional copper or silver ions had been coimplanted. The PL from the sulfur and copper coimplanted silicon peaked between 70 and 100 K and persisted to 260 K. This result strongly supports the original conjecture from the optical detection of magnetic resonance studies that the strong PL from sulfur-doped silicon comes from S-Cu isoelectronic complexes [Frens , Phys. Rev. B 46, 12316 (1992); Mason , ibid. 58, 7007 (1998).]. (c) 2007 American Institute of Physics.

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Low indium content InGaN/AlGaN multiple quantum wells (MQWs) have been grown on Si(111) substrate by metal-organic chemical vapour deposition (MOCVD). A new method of using an isoelectronic indium-doped AlGaN barrier has been found to be very effective in improving the crystalline quality and interfacial abruptness of InGaN quantum well layers. We grew five periods of In0.06Ga0.94N/Al0.20Ga0.80N:In MQWs with In-doped barrier layers and obtained strong near-ultraviolet (UV) emission (similar to 400 nm) at room temperature. An In-doped AlGaN barrier improves the room-temperature PL intensity of InGaN/AlGaN MQWs, making it a candidate barrier for a near-UV source on Si substrate.

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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.

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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.