M.R.

Publications

2 The Upconversion of co-doped Nd3+/Er3+Tellurite Glass

Authors: Azman, K., Sahar, M.R., Rohani, M.S.

Abstract:

Series of tellurite glass of the system 78TeO2-10PbO- 10Li2O-(2-x)Nd2O3-xEr2O3, where x = 0.5, 1.0, 1.5 and 2.0 was successfully been made. A study of upconversion luminescence of the Nd3+/Er3+ co-doped tellurite glass has been carried out. From Judd-Ofelt analysis, the experimental lifetime, exp. τ of the glass serie are found higher in the visible region as they varies from 65.17ms to 114.63ms, whereas in the near infrared region (NIR) the lifetime are varies from 2.133ms to 2.270ms. Meanwhile, the emission cross section,σ results are found varies from 0.004 x 1020 cm2 to 1.007 x 1020 cm2 with respect to composition. The emission spectra of the glass are found been contributed from Nd3+ and Er3+ ions by which nine significant transition peaks are observed. The upconversion mechanism of the co-doped tellurite glass has been shown in the schematic energy diagrams. In this works, it is found that the excited state-absorption (ESA) is still dominant in the upconversion excitation process as the upconversion excitation mechanism of the Nd3+ excited-state levels is accomplished through a stepwise multiphonon process. An efficient excitation energy transfer (ET) has been observed between Nd3+ as a donor and Er3+ as the acceptor. As a result, respective emission spectra had been observed.

Keywords: Tellurite glass, co-dopant, upconvertionluminescence spectra

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1 Dust Storm Prediction Using ANNs Technique (A Case Study: Zabol City)

Authors: Jamalizadeh, M.R., Moghaddamnia, A., Piri, J., Arbabi, V., Homayounifar, M., Shahryari, A.

Abstract:

Dust storms are one of the most costly and destructive events in many desert regions. They can cause massive damages both in natural environments and human lives. This paper is aimed at presenting a preliminary study on dust storms, as a major natural hazard in arid and semi-arid regions. As a case study, dust storm events occurred in Zabol city located in Sistan Region of Iran was analyzed to diagnose and predict dust storms. The identification and prediction of dust storm events could have significant impacts on damages reduction. Present models for this purpose are complicated and not appropriate for many areas with poor-data environments. The present study explores Gamma test for identifying inputs of ANNs model, for dust storm prediction. Results indicate that more attempts must be carried out concerning dust storms identification and segregate between various dust storm types.

Keywords: prediction, dust storm, Gamma Test, ANNs, Zabol

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