Effect of Same-Temperature GaN Cap Layer on the InGaN/GaN Multiquantum Well of Green Light-Emitting Diode on Silicon Substrate

GaN green LED was grown on Si (111) substrate by MOCVD. To enhance the quality of InGaN/GaN MQWs, same-temperature (ST) GaN protection layers with different thickness of 8 Å, 15 Å, and 30 Å were induced after the InGaN quantum wells (QWs) layer. Results show that a relative thicker cap layer is benefit to get InGaN QWs with higher In percent at fixed well temperature and obtain better QW/QB interface. As the cap thickness increases, the indium distribution becomes homogeneous as verified by fluorescence microscope (FLM). The interface of MQWs turns to be abrupt from XRD analysis. The intensity of photoluminescence (PL) spectrum is increased and the FWHM becomes narrow

Displacement Monitoring of a Bridge Based on BDS Measurement by CEEMDAN–Adaptive Threshold Wavelet Method

From the viewpoint of BDS bridge displacement monitoring, which is easily affected by background noise and the calculation of a fixed threshold value in the wavelet filtering algorithm, which is often related to the data length. In this paper, a data processing method of Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN), combined with adaptive threshold wavelet de-noising is proposed. The adaptive threshold wavelet filtering method composed of the mean and variance of wavelet coefficients of each layer is used to de-noise the BDS displacement monitoring data. CEEMDAN was used to decompose the displacement response data of the bridge to obtain the intrinsic mode function (IMF). Correlation coefficients were used to distinguish the noisy component from the effective component, and the adaptive threshold wavelet de-noising occurred on the noisy component. Finally, all IMF were restructured. The simulation experiment and the BDS displacement monitoring data of Nanmao Bridge were verified. The results demonstrated that the proposed method could effectively suppress random noise and multipath noise, and effectively obtain the real response of bridge displacement

Anaerobic Digestion of Aquatic Plants for Biogas Production

7th Global Conference on Global Warming (GCGW) -- JUN 24-28, 2018 -- Izmir, TURKEYWOS: 000587895700012Limited reserves of fossil fuel resources and negative environmental impacts increased energy demands toward renewable energy technologies. Bioenergy is one of the solutions, and biogas production from wastes and residues by anaerobic digestion (AD) is a promising technology. Municipal solid wastes, sludge from wastewater treatment plants, agricultural plant wastes, forestry residues and manure are the widely used sources in AD for biogas production. Aquatic plants can be evaluated as a renewable energy source. If waste and residues of these plants are not utilized in beneficial use, greenhouse gases (GHG) will be emitted through land-filling or direct combustion. Wastes should be converted to biogas with a high yield to decrease the quantity of wastes and biogas with a high-energy content. Substrate to inoculum ratio, temperature regime, C/N ratio, pH, volatile fatty acid and ammonia content are important process parameters for AD. Modified Gompertz, Cone and first-order equations are widely used model equations for kinetic parameters that are used in kinetic models (Monod, modified Andrew, Ratkowsky) for identification of optimum substrate concentration and temperature for each specific feed. This chapter evaluates effective process parameters on AD of aquatic plants for biogas production and application of kinetic analysis for assignment of optimum conditions.Scientific and Technological Research Council ofTurkey (TUBITAK)Turkiye Bilimsel ve Teknolojik Arastirma Kurumu (TUBITAK) [114Y500]; Ministry of Science, Industry and Technology of Turkish Republic [0330.STZ.2013-2]The authors acknowledge the Scientific and Technological Research Council ofTurkey (TUBITAK, Project No: 114Y500) for the financial support. We also thankThe Ministry of Science, Industry and Technology of Turkish Republic supporting our preliminary tests through the grant so-called SAN-TEZ (Project No: 0330.STZ.2013-2). We are grateful to IZSU Ci.gli Advanced BiologicalWastewater Treatment Plant, Izmir for giving us waste sludge for biogas production. We thank to Mr. G. Serin, M.Sc. students M. C. Akbas and B. Kaletas for assistance in laboratory studies. the authors acknowledge publisher "John Wiley and Sons" for permission of reuse of full article Gungoren Madeno.glu et al. [7]