Efficient PL Emission from p-type Porous Silicon: A Comparative Study for Selection of Effective Anodization Parameters

The physical mechanism of highly efficient photoluminescence (PL) emission from p-type silicon is described by a comparative study of the effectiveness of the etching parameters in an electrochemical anodization technique. Two series of porous silicon samples were prepared in a combination of anodization current and time, to maintain the total amount of anodic charge transfer constant. Photoluminescence studies show that irrespective of the amount of charge transfer, the samples prepared with comparatively higher current density show an efficient PL as well as stronger blueshift in the emission energy vis-à-vis the samples prepared for longer durations. An overall decrease in crystallite size, as estimated by Raman spectral analysis, was observed for both series of samples with the progress of charge transfer. Comparative analysis shows a marginal difference in crystallite size for both series of samples in the initial state of charge transfer, whereas major differences arise at higher values. This is explained with the formation of silicon suboxide on the porous surface at higher current density, leading to initiation of side wall reaction, and higher reduction rate in crystallite size as well as strong luminescence due to the carrier quantum confinement effect.     

Influence of Si-Doping on the Performance of InGaN/GaN Multiple Quantum Well Solar Cells

Semiconductors - The performance of InGaN/GaN multiple quantum well (MQW) solar cells with five different Si-doping concentrations, namely 0, 4 × 1017 cm–3, 1 × 1018 cm–3, 3...     

Matrix Transformation in Boron Containing High-Temperature Co–Re–Cr Alloys

An addition of boron largely increases the ductility in polycrystalline high-temperature Co–Re alloys. Therefore, the effect of boron on the alloy structural characteristics is of high importance for the stability of the matrix at operational temperatures. Volume fractions of ε (hexagonal close-packed—hcp), γ (face-centered cubic—fcc) and σ (Cr₂Re₃ type) phases were measured at ambient and high temperatures (up to 1500 °C) for a boron-containing Co–17Re–23Cr alloy using neutron diffraction. The matrix phase undergoes an allotropic transformation from ε to γ structure at high temperatures, similar to pure cobalt and to the previously investigated, more complex Co–17Re–23Cr–1.2Ta–2.6C alloy. It was determined in this study that the transformation temperature depends on the boron content (0–1000 wt. ppm). Nevertheless, the transformation temperature did not change monotonically with the increase in the boron content but reached a minimum at approximately 200 ppm of boron. A probable reason is the interplay between the amount of boron in the matrix and the amount of σ phase, which binds hcp-stabilizing elements (Cr and Re). Moreover, borides were identified in alloys with high boron content.     

Imaging of two-dimensional unsaturated moisture flows in uncracked and cracked cement-based materials using electrical capacitance tomography

The development of visualizing tools to monitor unsaturated moisture flow in cement-based materials is of great importance, as most degradation processes in cement-based materials are connected to and take place in the presence moisture. This paper investigates the ability of electrical capacitance tomography (ECT) to image two-dimensional (2D) unsaturated moisture flow in cement-based materials. In ECT, the electrical permittivity distribution within an object is reconstructed based on measured capacitances between electrodes attached on the object’s surface. In a series of experiments, mortar specimens with and without discrete cracks were imaged with ECT during a 2D moisture ingress. The results show that ECT is able to monitor the evolution of the moisture flow, and to approximate the shape and position of the moisture front. These findings indicate that ECT is a viable method for monitoring and visualizing 2D unsaturated moisture flow in cement-based materials in the presence and absence of discrete cracks.     

Appraisal of Agriglass in Promoting Maize Production Under Abiotic Stress Conditions

An agriglass composition containing different oxides acts as a slow release for macro and micro nutrients and was chosen to improve maize yield under most important abiotic stresses which affecting agriculture development; salinity and drought. A field experiment was performed in salt affected soil (EC =?7.5 dSm^??1) by using different water deficit rates (I1 = 100, I2 = 85 and I3 = 70% of maize water requirements). Irrigation levels were located in main plots. Every main-plot divided into six sub-plots contained glassy fertilizer treatments [F1 = 55 kg fed^?1 with 1/2 mm diameter of agriglass (fed. =?4200 m²), F2 = 55 kg fed^?1 with 1 mm diameter, F3 = 80 kg fed^?1 with 1/2 mm diameter, F4 = 80 kg fed^?1 with 1 mm diameter, F5 = Recommendations of Ministry of Agriculture and F6 = control]. The experimental results demonstrated that, ears, straw, grains and biological yields increased with increasing both water and agriglass rates. Application of agriglass as a slow release fertilizer improved yield more than mineral fertilizer. Some growth parameters, water use efficiency (IWUE), macronutrients concentration and their relations were included. Other studies on residual effect of agriglass and the annual application rates to withstand salinity and drought stress by strategic crops are required.     

Effect of ZnO layer thickness upon optoelectrical properties of NiO/ ZnO heterojunction prepared at room temperature

In this work, p-NiO/n-ZnO heterostructures were successfully prepared at room temperature using RF sputtering technique. The influence of ZnO layer thickness on the performance of the heterojunction was investigated. The deposited ZnO layers have a hexagonal Wurtzite structure with preferable growth orientations along (002) and (103) for thinner films. Increasing the thickness results in more crystallographic orientation randomness. The current–voltage measurements of the realized heterojunctions showed a clear rectifying behavior. The measured ideality factor varies from 2.5 to 1.6 according to the thickness of ZnO layer. The series resistance of the device is enlarged with increasing ZnO thickness. The deduced parameters from the I–V characteristics suggest that 200 nm is the optimal thickness of the ZnO layer according to our experimental conditions. We attribute the relatively better performance of this thickness to achieving reasonable compensation between serial resistance and ideality factor. The best heterojunction was tested and successfully used as a UV detector.     

Cross-Layer Optimization of Dynamic Packet Assignment for Video Transmission Over IEEE 802.11e Networks

Video transmission over IEEE 802.11e wireless networks still shows poor performance for large bandwidth demand and frequently changed environments. Thus, several enhancements of IEEE 802.11e were proposed. On the other hand, big frames and simultaneous sending of adjacent frames always cause packet dropping for buffer overflow. In the past, we proposed an IEEE 802.11e enhancement named DFAA and a content aware mechanism to solve the above problems. The motivation of this paper is to find a proper way to integrate these two mechanisms. A DFAA enhancement (DFAA-E) is proposed to make up the insufficiency of content aware mechanism. Experiments results show that the combination of DFAA-E and content aware mechanism improves the video decoded quality greatly. And its performance can be further enhanced by selecting the suitable settings of certain parameters.     

Automatic breast tumor detection in ABVS images based on convolutional neural network and superpixel patterns

Breast cancer is one of the most common female malignancies, as well as the second leading cause of mortality for women. Early detection and treatment can dramatically decrease the mortality rate. Recently, automated breast volume scanner (ABVS) has become one of the most frequently used diagnose methods for breast tumor screening because of its operator-independent and reproducible advantages. However, it is a challenging job to obtain the tumors’ accurate locations and shapes by reviewing hundreds of ABVS slices. In this paper, a novel computer-aided detection (CADe) system is developed to reduce clinicians’ reading time and improve the efficiency. The CADe system mainly contains three parts: tumor candidate acquisition, false-positive reduction and tumor segmentation. Firstly, a local phase-based approach is built to obtain breast tumor candidates for further recognition. Subsequently, a convolutional neural network (CNN) is applied to reduce false positives (FPs). The introduction of CNN can help to avoid complicated feature extraction as well as elevate the accuracy and efficiency. Finally, superpixel-based segmentation is used to outline the breast tumor. Here, superpixel-based local binary pattern (SLBP) is proposed to assist the segmentation, which improves the performance. The methods were evaluated on a clinical ABVS dataset whose abnormal cases were manually labeled by an experienced radiologist. The experiment results were mainly composed of two parts. At the FP reduction stage, the proposed CNN achieved 100% and 78.12% sensitivity with FPs/case of 2.16 and 0. At the segmentation stage, our SLBP obtained 82.34% true positive, 15.79% false positive and 83.59% Dice similarity. In summary, the proposed CADe system demonstrated promising potential to detect and outline breast tumors in ABVS images.