Microwave drying of CuCl residue from hydrometallurgical zinc recovery process

CuCl residue is a hazardous waste from the hydrometallurgical zinc recovery plant. It is very difficult to recycle due to complicated composition, highly corrosive nature, and refractory characteristics. Recently, a new process of microwave drying and roasting was successfully developed to produce both CuO solid and HCl gas products from the CuCl residue. In this paper, the dielectric property of the CuCl residue was measured under different moisture contents. The microwave absorption characteristics of the CuCl residue improved considerably as its moisture content increased. Laboratory-scale drying tests were conducted to evaluate the kinetics of microwave drying and to optimize the operation parameters. The efficiency of microwave drying was further demonstrated in industrial-scale level by microwave dryer developed in in-house. Finally, the drying mechanism of microwave heating of the sticky material was discussed and several measurements were optimized/implemented to intensify the drying process.     

Energy Efficient Clustering Algorithm Using RFD Based Multi-hop Communication in Wireless Sensor Networks

In recent years, researchers have focused on many challenging aspects in the area of Wireless Sensor networks (WSNs). Development of energy efficient data collection protocols became the major concern in WSN. Clustering is one of the suitable techniques for energy efficiency. However, in clustering, the cluster are formed with uneven size. This unbalances the energy consumption among clusters which in turn reduce the lifetime of the network. In this paper, in order to balance the energy among clusters, a multi-hop concept is introduced for both intra and inter cluster communication. Firstly, the RFDMRP: River Formation Dynamics based Multi-hop Routing Protocol has been proposed. Later, this protocol is integrated with clustering and a new hybrid technique, named as hybrid clustering communication algorithm using RFDMRP (HCCRFD) is introduced. HCCRFD improves energy conservation by reducing overall packet transmission distance of intra and inter cluster communication, which results in increased network lifetime. Energy consumption of proposed algorithm has been analyzed mathematically. Also, the algorithms were simulated using MATLAB and outputs observed. The observed outputs were compared with existing protocols such as LEACH, DEEC, ERA, and \(ACH^2\) in three different scenarios namely homogenous, heterogeneous environment, and node density. The comparison reveals that the proposed algorithm perform better than the existing protocols with respect to energy conservation and network lifetime.     

Effect of Homogenization Process on Microstructure of Al–Zn–Mg–Cu Aluminum Alloys

Herein, the best homogenization process of 466.5 °C × 36 h + 490 °C × (14–26.4 h) that can completely eliminate the coarse phases σ[Mg(Zn, Al, Cu)₂] and S(Al₂CuMg) in the Al–Zn–Mg–Cu aluminum alloy is developed. The homogenization process is determined by the method of calculation phase diagram, and the experimental verification. It is shown in the results that, first, in the microstructure of the as-cast alloys, the crystal structure of the σ[Mg(Zn, Al, Cu)₂], Al₇Cu₂Fe, and Mg₂Si phases is determined. Second, during the homogenization process, the σ[Mg(Zn, Al, Cu)₂] phase dissolves and also transforms into the S(Al₂CuMg) phase. Most importantly, the dissolution temperature range of the σ[Mg(Zn, Al, Cu)₂], S(Al₂CuMg), and Al₇Cu₂Fe phases is determined from 472.56 to 476.36 °C, from 484.09 to 485.39 °C, and from 540.18 to 547.23 °C, respectively. At best homogenization process, the residual Al₇Cu₂Fe phase area fraction ranges from 1.28 ± 0.16% to 1.60 ± 0.18%. In addition, dispersed η(MgZn₂) phase precipitates in supersaturated Al-matrix during differential scanning calorimeter heating. And, the concentration differences between the grain center and the eutectic of structure of Zn, Mg and Cu regression equations are established, which can provide some reference for the design of experimental parameters, thus reducing the experimental workload.     

HR-DO: High reliable–delay optimized controller placement in software-defined networking

Currently, networking technologies are pivoting towards software-defined networking (SDN) due to its easy management and centralized control system. The SDN network metrics, such as latency, scalability, robustness, and reliability largely depends on controller placement in the network domain. In view of betterment and best progression of network quality, the above mentioned network metrics need to be laid more emphases by considering controller placement. To achieve better network quality, an HR-DO (high reliable–delay optimized controller placement) is proposed. Fuzzy C-means, a meta-heuristic optimization algorithm, is used to optimize the number of controllers required in the network due to its effectiveness in cluster selection. It also eases the network latency. In addition, a minimal cut set-based Boolean logic approach and natural connectivity metric are used to improve the reliability and robustness of SDN with minimum worst-case latency. To check the performance, the proposed HR-DO is implemented on a topology-zoo network data set (OS3E and Chinanet). For comparison purposes, OCPA and K-means algorithms are taken into the account of latency, reliability, and robustness as parameters. The performance of the HR-DO approach outperforms over K-means and OCPA with respect to latency, reliability, and robustness.     

Extraction of gold and silver in the selective chlorination roasting process of cyanidation tailing

The selective chlorination of cyanidation tailing (CT) for the extraction of gold and silver has been investigated. The reaction operated at different conditions and their effect on the extraction of Au and Ag was studied. The mineral samples were characterized by fire assay, X-ray diffraction (XRD), X-ray fluorescence (XRF) and scanning electronic microscopy (SEM). The best recovery values were 95.32% of Au and 85.32% of Ag at 1373 K and 1.5 h with 5% KCl. The results show that gold chlorination reaction was controlled by the interfacial chemical reaction, and the apparent activation energy was 40.05 kJ/mol. Silver has an activation energy of about 8.97 kJ/mol, and silver removal is performed by diffusion control.     

Correction to: CS-CGMP: Clustering Scheme Using Canada Geese Migration Principle for Routing in Wireless Sensor Networks

Wireless Personal Communications - There was a mix-up of Figs. 5-8 in the initial, online publication.     

Glowing Combustion Synthesis,Characterization, and Toxicity Studies of Na2CaSiO4 Powders

Here, we are reporting the glowing combustion synthesis of Na₂CaSiO₄ powders for the first time at low temperature. L-alanine was used as reductant, and nitrates of sodium and calcium were used as oxidants. Phase evolution and formation was studied using X-ray diffraction (XRD), Fourier transform infrared (FTIR), Thermo gravimetric analysis-Differential thermal analysis (TGA–DTA) techniques. Powder morphology and particle size distribution were characterized using scanning electron microscopy (SEM), dynamic light scattering (DLS) techniques. Results confirms the formation of single phasic, microcrystalline sodium calcium silicate (Na₂CaSiO₄ phase) in cubic crystal system. Evaluation of hemolysis and (3-(4,5-Dimethylthiazol-2-yl)-2,5-Diphenyltetrazolium Bromide) (MTT) tests suggest that Na₂CaSiO₄ powders exhibit negative response in in vitro conditions.     

DR-NAP: Data reduction strategy using neural adaptation phenomenon in wireless sensor networks

Internet of Things (IoT) has got significant popularity among the researchers' community as they have been applied in numerous application domains. Most of the IoT applications are implemented with the help of wireless sensor networks (WSNs). These WSNs use different sensor nodes with a limited battery power supply. Hence, the energy of the sensor node is considered as one of the primary constraints of WSN. Besides, data communication in WSN dissipates more energy than processing the data. In most WSNs applications, the sensed data generated from the same location sensor nodes are identical or time-series/periodical data. This redundant data transmission leads to more energy consumption. To reduce the energy consumption, a data reduction strategy using neural adaptation phenomenon (DR-NAP) has been proposed to decrease the communication energy in routing data to the BS in WSN. The neural adaptation phenomenon has been utilized for designing a simple data reduction scheme to decrease the amount of data transmitted. In this way, the sensor node energy is saved and the lifetime of the network is enhanced. The proposed approach has been implanted in the existing gravitational search algorithm (GSA)-based clustered routing for WSN. The sensed data are transmitted to CH and BS using DR-NAP. Real sensor data from the Intel Berkeley Research lab have been used for conducting the experiments. The experiment results show 47.82% and 51.96% of improvement in network lifetime when compared with GSA-based clustered routing and clustering scheme using Canada Geese Migration Principle (CS-CGMP) for routing, respectively.