Impact of an External Magnetic Field on Solitary Waves in Quantum Electron–Hole Plasmas of Semiconductors

Semiconductors - The propagation of solitary acoustic pulses in magnetized quantum electron–hole plasmas of semiconductors has been studied. The effects of an external magnetic field and...     

Waste-to-wealth approach in water economy: The case of beneficiation of mercury-contaminated water in hydrogen production

Heavy metals (Hg, Cd, Pb, etc.) are micro-pollutants and result in water contamination. Significant bio-concentration of heavy metal like Hg can lead to fatal disease such as Minamata. Given this context, heavy metal removal from wastewater is essential before discharge. The wastewater treatment process requires considerable amount of energy which is being met by the conventional carbon-based fuels. This contributes to the global carbon dioxide emission, and hence global warming. Therefore, if clean energy sourcing is enabled during the treatment of the wastewater; it would offer obvious advantages. If the energy production is ‘clean’ and achieved via the process itself, it would serve two outcomes: (a) meeting the energy demand for wastewater treatment, and (b) getting rid of the need for external ‘carbon-based’ energy. Recently a few research articles have reported simultaneous clean energy production from wastewater during its treatment. Thus, the energy demand of the wastewater treatment process can be potentially met with the clean energy produced during the process. In this review, we will discuss mercury-contaminated wastewater treatment with simultaneous hydrogen production. We will provide a brief overview of waste-to-wealth approaches currently prevailing in water economy, recent mercury removal processes, and discuss future possibilities of self-sustained Hg-contaminated wastewater treatment.     

Conditional Preference Networks with User's Genuine Decisions

User's choices involve habitual behavior and genuine decision. Habitual behavior is often expressed using preferences. In a multiattribute case, the Conditional Preference Network (CP-net) is a graphical model to represent user's conditional ceteris paribus (all else being equal) preference statements. Indeed, the CP-net induces a strict partial order over the outcomes. By contrast, we argue that genuine decisions are environmentally influenced and introduce the notion of “comfort” to represent this type of choices. In this article, we propose an extension of the CP-net model that we call the CP-net with Comfort (CPC-net) to represent a user's comfort with preferences. Given that preference and comfort might be two conflicting objectives, we define the Pareto optimality of outcomes when achieving outcome optimization with respect to a given CPC-net. Then, we propose a backtrack search algorithm to find the Pareto optimal outcomes. On the other hand, two outcomes can stand in one of six possible relations with respect to a CPC-net. The exact relation can be obtained by performing dominance testing in the corresponding CP-net and comparing the numeric comforts.     

Overlapping community detection using core label propagation algorithm and belonging functions

Applied Intelligence - The community detection in complex networks has become a major field of research. Disjoint community detection deals often with getting a partition of nodes where every node...     

Thermal Decomposition Study on CuInSe$$_{}$$ Single Crystals

The thermal analysis of the chemical vapor transport (CVT)-grown \(\hbox {CuInSe}_{2}\) single crystals was carried out by recording the thermogravimetric, differential thermogravimetric and differential thermal analysis curves. All the three thermo-curves were recorded simultaneously by thermal analyzer in the temperature range of ambient to 1080 K in inert nitrogen atmosphere. The thermo-curves were recorded for four heating rates of 5 K \(\cdot \,\hbox {min}^{-1}\), 10 K \(\cdot \,\hbox {min}^{-1}\), 15 K \(\cdot \,\hbox {min}^{-1}\) and 20 K \(\cdot \,\hbox {min}^{-1}\). The TG curve analysis showed negligible mass loss in the temperature range of ambient to 600 K, stating the sample material to be thermally stable in this temperature range. Above 601 K to the temperature of 1080 K, the sample showed continuous mass loss. The DTG curves showed two peaks in the temperature range of 601 K to 1080 K. The corresponding DTA showed initial minor exothermic nature followed by endothermic nature up to nearly 750 K and above it showed exothermic nature. The initial exothermic nature is due to absorbed water converting to water vapor, whereas the endothermic nature states the absorption of heat by the sample up to nearly 950 K. Above nearly 950 K the exothermic nature is due to the decomposition of sample material. The absorption of heat in the endothermic region is substantiated by corresponding weight loss in TG. The thermal kinetic parameters of the CVT-grown \(\hbox {CuInSe}_{2}\) single crystals were determined employing the non-mechanistic Kissinger relation. The determined kinetic parameters support the observations of the thermo-curves.     

Oligomeric Composition of Polyols From Fatty Acid Methyl Ester: The Effect of Ring‐Opening Reactants of Epoxide Groups

Commercial availability of fatty acid methyl ester (FAME) from palm oil targeted for biodiesel offers a good feedstock for the production of structurally well‐defined polyols for polyurethane applications. The effect of molecular weight (MW), odd and even carbon numbers, and the linear and branched structure reactants used in the ring‐opening reaction of epoxidized fatty acid methyl ester (E‐FAME) on the properties of polyols was investigated. Conversions of E‐FAME to PolyFAME polyols were confirmed by Fourier transform infrared analysis, oxirane oxygen content, and hydroxyl number. Gel permeation chromatography (GPC) calibrated against polyether polyols as a standard and vapor pressure osmometry were used for MW determination. GPC chromatograms of PolyFAME polyols clearly demonstrated the formation of oligomers during ring‐opening reactions. MW, and odd and even carbon numbers in a structure of linear diols and branched diol used in the syntheses of PolyFAME polyols did not have an effect on crystallinity, glass transition, or melt temperatures measured using Differential scanning calorimetry (DSC). PolyFAME polyols ring‐opened with water, methanol, and 1,2‐propanediol contained secondary hydroxyl groups, whereas PolyFAME polyols ring‐opened with linear diols contained a mixture of primary and secondary hydroxyl groups. It was found that the concentration of primary hydroxyl groups increased significantly by increasing the number of carbons from C2 to C3 in the linear diols. The viscosity of PolyFAME polyols also increased with the MW of linear diols used in the E‐FAME ring‐opening reaction. These findings would be beneficial for formulators in choosing the most cost effective polyols for polyurethane formulations.     

A Numerical and Experimental Investigation into Hot Stamping of Boron Alloyed Heat Treated Steels

Hot stamping of steel sheets using water or nitrogen cooling media was studied on a laboratory scale. Sheets of grade 22MnB5 boron steels in three different thicknesses were investigated and the results of experimental hot stamping tests were considered. Microstructural analysis, linear and surface hardness profiling as well as tensile tests of formed samples were carried out. After hot stamping, mostly fully martensitic microstructures, which yield ultra high strength levels, were produced. It is concluded that die cooling media, i.e., water or nitrogen, have a significant effect on material properties after hot stamping. Using liquid nitrogen as coolant in the punch instead of water increases yield strength by 50 to 65MPa. Moreover, the evolution of the temperature and force during the hot stamping process was simulated by using a coupled thermomechanical FEM program. The results of numerical simulation and experimental results are in good agreement.     

Sensitivity Analysis on Neural Network Algorithm for Primary Superheater Spray Modeling

ABSTRACT

Nonlinear, large inertia with long dead time is always associated with the main steam temperature parameter in coal fired power plant. Successful control of the main steam temperature within ±2°C of its setpoint is the ultimate target for coal-fired power plant operators. Two of the most common main steam temperature circuit are primary superheater spray and secondary superheater spray. Various methods were used to model the primary superheater spray control valve opening, and the neural network remains one of the most popular choices among researchers. It remains inconclusive which neural network algorithm types, setup, number of layers, and training algorithm will give the best result. As such, the paper shows the best setup for the neural network algorithm based on sensitivity analysis methodology for one hidden layer. The inputs selected for the neural network are generator output, main steam flow, total spray flow, and secondary superheater outlet steam temperature, while the output selected is primary spray flow control valve opening.