Anaerobic-aerobic processes for the treatment of textile dyeing wastewater containing three commercial reactive azo dyes: Effect of number of stages and bioreactor type

In this study, the effect of number of stages and bioreactor type on the removal performance of a sequential anaerobic-aerobic process employing activated sludge for the treatment of a simulated textile dyeing wastewater containing three commercial reactive azo dyes was considered. Two stage processes performed better than one stage ones, both in terms of overall organic and color removal, as well as the higher contribution of anaerobic stage to the overall removal performance, thereby making them a more energy efficient option. The employment of a moving bed sequencing batch biofilm reactor, which uses both suspended and attached biomass, for the implementation of the anaerobic stage of the process, was compared with a sequencing batch reactor that only employs suspended biomass. The results showed that, although there was no meaningful difference in biomass concentration between the two bioreactors, the latter reactor had better performance in terms of chemical oxygen demand (COD) removal efficiency and rate and color removal rate. Further exploratory tests revealed a difference between the roles of suspended and attached bacterial populations, with the former yielding better color removal whilst the latter had better COD removal performance. The sequential anaerobic-aerobic process, employing an aerobic membrane bioreactor in the aerobic stage resulted in COD and color removal of 77.1±7.9% and 79.9±1.5%, respectively. The incomplete COD and color removal was attributed to the presence of soluble microbial products in the effluent and the autoxidation of dye reduction metabolites, respectively. Also, aerobic partial mineralization of the dye reduction metabolites, was experimentally observed.     

Decision Support System for Monthly Operation of Hydropower Reservoirs: A Case Study

This paper presents a decision support system for multipurpose reservoir operation. The mathematical models in the system are formulated for monthly operation of hydropower reservoirs. The key components of the system are four main modules: database management, inflow modeling and forecasting, operation management, and real-time operation. Flexibility is the key feature of the system, providing the users with different decision tools and different indices for measuring the performance of each tool. A cost function is developed based on the present value of the total capital cost and the cost of operation and maintenance of the system. This cost function, which is developed based on “reasonable” estimates of water and energy prices, is used to measure the performance of reservoir operation policies. A utility function based on multicriterion decision making (MCDM) that uses an analytical hierarchy process is also developed. The MCDM utility function enables decision makers to incorporate the priority of different objectives in developing optimal operating policies and can be effectively used when the priority of objectives is not clear and the decision-making process relies mainly on the decision maker’s preferences. Both economic and MCDM utility functions are implemented and coupled with deterministic and stochastic optimization models. The decision support system (DSS) is applied to the largest surface water resources system in Iran, namely, the Dez and Karoon river-reservoir system. The results of the case study have shown that the DSS has been able to significantly increase the long-term power generation of the system while satisfying water demands for different purposes.     

Potential health risks of arsenic,antimony and mercury in the Takab geothermal field,NW Iran

This study investigates the bioavailability, water–soil to plant transfer and health risks of arsenic (As), antimony (Sb) and mercury (Hg) in the Takab geothermal field north-west of Iran. Water used for irrigation, surface soils from agricultural lands and cultivated plants were collected from three polluted sites and analysed for As, Sb and Hg to assess associated health risks. As content in irrigation water ranges from 23.4 to 986.4?μg/L, whereas total As content in the surface soil is in the range of 16.3–492?mg/kg^?1. The results agree with other reports that metal (loid) concentrations in leaves are usually much higher than in grain. Most investigated plant species showed a significant correlation between As, Sb and Hg contents in their aerial parts and that available in the soil (r?=?0.82, p?=?0.012; r?=?0.84, p?=?0.004; r?=?0.79, p?=?0.011). Factors influencing the bioavailability of metal (loids) and their occurrences in plants are soil pH, cation exchange capacity, phosphate, calcite and organic matter content, soil texture and interaction between target elements. Available As in analysed soils is relatively low, implying that phosphate, as well as Fe-oxy-hydroxides and calcite are effective in absorbing As. But, sequential extraction analysis indicates that iron oxy-hydroxide surface can bind both As and Sb, with As being more strongly bound. The calculated bioaccumulation factor based on total metal (loids) and available metal (loids) in soil indicates that alfalfa (Medicago sativa L.) and sage (Saliva syriaca L.) are effective accumulators of As, Sb and Hg. The health risk index of the studied plants ranged from 0.0003 to 5.71, with the maximum being in wheat (Triticun aestivum L.), an alarming sign for human health. It is suggested that health risks from long-term consumption of wheat and other As-rich foodstuffs must be managed by monitoring contamination in the water–soil–plant pathway.     

Prediction of the Attractive Branch of the Effective Pair Potential Using the Joule–Thomson Inversion Curve

In the present work, the attractive branch of the effective pair potential is predicted by using p–v–T data of the Joule–Thomson inversion curve. It is concluded that all loci of the thermodynamic states of the inversion curve correspond to the attractive branch of the effective pair potential. It is also predicted that the minimum of the effective pair potential well, r _m, is less than that of the isolated pair potential, because the attraction term has a longer range than the repulsion term.     

A New Conducting Polymer with Exceptional Visible-Light Photocatalytic Activity Derived from Barbituric Acid Polycondensation

A novel covalent, metal-free, photocatalytic material is prepared by thermal polymerization of barbituric acid (BA). The structure of the photocatalyst is analyzed by using scanning electron microscopy, X-ray diffraction, and infrared, UV–visible, and ¹H solution and ¹³C solid-state NMR spectroscopy. The photodegradation efficiency of BA thermally polymerized at different temperatures is tested by photocatalytic degradation of aquatic rhodamine B (RhB) dye under visible-light irradiation. It is shown that heating BA at an optimized temperature of 300 °C, that is, still in the range that polymer-like polycondensation takes place, results in a photocatalyst that can remove RhB with 96% photodegradation efficiency after 70 min exposure to visible light. The polycondensation reaction of BA is identified to process through precipitation of trimer units as primary building blocks. Reference experiments such as addition of scavengers and saturation with oxygen are studied to understand the photodegradation process. It is shown that the presence of triethanolamine, and excess of oxygen and p-benzoquinone in the solution of RhB and photocatalyst (BA300) is not beneficial, but decreases the photodegradation efficiency.     

Effect of electrodeposition conditions on the electrochemical capacitive behavior of synthesized manganese oxide electrodes

Galvanostatic electrodeposition techniques were applied for the preparation of novel electroactive manganese oxide electrodes. The effects of supersaturation ratio on the morphology and crystal structure of electrodeposited manganese oxide were studied. Manganese oxide electrodes were synthesized by anodic deposition from acetate-containing aqueous solutions on Au coated Si substrates through the control of nucleation and growth processes. By changing deposition parameters, a series of nanocrystalline manganese oxide electrodes with various morphologies (continuous coatings, rod-like structures, aggregated rods and thin sheets) and an antifluorite-type crystal structure was obtained. Detailed chemical and microstructural characterization of as-deposited electrodes was conducted using SEM, TEM and AAS. Manganese oxide thin sheets show instantaneous nucleation and single crystalline growth, rods have a mix of instantaneous/progressive nucleation and polycrystalline growth and continuous coatings form by progressive nucleation and polycrystalline growth.In addition, the electrochemical behavior was investigated by cyclic voltammetry. The experimental results show that manganese oxide electrodes, with rod-like and thin sheet morphology, exhibited enhanced electrochemical performance. The highest specific capacitance (∼230 F g⁻¹) and capacitance retention rates (∼88%) were obtained for manganese oxide thin sheets after 250 cycles in 0.5 M Na₂SO₄ at 20 mV s⁻¹.     

Carbon Nanotube Field-Effect Transistors for High-Performance Digital Circuits—DC Analysis and Modeling Toward Optimum Transistor Structure

Scaling of silicon technology continues while a research has started in other novel materials for future technology generations beyond year 2015. Carbon nanotubes (CNTs) with their excellent carrier mobility are a promising candidate. The authors investigated different CNT-based field effect transistors (CNFETs) for an optimal switch. Schottky-barrier (SB) CNFETs, MOS CNFETs, and state-of-the-art Si MOSFETs were systematically compared from a circuit/system design perspective. The authors have performed a dc analysis and determined how noise margin and voltage swing vary as a function of tube diameter and power-supply voltage. The dc analysis of single-tube SB CNFET transistors revealed that the optimum CNT diameter for achieving the best I_ON-to-I_OFF ratio while maintaining a good noise margin is about 1 to 1.5 nm. Despite several serious technological barriers and challenges, CNTs show a potential for future high-performance devices as they are being researched     

Stochastic Time-Cost-Resource Utilization Optimization Using Nondominated Sorting Genetic Algorithm and Discrete Fuzzy Sets

In a construction project, the cost and duration of activities could change due to different uncertain variables such as weather, resource availability, etc. Resource leveling and allocation strategies also influence total time and costs of projects. In this paper, two concepts of time-cost trade-off and resource leveling and allocation have been embedded in a stochastic multiobjective optimization model which minimizes the total project time, cost, and resource moments. In the proposed time-cost-resource utilization optimization (TCRO) model, time and cost variables are considered to be fuzzy, to increase the flexibility for decision makers when using the model outputs. Application of fuzzy set theory in this study helps managers/planners to take these uncertainties into account and provide an optimal balance of time, cost, and resource utilization during the project execution. The fuzzy variables are discretized to represent different options for each activity. Nondominated sorting genetic algorithm (NSGA-II) has been used to solve the optimization problem. Results of the TCRO model for two different case studies of construction projects are presented in the paper. Total time and costs of the two case studies in the Pareto front solutions of the TCRO model cover more than 85% of the ranges of total time and costs of solutions of the biobjective time-cost optimization (TCO) model. The results show that adding the resource leveling capability to the previously developed TCO models provides more practical solutions in terms of resource allocation and utilization, which makes this research relevant to both industry practitioners and researchers.     

A novel digital logic implementation approach on nanocrossbar arrays using memristor-based multiplexers

This paper presents and evaluates a novel multiplexer (MUX) composed of memristive devices and nanowire crossbar arrays. The switching behavior of memristors is employed to reveal the desired output state. By applying a sequence of appropriate voltage pulses to the developed MUX, the output is derived and can be transferred through read/write CMOS circuitry. The performance is verified with the SPICE simulator including a threshold-type memristor model. Using the proposed MUXes instead of memristor-based NAND gates, the routing effects that are a major challenge for implementing combinational logic in hybrid circuits can be reduced. Our evaluation results show that both density and delay are effectively improved in pure-MUX-based fabrics.