Simulating the impact of kraft pulping and bleaching parameters on Eucalyptus camaldulensis pulp properties using MATLAB

In this work, Eucalyptus camaldulensis was evaluated as the raw material for chemical pulp under different pulping and bleaching conditions. The pulping was carried out at different H‐factors, and at different effective alkalis. The resulting pulps were then oxygen delignified and bleached using various dosages of bleaching chemicals in a D₀EpD₁ sequence. The effect of independent variables (pulping or bleaching variables) on dependent variables (pulp properties) was analysed based on the multivariable least square method via MATLAB software. An agreement was found between the results predicted from the models and the experimental data. To obtain a kappa number of 15, the optimum pulping conditions were a temperature of 155°C, a time of 225 min, and an EA of 23%. Also, the hexenuronic acid (HexA) content of cooked pulp was significantly decreased in the chlorine dioxide bleaching stages, and was only marginally related to the final HexA content of bleached pulps.     

Amino acid bound surfactants: a new synthetic family of polymeric monoliths opening up possibilities for chiral separations in capillary electrochromatography

By combining a novel chiral amino-acid surfactant containing an acryloyl amide tail, a carbamate linker, and a leucine headgroup of different chain lengths with a conventional cross-linker and a polymerization technique, a new "one-pot" synthesis for the generation of amino-acid based polymeric monolith is realized. The method promises to open up the discovery of an amino-acid based polymeric monolith for chiral separations in capillary electrochromatography (CEC). The possibility of enhanced chemoselectivity for simultaneous separation of ephedrine and pseudoephedrine containing multiple chiral centers and the potential use of this amino-acid surfactant bound column for CEC and CEC coupled to mass spectrometric detection are demonstrated.     

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.     

Prediction of position error signal of a hard disk drive undergoing a long seek

To expedite design cycles and to evaluate performance of designed hard disk drives, mathematical models to predict position error signal (PES) are needed. Existing mathematical model can successfully predict PES during track following. However, there is no computational efficiency approach to predict PES after a long seek presently. In this paper, we presents a feasible mathematical model to achieve this purpose. Detail mathematical derivations and numerical simulations are also included in this paper. Our mathematical models are capable to obtain reasonable qualitative predications after a long seek.     

THERMODYNAMICS OF MOISTURE SORPTION IN ALFALFA PELLETS

Experimental data on sorption isotherms of alfalfa pellets were used to determine the thermodynamic functions (differential heat of sorption, spreading pressure, net integral enthalpy and entropy) of the pellets. The thermodynamic functions were then utilized in modeling the specific heats of pellets as a function of moisture content. The estimated values of the thermodynamic functions at different moisture contents confirmed the results of an earlier study on the influence of moisture sorption on the physical integrity of the pellets. The changes in the thermodynamic properties and physical integrity were prominent when the moisture of the pellets were between 0.10 and 0.12 (mass fraction basis). Using the differential heat of sorption, it was determined that alfalfa pellets have higher affinity for moisture uptake when compared to wheat and lentils. The specific heat of the solids of alfalfa pellets had a parabolic relationship with moisture whereas the specific heat of water fraction increased linearly with moisture content of the pellets.     

An Approach for Probabilistic Hydrological Drought Forecasting

This paper proposes an approach to monitor and forecast hydrological drought in a probabilistic manner. The proposed approach deals with the supply and demand variables and the role of carryover in a system to estimate the probability of drought severity at different hydroclimatlogical conditions as well as different storage volume levels. This approach might be of significance when the supply and demand variables of a water resources system change considerably by climate variation. Major probability values and their mutual use in the proposed drought forecasting method are discussed. The presented approach is applied for the hydrological drought forecasting of Zayandeh-rud river basin in Iran. This probabilistic view of drought monitoring and forecasting is useful for risk-based decisions in water resources planning and management. The proposed index could be used to overcome the lack thereof in the existing surface water supply index.     

Fabrication of asymmetric polyethersulfone membranes for separation of carbon dioxide from methane using polyetherimide as polymeric additive

Polyetherimide (PEI) was used as a polymeric additive for preparing an asymmetric polyethersulfone (PES) membrane for the separation of CO₂ from CH₄. In pure gas experiments, the higher skin layer thickness and the lower porosity of the sub layer for the membrane prepared from the polymer blend with the composition of 98:2 lead to an increase in CO₂/CH₄ selectivity and a decrease in the CO₂ permeance in contrast with a pristine PES. For higher PEI contents, the higher fractional free volume of the membranes improves the gas permeance and reduces the CO₂/CH₄ selectivity. The incorporation of PEI in PES reduces the CO₂ sorption in PES via decreasing the non-equilibrium free volume and imparts antiplasticization properties to the membrane.     

Developing a new method for spatial assessment of drought vulnerability (case study: Zayandeh‐Rood river basin in Iran)

The paper presents an approach to spatially representative depiction for assessing the vulnerability of central Iran's Zayandeh‐Rood river basin to drought using multiple indicators. Drought conditions prevailed in the study basin from 2002 to 2007, with an annual rainfall deficiency of 45 to 55%. Multi‐attribute decision making (MADM) methods develop a framework to evaluate the relative priorities of drought assessment based on a set of preferences, criteria and indicators. The proposed MADM process uses well‐known techniques for product weights analytic hierarchy process (AHP) and order preference (TOPSIS). These indicators include the Standard Precipitation Index (SPI), water demand, the Palmer Drought Severity Index (PDSI) and the Groundwater Balance and Surface Water Supply Index (SWSI). Indicators' spatial information was categorised in layers prepared in the spatial domain using a geographic information system (GIS). The alternatives were ranked and presented using TOPSIS. Results show that the proposed method was highly effective in representing assessments of drought vulnerability.     

Maximum SiO2 layer thickness by utilizing polyethylene glycol as the surfactant in synthesis of core/shell structured TiO2–SiO2 nano-composites

TiO₂–SiO₂ nano-composites with the core/shell structure have been prepared by means of a technique based on an extension of well-known Stöber process. In this way, the silica coating of TiO₂ nano-particles in the presence of various commercially available surfactants of cationic, anionic and nonionic has been conducted with the aim to increase barrier properties against UV (UV blocking) radiation, in order to optimize photo-killing ability of the TiO₂ nano-particles and decline of the high photo-catalytic property of titania. The influences of varying coating parameters such as time and temperature on the silica content of nano-composites have been studied and optimum conditions for attaining a thick layer of SiO₂ have been determined. Electro-phoretic mobility measurements indicated that the silica coating shifted the iso-electric point of titania toward that of a typical pure colloidal silica. Surface elemental composition of core/shell structured TiO₂–SiO₂ nano-composites was verified by using energy dispersive X-ray analysis. It was found that maximum silica shell thickness can be obtained in the presence of polyethylene glycol as a nonionic surfactant at 80 °C for 360 min. The photo-catalytic activities were evaluated by the degradation of an aqueous solution of methylene blue under UV light irradiation. In addition, the resultant optimum nano-composites have been characterized by FESEM, TEM, BET, FTIR and UV–Vis spectroscopy.     

Nanocrystal Skins with Exciton Funneling for Photosensing

Highly photosensitive nanocrystal (NC) skins based on exciton funneling are proposed and demonstrated using a graded bandgap profile across which no external bias is applied in operation for light‐sensing. Four types of gradient NC skin devices (GNS) made of NC monolayers of distinct sizes with photovoltage readout are fabricated and comparatively studied. In all structures, polyelectrolyte polymers separating CdTe NC monolayers set the interparticle distances between the monolayers of ligand‐free NCs to <1 nm. In this photosensitive GNS platform, excitons funnel along the gradually decreasing bandgap gradient of cascaded NC monolayers, and are finally captured by the NC monolayer with the smallest bandgap interfacing the metal electrode. Time‐resolved measurements of the cascaded NC skins are conducted at the donor and acceptor wavelengths, and the exciton transfer process is confirmed in these active structures. These findings are expected to enable large‐area GNS‐based photosensing with highly efficient full‐spectrum conversion.