Effect of Silicone Nano,Nano/Micro and Nano/Macro‐Emulsion Softeners on Color Yield and Physical Characteristics of Dyed Cotton Fabric

The study of silicone nano‐emulsions and softeners to alter physical properties of undyed cotton fabric has recently gained a substantial interest. However, systematic investigation of silicon nano‐emulsion softeners on dyed cotton fabric has not so far been conducted. This paper deals with the application of silicone nano‐, micro‐, and macro‐emulsion softeners, and combinations of nano/micro and nano/macro, on dyed cotton fabric. We report the effect of silicon nano/micro‐ and nano/macro‐emulsion softeners on color yield and physical characteristics of dyed cotton fabric. All bleached fabrics were dyed with CI Reactive Black 5 and then treated with known concentrations of silicone softeners by the pad‐dry method. The silicone nano‐emulsion was combined with micro‐ and macro‐emulsion softeners using blending ratios of nano/micro (1:1) and nano/macro (1:1). Treated fabrics were compared in terms of physical properties such as fabric handling, wrinkle recovery angle, bending length, abrasion resistance and tensile strength. The color changes were evaluated by color yield (K/S) values and total color difference (ΔE_cmc). The results revealed that the silicon nano‐emulsion had better physical properties than micro‐, macro‐ and combination nano/micro‐ and nano/macro‐emulsion softeners. Among all treated samples, nano‐emulsion softeners showed better ΔE_cmc values. Scanning electron microscopy analysis suggests that the fiber morphology of treated fabrics was very smooth and uniform.     

Magnetization Process of the Spin-1/2 Two-Leg Ladder Compound (C5H12N)2 CuBr4: The Jordan-Wigner Approach

We have studied the magnetization process in the spin S = 1/2 antiferromagnetic two-leg ladder compound (C₅H₁₂N)₂ CuBr₄ by using the analytical fermionization technique. The magnetization and the susceptibility are calculated as functions of the temperature and the external magnetic field. The magnetization of the system shows various behaviors in different regions of the magnetic field. The field-dependence of the susceptibility is almost symmetric about the average of quantum critical fields in the low-temperature region leading to a complete agreement with the experimental results.     

Effect of Particle Size on Direct Compaction of Urea Fertilizer

The effect of particle size on compaction properties and characteristics of urea tablets manufactured from available urea granules (TG tablets) and ground urea powders (TP tablets) was investigated. The compaction properties, namely, plastic work, elastic work, friction work, and maximum ejection pressure were analyzed from the force-displacement profile of the compaction process. Five applied pressures ranging between 37.67 MPa and 188.35 MPa were used to compact the materials using a universal testing machine. Characteristics of the tablets tested were mechanical strength and the release of ammonium ion through dissolution test. The results demonstrated that TG tablets underwent high plastic work and elastic work but low friction work compared to the TP tablets. TG tablets released lower amount of ammonium ion compared to the TP tablets at almost all applied pressures, except at 75.34 MPa. This study provides a valuable data for evaluating the behavior of urea in the form of granules and powders during the compaction process as well as the suitability in choosing the form of raw material for the production of urea tablets.     

Kinetic studies for Ni(II) biosorption from industrial wastewater by Cassia fistula (Golden Shower) biomass

The present study explores the ability of Cassia fistula waste biomass to remove Ni(II) from industrial effluents. C. fistula biomass was found very effective for Ni(II) removal from wastewater of Ghee Industry (GI), Nickel Chrome Plating Industry (Ni-Cr PI), Battery Manufacturing Industry (BMI), Tanner Industry: Lower Heat Unit (TILHU), Tannery Industry: Higher Heat Unit (TIHHU), Textile Industry: Dying Unit (TIDU) and Textile Industry: Finishing Unit (TIFU). The initial Ni(II) concentration in industrial effluents was found to be 34.89+/-0.01, 183.56+/-0.08, 21.19+/-0.01, 43.29+/-0.03, 47.26+/-0.02, 31.38+/-0.01 and 31.09+/-0.01mg/L in GI, Ni-Cr PI, BMI, TILHU, TIHHU, TIDU and TIFU, respectively. After biosorption the final Ni(II) concentration in industrial effluents was found to be 0.05+/-0.01, 17.26+/-0.08, 0.03+/-0.01, 0.05+/-0.01, 0.1+/-0.01, 0.07+/-0.01 and 0.06+/-0.01mg/L in GI, Ni-Cr PI, BMI, TILHU, TIHHU, TIDU and TIFU, respectively. The % sorption Ni(II) ability of C. fistula from seven industries included in present study tend to be in following order: TILHU (99.88)>GI (99.85) approximately BMI (99.85)>TIFU (99.80)>TIHHU (99.78)>TIDU (99.77)>Ni-Cr PI (90.59). Sorption kinetic experiments were performed in order to investigate proper sorption time for Ni(II) removal from wastewater. Batch metal ion uptake capacity experiments indicated that sorption equilibrium reached much faster in case of industrial wastewater samples (480min) in comparison to synthetic wastewater (1440min) using same biosorbent. The kinetic data were analyzed in term of pseudo-first-order and pseudo-second-order expressions. Pseudo-second-order model described well the sorption kinetics of Ni(II) onto C. fistula biomass from industrial effluents in comparison to pseudo-first-order kinetic model. Due to unique high Ni(II) sorption capacity of C. fistula waste biomass it can be concluded that it is an excellent biosorbent for Ni(II) uptake from industrial effluents.     

Ni(II) biosorption by Cassia fistula (Golden Shower) biomass

Cassia fistula is a fast-growing, medium-sized, deciduous tree which is now widely cultivated worldwide as an ornamental tree for its beautiful showy yellow flowers. Methods are required to reuse fallen leaves, branches, stem bark and pods when they start getting all over lawn. This investigation studies the use of these non-useful parts of C. fistula as naturally occurring biosorbent for the batch removal of Ni(II) in a well stirred system under different experimental conditions. The data showed that the maximum pH (pHmax) for efficient sorption of Ni(II) was 6 at which evaluated biosorbent dosage, biosorbent particle size, initial concentrations of Ni(II) and sorption time were 0.1 g/100 mL, <0.255 mm, up to 200 mg/L and 720 min, respectively. The experimental results were analyzed in terms of Langmuir and Freundlich isotherms. The Langmuir isotherm model fitted well to data of Ni(II) biosorption by C. fistula biomass as compared to the model of Freundlich. The kinetic studies showed that the sorption rates could be described better by a second order expression than by a more commonly applied Lagergren equation. The magnitude of the Gibbs free energy values indicates spontaneous nature of the sorption process. The sorption ability of C. fistula biomass for Ni(II) removal tends to be in the order: leaves相似文献   

Multi-objective optimal design of online PID controllers using model predictive control based on the group method of data handling-type neural networks

In this paper, model predictive control (MPC) is used for optimal selection of proportional-integral-derivative (PID) controller gains. In conventional tuning methods a history of response error of the system under control in the passed time is measured and used to adjust PID parameters in order to improve the performance of the system in proceeding time. But MPC obviates this characteristic of classic PID. In fact MPC tries to tune the controller by predicting the system's behaviour some time steps ahead. In this way, PID parameters are adjusted before any real error occurs in the system's response. For this purpose, polynomial meta-models based on the evolved group method of data handling neural networks are obtained to simply simulate the time response of the dynamic system. Moreover, a non-dominated sorting genetic algorithm has been used in a multi-objective Pareto optimisation to select the parameters of the MPC which are prediction horizon, control horizon and relation of weight of Δ u and error, to minimise simultaneously two objective functions that are control effort and integral time absolute error of the system response. The results mentioned at the end obviously declare that the proposed method surpasses conventional tuning methods for PID controllers, and Pareto optimal selection of predictive parameters also improves the performance of the introduced method.