Recent Innovations in Chemical Engineering (Formerly Recent Patents on Chemical Engineering) - Volume 12, Issue 2, 2019

Background and Objective: This study utilizes Rhodobacter sphaeroides bacteria for the photoproduction of hydrogen under various cultural conditions. R. sphaeroides was isolated from sewage water. We have examined different carbon and nitrogen sources for hydrogen production and further established the conditions for optimum hydrogen production by R. sphaeroides. Methods: The cumulative hydrogen produced by the bacteria at various intervals of time was measured using a Gas Chromatograph. Initially, by classical one factor at a time method, it was found that Benzoate and Glycine promote higher amounts of hydrogen production under anaerobic light conditions after 96 h. Results: The production was also observed to be enhanced in the presence of growth factors B12. Further, the Response Surface Methodology (RSM) was employed to optimize the hydrogen production. The first level of optimization was done using Box-Behnken Design (BBD) followed by Central Composite Design (CCD) method. The maximum production of hydrogen achieved by BBD and CCD was 6.8 ml/30 ml and 8.12 ml/30 ml, respectively. The significant model predicted is a quadratic model with R2 value 0.9459. Conclusion: Moreover, work presented here suggests an environment-friendly approach of harvesting H2, which could meet energy demand as clean fuel via the green route.

Background: Renewable sources of energy like biodiesel are substitute energy fuel which are made from renewable bio sources or biomasses. Due to many advantages of using algae (Chlorella sp), we performed design of experiments in terms of functional and biochemical factors such as biomass, chlorophyll content, protein moiety and carbohydrate and lipid contents. Objective: Our objective is maximization of lipid accumulation (y1) and chlorophyll content (y2) and minimization of carbohydrate consumption (y3), protein (y4) and biomass (y5) contents. By using the experimental data, the regression model has been developed in order to obtain the desired response (biomass, chlorophyll, protein, carbohydrate and lipid) therefore it is necessary to optimize input conditions. The pre-optimization stage is an important part and useful for the production of biodiesel as biomass which is renewable energy to improve the quality. Methodology: The corresponding input and output conditions with multi-objective optimisation using naïve & sorting genetic algorithm (NSGA) is X1=0.99, X2=0.001, X3=-1.111, X4=0.01 and Lipid= 42.34, Chlorophyll=1.1212 (μgmL-1), Carbohydrate= 24.54%, Protein= 0.0742 (mgmL-1), Biomass=0.999 (gL-1). Conclusion: The multi-objective optimization NSGA prediction is compared with the response surface model combined with a genetic algorithm (RSM-GA) and we observed better productivity with NSGA.

Background: Brazilian bentonites have a low sodium concentration in their interlayer structure. This is a problem with most of the industrial applications that demand the characteristics of sodium bentonites. Objective: As a solution for this limitation, sodium carbonate is added to in natura clays, promoting ion exchange between other interlayer cations with sodium. Methods: A process was used based on the principle of Stokes’ Law (BR Patent 10 2013 016298). For this, we used four glass columns in series, in which a high water flow was considered to obtain purified clays. It was proposed as a simple, fast and economical method for sodium determination that was developed and applied in bentonites by flame photometry. The equipment calibration was performed with a NaCl standard solution in concentrations between 80 and 110 ppm. The bentonites in the suspension were separated by means of centrifugation, being thus analyzed by a flame photometer. Results: The samples were prepared according to the manufacturer’s specifications to contain detectable amounts of sodium by means of flame photometry. A resulting linear relationship between the average value readings versus sodium standard content solution (both in ppm) was obtained by the logarithmic scale, as expected. Conclusion: The procedure allowed to define a method that could be used in the sodification control process, thus making it possible to differentiate the sodium cation content in terms of the value of cation exchange capacity (CEC) from bentonite. X-ray analysis of in natura and the sodified clays showed nanostructural differences related to interlayer distance.

Background: Fatty alcohol polyoxyethylene ether sulfonate (AESO) was synthesized by the following two steps reactions: fatty alcohol polyoxyethylene ether 5 (AEO-5) reacted with metallic sodium to form sodium alkoxide, then in toluene solvent, the sodium alkoxide reacted with 2-chloroethyl sulfonate sodium to form AESO. Methodology: The reaction factors, such as temperature, reaction time and reactant ratio, which effect on the product yield were discussed. The products were characterized by Fourier Transform Infrared (FTIR) spectra in order to examine the aim of the product synthesized. The AESO performances including thermal stability, salt resistance, emulsifying and surface properties were studied. Results: The results show that the optimum conditions of AESO synthesis are as follows: the reaction temperature is 64oC, the reaction time is 5h, the molar ratio of chloroethyl sulfonate sodium and sodium alkoxide is 1.2:1. In the above reaction conditions, the AESO has the highest yield, which is 74.43% and its purity is 89.25%. AESO’s surface properties, thermal stability, and salt resistance are much better than that of fatty alcohol polyoxyethylene ether sulfate (AES). The AESO presents the best emulsifying performance at the concentration of 1250mg/L. Conclusion: The solubility of AES and AESO are all increased due to the EO groups’ existence and their hard water resistances are better than that of lauryl sodium sulfate. The foamability test shows that AESO has the best foaming ability at the concentration of 1480mg/L, which decreases with the increase of the Ca2+ concentration, but the foam stability increases. It can be seen that AESO has favorable resistance to high temperature and high salinity.

Background: Lead ions form a dangerous pollutant to both human and aqua lives when discharged to the environment with wastewater due to the diseases and the damage of the live cells caused by these ions, so, it is very important to find an effective method for lead ions removel. Methodology: Lead ions were successfully recovered from simulated wastewater by a flowthrough batch recycle electrochemical reactor with stainless steel tubes bundle as a cathode operating under mass transfer control conditions in 0.5 M NaCl electrolyte solution. Effects of initial lead ions concentration, electrolyte flow rate, and PH were studied and the mass transfer coefficient was determined under these conditions. Performance of this reactor was analyzed by the construction of some figures of merit like fractional conversion, specific energy consumption, space-time yield, and space velocity. Results: Experimental results were correlated in the general form of a dimensionless mass transfer correlation as SH = 1.024Re0.00699Sc1/3.

Background & Objective: In this paper, jute yarns were bio-treated with pectinase enzyme. Then, the untreated and bio-treated yarns were dyed with Direct Yellow 24. The biotreated jute yarn showed higher dye sorption compared to that of untreated jute yarn. Methods: The sorption isotherms were fitted with the Nernst, Freundlich, Langmuir, Temkin and BET models. At all temperatures studied, the experimental data were better described with the Freundlich model. Thermodynamic parameters such as a change in free energy (ΔG0), the enthalpy (ΔH0), and the entropy (ΔS0) were also evaluated. The values of ΔH0 and ΔG0 indicated that the sorption of direct dye onto jute yarn was a physical sorption process. Furthermore, the sorption process was exothermic and spontaneous. Results: The results indicated that bio-treated jute yarn was more favorable (1/n < 1) for the sorption of direct dye as compared to that of untreated jute yarn (1/n > 1). Conclusion: Among the kinetic models studied, it was found that the pseudo second-order kinetic model was the best model to describe the sorption process of Direct Yellow 24 onto the bio-treated and untreated jute yarns.