Zeolite were formed through agar gelcasting method.Response surface methodology ( RSM ) is proposed as a tool for rapidly optimizing the activation parameters in order to obtain the highest porosity of samples. 40 % of zeolite and 1 wt %  of agar was selected as optimal conditions. porous bodies with an optimal combination of 54.4% porosity , density 0.9 g / cm3 , and compressive strength of 6.67MPa  were made and observed that there is a slight difference between predicted values by the software and the measured values.  Longer time to mixing from 1 / 5 min to 3 min , the porous body has 67.17 % porosity , density 0.69 g / cm3 , and compressive strength of 5 / 3 MPa .XRD and SEM analysis was used to investigate the phase and structural changes at 800 C. The highest percentage of adsorption of methylene blue at 4ppm concentration after 72 h was 98.94 %.

Introduction: Kojic acid with the chemical structure of 5-hydroxy-2-hydroxymethyl-ˠ-Piron is an organic acid that is biologically produced through aerobic fermentation process by using various substrates and via the function of variety of fungi. This study was aimed to study the optimization of Kojic acid production by Locally Isolated Fungi Aspergillus sp., using ‘Response Surface Methodology’.Materials and Methods: Kojic acid was produced by fermentation of isolated strain of genus Aspergillus in submerged culture medium. Initial investigation in Kojic acid production process was performed via Plackett-Burman method and by using different nitrogen sources such as yeast extract, peptone, ammonium sulfate, ammonium chloride, urea as well as different carbon sources, including fructose, sucrose, glucose, lactose and maltose.Results: Based on our study, peptone and glucose were the most effective factors with carbon and nitrogen sources in production of kojic acid (P<0.05). The next step was production of 34.4g/L kojic acid by optimizing the effect of environmental factors such as temperature, pH, glucose and peptones, such as carbon and nitrogen sources, used in production of kojic acid and by employing ‘Response Surface Methodology’.Conclusion: Based on the results of this study, the maximum production of kojic acid can be achieved by using; glucose (%8.71), peptone (37.4%), temperature (29.9oC) and adjusting pH to 6.75 in the production process.

In this research, in order to separate germanium from an aqueous solution containing tartaric acid, liquid-liquid extraction (LLX) and supported liquid membrane (SLM) were employed. In these systems, polytetrafluoroethylene (PTFE) as the membrane and Alamine 336 as the carrier/extractant were used. In the LLX system, the effect of concentrations of extractant, tartaric acid, and HCl as a strippant was studied. As a result, the germanium extraction efficiency increased 100% after reaching Alamine 336 concentration to 10 %v/v. At the tartaric acid concentration of 0. 275 mM, the highest germanium extraction (98. 6%) was obtained. According to the SLM experiments, the carrier concentration of 15 %v/v was enough for the efficient transport of germanium from feed to strip phase. In comparison with LLX system, despite transportation of all germanium species in the SLM system, the time of this process (20 h) is higher than that of the LLX system.

Response Surface Methodology is used to optimize the parameters of a process when the function that describes it is not known and the experimenter wants to find the optimal solution of process input variables by RSM.In some cases, there is more than one response and it is necessary to optimize them simultaneously. But the experimenter always knows about producer requirements (such as standards, objectives, etc.) and customer need can be another response in multiresponse surface problems. High technology industry, with more competitiveness, must continuously improve multiple correlated product quality characteristics and the consumer must assess them. This paper extends the ideas of a multiresponse surface to the tracking of dynamic optimization, with respect to customer response. Indeed, this study presents a new approach to formulate multiple response customer voice (by using Conjoint Analysis) and other responses and, also, by solving the correlated responses using a metaheuristic optimization method. The proposed procedure is illustrated with an experiment from the literature.

Since Amaranth (AM) is one of the dye compounds which is harmful to human’ s life its removal from industrial waste water would reduce their environmental impact and health effect. Copper nanoparticle (CuNP) is a simple and eco-friendly material which can be used to remove this pollutant. In this paper, copper nanoparticles were synthesized, for removal of AM dye. The experiments were designed by response surface methodology with a modified cubic model to predict the variables. To investigate variables and interaction between them analysis of variance was used with high F-value (1. 44), low P-value (<0. 0409), non-significant lack of fit, the determination coefficient of 0. 898 and the adequate precision of 7. 25. Experimental and predicted values of the response illustrated a good correlation. The optimum parameters catalyst amount (0. 14 w/w%), initial concentration (7. 38 mg/l), reaction time (47. 75 s) and pH (2. 83) for the highest removal percentage of (96. 10%) was attained.

Background and objectives: Rice is a very popular cereal in world and very important from economic point of viwe. The problems of drying paddy rice is lack of drying uniformity in the paddy rice that creates stress temperature and moisture and thus will cause losses in the later stages. The purpose of this research was to develop a high performance system for processing the paddy to healthy white rice in the shortest drying time. Materials and methods: In this study, to reduce losses and increase the drying rate, an innovative laboratory rotary dryer machine was used. The response surface methodology (RSM) with central composite design was used for modeling and determinimg the optimum processing conditions for paddy drying. Independent variables for this process were temperature (40 to 80° C), cylinder rotation speed (2 to 10 rpm) and the cylinder fullness (25 to 66%). The percentage of breakage, percentage of crack and drying time were used as response parameters to develop predictive models and optimize the drying process. Results: The results showed that the temperature, cylinder rotation speed and cylinder fullness had significant effect (P<0. 01) on the percentage of breakage, percentage of crack and drying time, as temperature was the most effective parameter. According to optimization process, the minimum losses (percentage of breakage and percentage of crack) and drying time were found with the inlet air temperature 56. 53 ° C, cylinder rotation speed of 10 rpm and the cylinder fullness of 54. 20%. Conclusion: Conditions and parameters of drying process had important rule in the final quality properties and losses of paddy rice. Our results revealed that RSM could be used to develop adequate prediction models for describing quality changes in paddy rice during drying. The changes in the quality parameters were adequately described by quadratic model. Also, the result showed that inlet temperature was more important than cylinder rotation speed and cylinder fullness on losses of paddy rice.

A central composite face-centered design was used to study and to optimize lead biosorption from aqueous solution on Aspergillus terreus biomass. Four factors such as stirring speed, temperature, solution pH and biomass dose at different levels were studied. The hierarchical quadratic model were established by adding replicates at the central point and axial points to the initial full factorial design (24). The percentage removal of lead was affected by biomass dose, pH, and interactions between pH and biomass dose, pH and stirring speed, pH and temperature. The hierarchical quadratic model described adequately the response surface based on the adjusted determination coefficient (R2Adj=0.97) and the adequate precision ratio (42.21). According to this model, the optimal conditions to remove lead completely from aqueous solutions (at initial lead concentration of 50 mg/L and solutions of 100 mL) with Aspergillus terreus were at pH 5.2, 50oC, stirring speed of 102/min and a biomass dose of 139 mg. The response surface methodology can be used to determine the optimal conditions for metal adsorption on several adsorbents. In addition, results reported in this research demonstrated the feasibility of employing A. terreus as biosorbent for lead removal.