جستجوی مقالات مرتبط با کلیدواژه "response surface methodology" در نشریات گروه "علوم پایه"

This study aims to screen Salvia L. species to select a plant species with a high level of antioxidant activity and rosmarinic acid content to consider as a potential source for possible use in food industries and human health supplements.  For this purpose, eight Salvia species growing widely in Iran were selected to investigate their polar extract in terms of antioxidant activity and rosmarinic acid content. The polar extract of aerial parts of studied plants was obtained by methanol/water (1:1) and their DPPH radical scavenging potential was evaluated. Salvia sclarea L. showed the highest antioxidant activity and was selected to optimize the ultrasound-assisted extraction process. Antioxidant activity and rosmarinic acid were optimized by response surface methodology to obtain high amounts in the extract. The optimized condition for antioxidant activity was obtained as 40 min, 50% aqueous methanol, 0.1% acid concentration, and 0.07 plant-to-solvent ratio. Antioxidant activity for all studied plants resulted in the range of 1.66 and 0.16 for S. scalarea and S. chloroleuca Rech.f. & Aellen, respectively. In addition, the optimized condition for rosmarinic acid content was conducted as 30 min, 70%, 0.3%, and 0.05 plant-to-solvent ratio. Rosmarinic acid values in all plants studied were obtained at 0.30 and 23.24 mg/g plant dried weight for Salvia sahendica Boiss. & Buhse and S. sclarea, respectively. These findings indicate that optimizing extraction parameters for a distinct compound can be generalized for other plant species in the studied genus. However, optimization for some properties like antioxidant activity which originated from all components in the extract cannot be generalized for other plants. Furthermore, this study suggests that the optimized extract of S. sclarea promisingly can be applicable as a source of rosmarinic acid with considerable antioxidant activity in food industries and human nutrition supplements.

The study focuses on the synthesis of nanocomposite adsorbents from modified Graphene Oxide (mGO) polymerized with 5-AIPA groups (mGO-AIPA) using a simple coprecipitation method. Various methods including FT-IR, TGA, FESEM, XRD, and VSM were utilized to assess the morphology and properties of nanoparticles. The study analyzed the effectiveness of Cd (II) and Pb (II) ion adsorption by using the composite Response Surface Method (RSM). The factors evaluated included adsorbent dose, pH, contact time, and initial ion concentration. The results showed that the mGO-AIPA nanocomposite had the highest adsorption capacity for Cd (II) ions, at 120.51 mg/g, and for Pb (II) ions, at 198.79 mg/g, both at a pH level of 6.5. The correlation coefficients for the adsorption of Pb (II) and Cd (II) ions in the Freundlich isotherm model were 97% and 95%, respectively. Moreover, the removal of both metal ions by the mGO-AIPA nanocomposite was consistent with the 97% correlation coefficient of the pseudo-second-order kinetic model. The thermodynamic model analysis indicated that the adsorption process of both metals by the mGO-AIPA nanocomposite was exothermic and spontaneous. In conclusion, the study suggests that magnetic graphene oxide functionalized with organic polymers is an effective method of eliminating heavy metal pollution, particularly cadmium and lead ions, from aquatic environments.

The use of pesticides like malathion has been increased due to agricultural development and the diversification of plant pests and have caused serious impacts towards human health and ecosystem. The aim of this study was to use a material sourced from a bio-waste via cellulose extraction for the preparation of cationic nanocellulose fiber (NC) intended for the uptake of negatively charged ions of malathion pesticides. In this study, we reported the preparation and characterization of cationic functionalized-NC with glycidyltrimethylammonium chloride (GTMAC). The NC and functionalized-NC structural and chemical properties were characterized using Fourier transform infrared spectroscopy (FTIR), Elemental analyzer (CHNS), Field Emission Scanning Electron Microscopy with Energy Dispersive X-Ray Spectroscopy (FESEM-EDX), Transmission electron microscopy (TEM) and Zeta potential. The adsorbent weight (1.0-5.0 mg), contact time (30-150 s), and concentration of malathion (6.0-14.0 mg/L) were studied to determine the optimum condition using the composite central design (CCD) based on the response surface methodology (RSM). The adsorption capacity was obtained 54.34 mg/g with an adsorbent weight of 1.0 mg, contact time of 130 s, and initial concentration of malathion 10.0 mg/L. The results revealed that quadratic model was proper for the prediction adsorption capacity of the adsorbent. The adsorption kinetics and isotherms were examined under optimal conditions. The Langmuir with a coefficients of determination (R2) = 0.9737 and pseudo-first-order with (R2) = 0.9774 were identified as the optimal models. The results showed that the NC-GTMAC can be effective and affordable adsorbent towards malathion in aqueous solution.

Since natural bitumen without additives is not suitable for creating a robust pavement structure to withstand diverse weather conditions and traffic loads, researchers have been exploring innovative methods to improve and enhance the properties of bitumen in recent years. This paper aims to optimize the composition of modified bitumen, considering the best physical performance for use in hot regions. To achieve this, the influence of four types of additives, namely Recycled Tire Rubber (RTR), Styrene-Butadiene-Styrene (SBS), reused Low-Density PolyEthylene (LDPE), and Sulfur (S), at three levels, is evaluated on the properties of bitumen using the Response Surface Methodology based on Central Composite Design (CCD). Based on the evaluations, optimal values for the additives are determined. Laboratory results demonstrate that the optimal values of the additives not only improve the penetration grade, softening point, ductility, and viscosity of bitumen but also exhibit synergistic effects. Furthermore, the addition of mineral additives significantly enhances the storage stability of the incorporated polymers in bitumen. The optimized modified bitumen, with the aforementioned properties, demonstrates an error value consistently less than 2% of the measured values, providing satisfactory performance for use in hot regions.

The adsorption of zinc, lead, and copper ions onto silica gel adsorbent has been successfully carried out in this study. Linear regression of polynomial transformation from input variables was employed to model the correlation between estimator variables (adsorbent dose, initial concentration, contact time, and pH) and output variable (%removal). Although the R2 scores varied, overall, the models performed well in predicting metal ion removal. The regression coefficients of the models revealed that adsorbent dose and pH were the most significant factors for zinc and copper adsorption, while initial concentration and contact time also have a significant role in lead adsorption. Bayesian regression was used as a complementary approach to Response Surface Methodology (RSM), revealing different weight distributions for zinc and copper adsorption compared to RSM polynomial regression. The study concludes that copper and lead adsorption using RSM are more reliable compared to zinc, and suggests further optimization of factors or levels for more accurate results. The use of Bayesian regression provides valuable insights into variable weights and can improve the optimization process. Overall, this study provides useful information for designing efficient metal ion adsorption processes. This study provides useful insights for future research on the competition for metal ions in adsorption processes.

The bioconversion of sweet sorghum bagasse as lignocellulosic biomass into bioethanol is a complex and challenging process. The present study focuses on optimizing the pretreatment, enzymatic hydrolysis, and fermentation processes during bioethanol production from the bagasse of a drought-tolerant and high-yield sweet sorghum genotype (ISCV 25264).A comparison of acid and alkali pretreatment methods on enhanced enzymatic saccharification of sweet sorghum bagasse indicated that alkali pretreatment with NaOH was more effective. Three independent variables including the NaOH concentration (2-4%), pretreatment time (10-40 min), and pretreatment temperature (80-120°C) were optimized using Response Surface Methodology (RSM) based on central composite design. Pretreatment optimization resulted in a glucose concentration of about 84 g/L during the enzymatic hydrolysis. Afterward, the key variables affecting the hydrolysis process, which included the substrate concentration (5-10%), time (20-70 h), and the temperature (38-50°C) of the hydrolysis reaction were optimized by RSM. Glucose concentration was increased to 93 g/L by using the optimized enzymatic hydrolysis parameters (substrate concentration of 10%, incubation time of 60 h, and incubation temperature of 50°C). Subsequently, Simultaneous Saccharification and Fermentation (SSF) and separate hydrolysis and fermentation (SHF) methods were performed for bioethanol production using Saccharomyces cerevisiae. The results indicated that the ethanol concentration after 48 h was higher under the SHF method (48.714 g/L), compared to SSF (29.582 g/L); however, this method was not commercially attractive due to the much longer total time for bioethanol production. Finally, optimization of the parameters during the SSF process (substrate and yeast concentrations of 30% and 4%, respectively) led to an ethanol concentration of 33 g/L. The optimization of the bioethanol production process in this research has created a platform for pilot-scale studies to investigate the feasibility of bioethanol production from sweet sorghum bagasse at the industrial level.

To enhance the effectiveness of medicinal medicines and minimize side effects, the expansion of an intelligent oral drug delivery system that is sensitive to the pH in the human body is a critical need. Here, pH-sensitive nano molecular imprinted polymers (NMIPs) were synthesized as a drug carrier to release mesalazine in the colon. A precipitation polymerization process was employed to synthesize the NMIPs using mesalazine (MZ), methacrylic acid (MAA), ethylene glycol dimethacrylate (EGDMA), and azobisisobutyronitrile (AIBN) as a template, functional monomer, cross-linker, and radical initiator, respectively. The preparation conditions of the MIPs were optimized by the Response Surface Methodology (RSM) based on the Central Composite Design (CCD) by investigating the effect of two main factors as Molar ratio of drug/monomer and the Molar ratio of monomer/cross-linker. The predicted data are in admissible assent with the empirical data using RSM (R2 = 0.9729). The optimum molar ratio of the template: monomer: cross-linker was achieved 1:2:10. The synthesized nanopolymers were characterized by Fourier Transform InfraRed (FT-IR) spectroscopy, Scanning Electron Microscopy (SEM), Transmission Electron Microscope (TEM), Brunauer Emmett Teller (BET), X-Ray powder Diffraction (XRD) and Thermo Gravimetric Analysis (TGA). The NMIP-loaded release with MZ was investigated in vitro and shown to an extremely pH-dependent. The desorption process showed that the drug desorption was minor in simulated gastric fluid (pH = 1.2), In contrast, in the simulated colon fluid (pH = 7.4), it was sustained and represented a great method for delivering colon-specific medication. These polymers showed 10.35% and 99.16% drug release at pH 1.2 and 7.4, respectively. According to kinetic investigations, the drug's release rate closely matches the first-order equation. The results demonstrate that the NMIPs can be used as a pH-responsive oral delivery system to deliver drugs to target organs in a regulated manner.

This research investigates the usage of pipette tip micro solid phase extraction for the separation of 6-mercaptopurine of complicated matrices before its spectrophotometric detection. To overcome the non-selectivity of spectrophotometry, an ethylene glycol dimethacrylate-based molecularly imprinted polymer was prepared and applied as an adsorbent, which enabled selective and fast extraction of the analyte. To improve the transfer of the analyte to the adsorbent, salting-out effect was employed by the addition of 300 mg of NaCl to the sample before performing microextraction. Variables affecting the microextraction of the protocol were investigated utilizing two ways of one-factor-at-a-time and response surface methodology, which showed good consistency with each other. Extraction parameters were optimized as pH of sample = 9.0, sample volume = 10 mL, amount of adsorbent = 2.0 mg, eluent = 250 µL of methanol:acetonitrile (1:5 v/v), and extraction and elution cycles of 10 and 12 times, respectively. The dynamic linear range of the protocol was 1.0–1000.0 µg L-1, with a limit of detection of 0.25 µg L-1. The method was compared with extraction by a non-imprinted polymer. The extraction efficiency of the analyte obtained from 96.0% to 99.8%, by relative standard deviations better than 5.3%. The suggested technique was employed to determine 6-mercaptopurine in seawater and body fluid samples, and the results were validated by comparing them to a standard HPLC method. The whole analysis time, including microextraction, was about 25 minutes and to perform this method, the sole instrument required is a conventional spectrophotometer.

Efficient management of economic and sustainable production of microalgae necessitates the strategic utilization of influential growth factors. A pivotal aspect involves optimizing the utilization of photonic energy in conjunction with environmental parameters through elevating algal efficiency to its maximum potential. This investigation delves into the effect of Light Emitting Diodes (LEDs) on different microalgal species under diverse conditions, specifically exploring the impact of blue light intensity, photoperiod, and phosphorus on biomass and chlorophylls a and b content in Chlorella vulgaris. To achieve this objective, a Response Surface Methodology (RSM) approach was employed. The study revealed that the combination of 40 µmol photons . m-2. s-1, 12:12 photoperiod (light:dark), and 80 mg/L phosphorus in media yielded a biomass production of 40*106 cells/ml and 27.7 mg/L chlorophyll a, respectively. Furthermore, response surface analysis identified the optimal condition at 36.58 µmol photons . m-2 . s-1, a 12:12 photoperiod, and 80 mg/L phosphorus in media, which led to 36.24*106 cells/ml, 27.83 mg/L chlorophyll a, and 5.43 mg/L chlorophyll b, with a remarkable approval rating of 93 percent. These findings indicate the potential of LEDs technology to augment biomass production and enhance the content of bioactive compounds in microalgae, thereby endowing them with significant economic value across diverse industries.

Wastewater treatment plants are an important pathway for microplastics (MPs) to enter the environment. In recent decades, hybrid treatment technologies such as sono-electrocoagulation have been used to treat various types of wastewater. This study aimed to remove polypropylene microplastics from synthetic wastewater by sono-electrocoagulation process using central composite design. The central composite design was utilized to investigate the relationship among four independent variables including the number of MPs (0.003-0.03 MPs/L), sodium sulfate concentration (180-9000 mol/L), voltage (1-15 V) and reaction time (20-180 min) on the efficiency of polypropylene microplastic. Design Expert 13 software and central composite design method were used to design and analyze the experiments and results. The optimum number of concentration of MPs, sodium sulfate concentration, voltage, and reaction time were found to be 6343.36 MPs/L, 0.0181924 mol/L, 10.0356 V, and 62.21 min, respectively. In optimal conditions, polypropylene removal was found to be %90.34. Central composite design proposed a quadratic model for this process. Adequacy of the model using lack of fit statistical tests values, p-values, and F-values was checked, yielding the values of were 1.76, 0.0001 ˂, 19.51, respectively. The R2, R2 adjusted, R2 predicted values which were 0.9367, 0.8776, 0.6959, respectively. Considering the proper removal efficiency, the sono-electrocoagulation process can be used to remove microplastics.

In this study, the effects of ethanol-butanol/gasoline blends (EB0%, EB10%, and EB20%) on spark ignition engine performance and emissions were investigated for the different compression ratios (6.0:1, 8.0:1, and 10.0:1), and different load conditions (2kW, 4kW, and 6kW). Based on the experimental results, the response surface methodology has been used to develop a model and to estimate the outputs of brake thermal efficiency, brake-specific energy consumption, carbon monoxide, hydrocarbon, and oxides of nitrogen. The optimum operating conditions, 9.970% of the ethanol-butanol blend, 10.0:1 compression ratio, and 6 kW of engine load were obtained through the desirability approach of response surface methodology. Brake thermal efficiency, brake-specific energy consumption, carbon monoxide, hydrocarbon, and oxides of nitrogen at optimum conditions are 35.041 %, 0.493 kg/kWh, 0.217 %, 213.575 ppm, and 1263.787 ppm, respectively. Moreover, the developed models have higher R2 values near 1, and the optimum responses are obtained with a higher desirability value of 0.768. Ethanol-butanol/gasoline blends improved the brake thermal efficiency, carbon monoxide, and hydrocarbons. Whereas it increased the brake-specific energy consumption and oxides of nitrogen.  In addition, the validation test results illustrate that the acceptable error rate between optimized values obtained through the desirability approach of response surface methodology and experimental values is below 7%.

In this report, different extracts from the aerial parts of Ammi visnaga (L.), e.g., flowers, leaves, and stems were prepared using water, methanol, and ethanol. To optimize the extraction process, the design of mixtures was carried out using different extracting solvents and their combinations. The special cubic model explained the variance of the TPC and the antioxidant activity of the extracts at a level of R2 > 95%. In general, the analysis of the model-derived response surfaces revealed that in binary mixtures (50% ethanol + 50% methanol), the yielded values of phenolic compounds and the antioxidant activity increase with the water proportion of different prepared mixtures. The ability of the quaternary mixture to extract the phenolic compounds was also positively and significantly influenced by the water content, creating a mild polar medium for the extraction of phenolic compounds. The phenolic profile of different extracts under study revealed the presence of a cocktail of active ingredients, including chlorogenic acid, caffeic acid, rutin, p-coumaric acid, etc. especially the flower extract of A. visnaga (L.).

In this study, ZnO/Fe2O3 and ZnO/activated carbon nanoparticles have been employed as efficient adsorbents for the removal of ibuprofen antibiotic from aqueous solutions. Nano-adsorbents were characterized using X-ray diffraction (XRD), scanning electron microscopy (SEM), and transmission electron microscopy (TEM) analyses. The results illustrate that the ZnO/Fe2O3 and ZnO/activated carbon nanocomposite were successfully synthesized. Optimization of the removal of ibuprofen was scrutinized via response surface methodology (RSM) based on central composite design (CCD). The process parameters, such as pH (4-6), contact time (10-20 min), nanoparticles dosage (0.02-0.04 wt.%), and nano-adsorbent type (ZnO/Fe2O3 and ZnO/activated carbon) were investigated in batch experiments. Within the range of the chosen experimental conditions, the optimized values of pH, contact time, nanoparticles dosage, and nano-adsorbent type were obtained to be 5.48, 17.22 min, 0.03 wt.%, and ZnO/Fe2O3, respectively. According to the optimum condition, the anticipated Ibuprofen removal was 83.74% and the empirical value was 85.42%. The high values of R2 95.96 and R2 adj 93.78 demonstrate that the fitted model shows a satisfactory accord with the anticipated and empirical Ibuprofen removal. Adsorption kinetics and isotherms are well-fitted with pseudo-second-order and Langmuir models, respectively, meaning that monolayer adsorption of Ibuprofen to the adsorbent's surface is controlled by electrostatic interactions, stacking of π-π, and linkages of hydrogen

This study extracted the essential oil from Foeniculum vulgare Mill seeds (Fennel) with subcritical water and compared it to the method of Hydro distillation. The important ingredient of essential oil is trans-Anethole. Identification of substances in essential oil and their amount were performed by GC and GC/MS analysis. The effect of temperature, mean particle size, flow rate, and extraction time on the amount, and quality of subcritical water extraction was studied. To facilitate the experiments and investigate the effect of the parameters in their extraction and interaction, used the method of response surface with a central composite design (CCD). The optimum conditions for trans-Anethole extraction happened at a temperature of 125 °C and a mean particle size between 0.5 and 0.71 mm in 65 min and a flow rate of 25.1 mL/min. The total maximum yield (0.02345 mg essence/g dry sample) obtained at the optimal conditions was more than that achieved by the Hydro distillation method (0.01322 mg essence/g dry sample).