جستجوی مقالات مرتبط با کلیدواژه « response surface methodology » در نشریات گروه « شیمی »

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.

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.

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.

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.

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).

Carbon monoxide is one of the main air pollutants, mainly produced from the incomplete combus tion of fossil fuels. This s tudy aims to oxidize carbon monoxide by copper oxide nanoparticles immobilized on zeolite13X subs trate. The present inves tigation was conducted to determine the effect of carbon monoxide concentration parameters (in the range of 200-1400 ppm) and reaction temperature (in the range of 100-500 °C) on the efficiency of carbon monoxide conversion by CuO/Zeolite 13X nanocatalys t. The design of the experiment and the determination of the number of experiments were analyzed using the central composite design method, and the s tatis tical tes t of analysis of variance was done using the response surface method. Also, the s tructural and morphological characteris tics of the nanocatalys t were inves tigated using BET, BJH, FE-SEM, EDX, and XRF tes ts. The results show that CuO/Zeolite 13X nanocatalys t efficiently oxidizes carbon monoxide. The highes t conversion efficiency of 82.6% was obtained at a temperature of 400 °C and a carbon monoxide concentration of 500 ppm as the optimal conditions. According to the EDX tes t results, copper oxide nanoparticles with a weight percentage of 5.9% were loaded on the Zeolite 13X subs trate. Design Expert11 software reduced the cubic model with an R2 coefficient of 0.98.

In this study, an attempt was made to synthesize a new sorbent based on the second generation of silica coated magnetic poly(amidoamine) (Fe3O4@SiO2@PAMAM) to improve the performance of magnetic solid phase extraction (MSPE) of some antifungal drugs including miconazole, clotrimazole and ticonazole in various real samples such as urine and human plasma. The extracted analytes were measured by high performance liquid chromatography equipped with ultraviolet detection (HPLC-UV). Field emission-scanning electron microscopy (FE-SEM), X-ray diffraction analysis (XRD), Thermogravimetric analysis (TGA), Transmission electron microscopy (TEM) and Fourier transform-infrared spectroscopy (FT-IR) were used to study the morphology and structure of the prepared sorbent. The various factors such as: extraction time, sorbent amount, solvent desorption volume, desorption time, ionic strength and pH were studied and optimized. The method is validated according to ICH guidelines with respect to precision, accuracy, linearity, specificity, robustness, and limits of detection and quantification. Under the optimized condition, the linearity of the method was in the range of 1–500 µg L-1 (miconazole= 1-200 µg L-1, clotrimazole = 1-500 µg L-1 and ticonazole = 1-200 µg L-1). The obtained correlation coefficients (r^2) were between 0.9871-0.9977. The limits of detection (LODs) were also calculated to be 0.14-0.18 µg L-1 (miconazole= 0.16 µg L-1, clotrimazole = 0.18 µg L-1 and ticonazole=0.14 µg L-1). The limits of quantification (LOQs) were also in the range of 0.46-0.60 µg L-1 for the selected analytes. The relative standard deviations (RSDs%), were obtained in the range of 4.6 to 5.9%. Moreover, the calculated enrichment factors were between 85 and 93. The proposed method was also employed for the analysis of various real samples such as urine and plasma samples. The obtained recoveries indicated that the method was useful and applicable in complicated real samples

The main goal of this study was to apply chemometrics techniques such as (ANOVA)-Simultaneous Component Analysis (ASCA), Response Surface Methodology (RSM), and Central Composite Design (CCD) to identify important factors in Dexamethasone Sodium Phosphate (DSP) microextraction from plasma samples. This work proposes the pre-concentration and determination of DSP using a Dispersive Liquid-Liquid Microextraction (DLLME) and spectrophotometry in combination with chemometrics approaches. ASCA as a multivariate statistical tool was used to more thoroughly analyze the influencing factors on DLLME and their interactions. By ASCA the diversity of the data matrix was divided into five levels for four variables: the major impact of each experimental component (dispersive and extraction solvent volume, amount of salt, and incubation time), followed by the impact of each second-order interaction. The significance of each factor or interaction effect was determined by a permutation test. The outcomes were compared with the results of the ANOVA approach to determine the ideal circumstances for measuring the trace amount of DSP. Under optimal conditions, a linear calibration curve with a detection limit of 0.071 µg/mL in the 0.1-5 µg/mL range was obtained.

Recently, the synthesis of biolubricants has been the focus of researchers because of their good lubricating properties and environmentally friendly products. This study was performed to optimize reaction parameters for the enzymatic transesterification reaction between waste edible oil methyl ester (biodiesel, FAME) and trimethylolpropane (TMP) by using Response Surface Methodology (RSM). The parameters that affect the enzymatic transesterification reaction were chosen as temperature (35–55°C), amount of catalyst (0–10 %wt. of mixture), TMP-to-FAME molar ratio (0.17-0.33), and reaction time (0–96 h), to produce TMP triester (biolubricant). Response surface methodology (RSM) and three-level–four-factor Central Composite Design (CCD) were employed to evaluate the effects of these synthesis parameters on the percentage conversion of FAME by transesterification. Enzyme amount and reaction time were the most important variables. The optimum reaction conditions were determined to be the temperature at 50°C; the amount of catalyst, 5%wt; molar ratio, 0.25 and 48 h of reaction time, under these conditions 91% TMP ester's yield was obtained. The interaction parameter of the lipase quantity with the FAME to TMP molar ratio was found to be the most important among all of the other parameters.

The non-toxic BSA-based NanoParticles (NPs) are developed without any additives with hydrothermal SubCritical Water Treatment (SCWT). The optimum BSA-based NPs are gained by applying Response Surface Methodology (RSM) based on particle size, zeta potential, and polydispersity. The SCWT conditions are optimized in terms of these three dependent variables, which have significant impacts on the BSA-based NPs application. The optimum BSA-based NPs prepared with 2.73% (w/v) of initial BSA solution concentration, the lowest initial concentration that is used to synthesize BSA-based NPs by now. The SCWT condition of 173 °C and 2.07 min of SCWT holding time shows that the zeta potential of -38.87 mV with the finest particle size and PI (147.32 nm and 0.24, respectively) is the optimized composition. The fabricated BSA-based NPs are characterized by the UV-vis, screening electron microscope (SEM), and stability assessment study.

A large amount of sugar beet pulps are produced annually as waste which causes environmental pollution. However, the composition of sugar beet pulp indicates the possibility of producing several value-added products. In this study, high-quality α-cellulose was extracted from sugar beet pulp. The purity and optical properties of α-cellulose significantly affect its application in various industries, such as the production of napkins or a variety of papers. The bleaching step has a significant effect on the quality of cellulose. So bleaching conditions including the concentration of NaClO (4.5-1 % w/w), temperature (25-60 °C), and time (15-45 minutes) were optimized based on response surface methodology. The results showed good optical properties, low Kappa number, and high cellulose content (yield) could be achieved when the operating parameters were controlled. Severe bleaching conditions such as higher NaClO concentration or longer bleaching time caused cellulose oxidation and reduced efficiency. Optimal bleaching conditions for SBP were determined as 3.28% (w/w) NaClO at 25 °C for 45 minutes. These conditions led to the production of α-cellulose with a 69.38% of whiteness index, a Kappa number of 1.02, and a yield of 23.16%. The structure of the samples was investigated by SEM and FT-IR analysis. Therefore, the pulping and bleaching process has led to value-added products with industrial applications from sugar beet pulp.

In this study, the removal of vitamin B2 from the aqueous solution using a synthesized multi-component nano-magnetic adsorbent modified by orange peel was studied. The structure and the morphology of the prepared nanocomposite were characterized using Fourier Transform InfraRed (FT-IR), X‐Ray Diffraction (XRD), Scanning Electron Microscopy (SEM), Atomic Force Microscopy (AFM), Brunauer–Emmett–Teller (BET), and Dynamic Light Scattering (DLS) techniques. The average size of the synthesized nanoparticles was 80 nm. The effect of experimental parameters such as pH, amount of adsorption, and contact time on vitamin B2 adsorption was investigated. Response Surface Methodology (RSM) based on the Central Composite Design (CCD) was used to obtain the optimum conditions for removing vitamin B2. Results revealed that the pH=5, adsorbent dosage of 0.4 g, and contact time of 180 min were obtained as optimum conditions. The isotherms (Langmuir, Freundlich, Temkin) and kinetic (pseudo-first-order, pseudo-second-order) studies were assessed. The data were fitted well with Langmuir (R2=0.9984) with qmax=53.47 mg/g and pseudo-second-order (R2=0.9984) models. The results showed that the two-component magnetic nanoparticle modified with orange peel, as an adsorbent, was suitable for the process of vitamin B2 adsorption from the aqueous solution.

In the current research sodium silicate has been used to synthesize silica colloid by ion exchange process. Deterministic relations for zeta potential, size and solid content have been developed by optimization of three input parameters: seed concentration (0, 1, 2%wt), temperature (30, 55, 80°C) and KOH concentration (0.5, 1, 1.5%wt). Central Composite Design of Response Surface Methodology was used to optimize silica colloid. The goal of this optimization is to achieve the silica colloid with the highest zeta potential, the minimum particle size and the highest solid content. The derived equations and contour plots predict the values of selected independent variables for preparation of optimum silica colloid with desired properties. Based on the fitted models, the optimum silica colloid is prepared by 0.756%wt KOH in 70°C that contains 59.9 %wt SiO2. Also, this silica colloid sample contains a particle size of 11.5 nm and zeta potential of -6.48 mV.