جستجوی مقالات مرتبط با کلیدواژه "optimization" در نشریات گروه "شیمی"

The electrochemical method of recovering tungstic acid uses nitric acid as the electrolyte. At the anode, carbide material is oxidized, yielding insoluble tungstic acid (H2WO4) and cobalt ions in the solution. Tungstic acid is then used to make tungsten oxide (WO3), a valuable industrial material. Initially, experiments in this study were prepared and carried out using experimental design approaches and grey relational analysis (GRA), which was based on the Taguchi method and carried out using Minitab17 software. Datafit (Versions 9.1) software was used to create regression models for predicting weight loss and energy usage. The goal function of the tests was anode weight loss/hour and electrochemical cell power consumption, whereas the impacting variables were current density, electrolyte concentration, cell temperature, and cathode electrode type. The optimal electrochemical cell has a current density of 4000 A/m2, 1.8 M electrolyte concentration and 70 °C cell temperature, and an aluminum cathode.

This research study utilized the synthesis method of the Cr-V@MOF5 catalyst to integrate findings from multiple prior studies. The oxidative dehydrogenation method was chosen due to its exothermic nature and lack of thermodynamic constraints on catalytic conversion, which are advantages over catalytic dehydrogenation without oxidation and thermal breakdown. In this research at Islamic Azad University in Omidiyeh, the catalytic bases of zeolite and metal-organic framework (MOF) were used. The synthesized catalysts were modified by some improvers, and each improver was assessed to find out which one is suitable for this oxidative dehydrogenation process. The goal was to reach the optimal point of propane-to-propylene conversion using statistical analysis. Design Expert software was utilized to ascertain the difference between the laboratory data and the optimized objective function. Subsequently, a comparison was made regarding the quantity of propylene produced in the presence of two distinct catalysts. The results revealed that the presented synthesis method is not repeatable. Also, the results showed that since the organometallic framework catalyst had a larger surface area compared with the ZSM-48 zeolite, it had a better catalytic performance than the zeolite catalyst. The functional comparison of zeolites and organometallic frameworks in terms of structure and the results of propylene production resulting from the performance of these two catalysts is also among the achievements of the project.

In this research, a new design approach for shell and tube heat exchanger optimization design based on NEPCM nanofluid and applying adoptive genetic algorithm has been developed. Nano Encapsulated Phase Change Material (NEPCM) was used as base fluid inside the Shell and Tube Heat Exchanger (STHE). A systematic optimization design approach has not been introduced for designing these nanofluid-based STHE. The exergy efficiency and cost are two important parameters in heat exchanger design. The total cost includes the capital investment for equipment (heat exchanger surface area) and operating cost (for energy expenditures related to pumping). Tube. diameter, tube pitch ratio, tube number, baffle spacing ratio, nanofluid concentration as well as baffle cut ratio were considered as seven design parameters. For optimal design of a shell and tube heat exchanger, it was first thermally modeled using eeNTU method while BelleDelaware procedure was applied to estimate its shell side heat transfer coefficient and pressure drop. Fast and elitist non-dominated sorting. genetic algorithm (.GA) with continuous and discrete variables were applied to obtain the maximum exergy efficiency and the minimum total cost as two objective functions. The results of optimal designs were a set of multiple optimum solutions, called ‘Pareto optimal solutions. The sensitivity analysis of change in optimum effectiveness and total cost with change in design parameters of the shell and tube heat exchanger was also performed and the results are reported. The results showed that using NEPCM concentration and tube number enhanced exergy efficiency around 9%, while increasing cost about 22%.

This study investigates the application of Deep Neural Networks (DNNs) to optimize the formulation, development, and performance evaluation of Metformin Hydrochloride sustained-release tablets, a key medication for managing Type 2 diabetes. Traditional drug formulation methods are often time-consuming and constrained by the complexity of the formulation process. This research addresses these challenges by utilizing DNNs to create predictive models that accurately forecast critical formulation outcomes, such as dissolution rates. The study began with a comprehensive pre-formulation analysis to assess the physicochemical properties of Metformin Hydrochloride and its compatibility with various excipients. Using a 3² factorial Design of Experiments (DoE) approach, 24 formulations (F1–F24) were prepared through the wet granulation method, varying the concentrations of Polyox WSR 303 and Povidone K30. The tablets were evaluated for post-compression parameters and in vitro dissolution performance. Experimental data from these formulations were used to train a DNN model to predict optimal formulation parameters based on performance metrics. Among the formulations, the DNN identified F1 as the optimal formulation, predicting a drug release of 99.23%. Experimental validation of F1 revealed an in vitro drug release of 98.95%, closely matching the predicted value. The optimal composition included 95 mg of Polyox WSR 303 and 115 mg of Povidone K30. A comparison with a computerized simulation model showed a difference factor (f1) of 1.71 and a similarity factor (f2) of 91.48, confirming a high degree of similarity between the dissolution profiles. This study highlights the potential of deep learning to streamline pharmaceutical development, improve formulation precision.

Teh present study examined its application in removing Zinc (Zn) from synthetic water. Teh mechanism for teh adsorption of Zn by sugarcane bagasse (SCB) and cashew nut shell (CNS) is linked to teh role played by teh vital stretching functional groups such as hydroxyl (-OH) and other phenol and aromatic groups, as revealed by teh Fourier Transform Infrared (FTIR) characterization technique. Teh existence of porous channels on teh activated carbon (AC) revealed by Scanning Electron Microscopy (SEM) and depleted Zn ions in teh water after sorption by Atomic Adsorption Spectrometry (AAS) analysis was an added merit. Teh effect of varying contact time (0-50 min) and initial Zn concentration (30-100 mg L–1) resulted in good fits of teh predicted adsorption capacity and removal responses (%), described by 3 quadratic and one linear model. Statistical metrics, 3D surface, and contour plots based on Central Composite Design (CCD) Response Surface Methodology (RSM) carried out put CNS-AC ahead of SCB-AC as teh most efficient adsorbent for ion removal under shorter and longer contact times. In optimized conditions, teh parameters such as initial concentration, contact time, removal, adsorption capacity, and desirability for CNS and SCB were achieved at (98.74 mg L–1, 50 min, 98.51%, 7.83 mg g–1, and 0.995) and (77.61 mg L–1, 5 min, 95.8529%, 6.01 mg g–1 and 0.816), respectively. Where teh need to use these adsorbents is found, it is important to consider teh abundance of teh plant waste in teh location or contrive a scheme for their massive production.

Today, there has been a significant emphasis on developing sustainable and environmentally friendly processes in various industries, including hydrometallurgy. This study focuses on the process of leaching chalcopyrite concentrate using an ionic liquid called 1-butyl-3-methyl-imidazolium hydrogen sulfate ([Bmim][HSO4]). To study the impact of various parameters on the chalcopyrite leaching, such as temperature, [Bmim][HSO4] and H2O2 concentration, speed of stirring, solid-to-liquid ratio, and their interactions, design expert software was used. Employing the CCD layout of RSM matrix, 32 experiments were designed and executed. The results showed that the temperature, oxidizing agent concentration, and ionic liquid concentration, as well as the interaction between the oxidizing agent concentration with the ionic liquid concentration and temperature, have the most significant effect on the dissolution of chalcopyrite. Also, the highest amount of copper extraction (90.32%) was obtained at 40°C using 40% [Bmim][HSO4], 30% H2O2, ratio of solid-to-liquid 10 g/L, and speed of stirring 300 rpm. The examination of kinetic studies employing the SCM showed that the process of extracting copper from chalcopyrite utilizing BmimHSO4 ionic liquid follows from the chemical reaction, and in this condition, the activation energy is 49.61 kJ/mol. Finally, evaluation of surface morphology and characteristics of leaching residue using XRD and SEM/EDX analyses revealed that most of the CuFeS2 has been dissolved and elemental sulfur is the major solid product that exists in the chalcopyrite leaching residue.

In this study, the impact of geometric characteristics on the Entransy Dissipations Total Number (EDTN), the Exergy Loss Number  (ELN), and the Entropic Potential Losses Number (EPLN) in Finned Tube Heat Exchangers (FTHEs) is investigated. Also, by using the NSGA2 method, the EDTN as the main part of irreversibility in the studied heat exchanger is minimized. The EDTN consists of two terms: thermal and frictional. In this research, the expressions of thermal and frictional entransy dissipations are minimized as two independent objective functions. The transverse tube pitch, mass flow rate, hot fluid inlet temperature, cold fluid outlet temperature, tube outer diameter, shape width, and shape height were chosen as optimization variables. The research revealed that as the tube's outer diameter increases, the EDTN and the EPLN decrease, and the ELN increases. It has been discovered that the values of the EDTN, EPLN, and ELN were 0.72, 0.4, and 0.48, respectively. It is obvious that the EDTN compared to the EPLN and the ELN is the main factor in the irreversibility investigation. It was also observed that by minimizing the EDTN, the efficiency of the FTHE was enhanced. by about 45.5% and the heat transfer rate was approximately 6.15 times its value prior to optimization. In addition, the optimization results indicated that the EPLN and the ELN were reduced by 66% and 34%, respectively, compared to the initial results.

In this study, an Electro-Fenton (EF) reaction was employed to treat hazardous and resistant wastewater from a pesticide factory using graphite cathode modified with industrial carbon black (N330). Carbon black nanoparticles (N330) could increase the porosity of the cathode surface and hydrogen peroxide production during the electro-Fenton reaction. In order to examine the quality of the porous surface of the modified cathode, Atomic Force Microscopy (AFM) and Field Emission Scanning Electron Microscopy (FESEM) tests were successfully applied. Moreover, the performance of the modified cathode was assessed by the Cyclic Voltammetry (CV) test. The experiments were designed using the Central Composite Designs (CCD) technique under the Response Surface Methodology (RSM). The Analysis of Variance (ANOVA) showed that the model accurately predicted the process. 78.15% of COD removal was optimally found with a current intensity of 253 mA, air flow rate of 1.56 L/min, Fe2+ catalyst dosage of 0.63 g, pH of 3, and reaction time of 126 min, while 33.78% of COD removal (with 15 mmol/l of hydrogen peroxide production) was obtained at pH of 6 (close to the original pH of wastewater) on the modified cathode.

An eco-friendly and cost-effective biosorbent has been developed for the efficient elimination of acid red 114 dye from aqueous media. Batch studies were carried out to determine the effects of various operating parameters, namely the effect of temperature, pH, contact time, and concentration. The Response Surface Methodology (RSM) and the Artificial Neural Network (ANN) are also examined. The quadratic model is the most useful model for describing the adsorption of AR 114 dye, with a correlation coefficient of 0.9506. In addition, the adjusted R2 for the quadratic model was 0.9045. Compared to other parameters, AR 114 dye concentration is the most important. The adsorption capacity is best at pH=11. The pseudo-first-order describes the kinetic adsorption. The adsorption capacity increases with temperature. Experimental data are well illustrated by Langmuir-Freundlich and Baudu models. The process of AR 114 adsorption on bentonite is spontaneous, endothermic, and disordered. The statistical physical model results show that AR 114 adsorbs on the surface in a nonparallel orientation. Furthermore, the adsorption energy in the systems is 3.07 kJ/mol, indicating physical adsorption. The dye's adsorption efficiency fell from 244 to 173 mg/g after five adsorption/desorption cycles. In summary, this investigation showed that bentonite exhibits great potential as a suitable sorbent in the elimination of AR 114 dye from aqueous solutions.

In this study, ultrasound extraction technology was used to extract the active constituents of pomegranate (Punica granatum L. variety SisheKape-Saveh). The effects of independent variables such as ultrasound exposure time and temperature on extraction yield, anthocyanin content, TPC, EC50, and FRAP were examined using the response surface technique. The extraction and measurement of various polyphenols from agricultural pomegranate waste is a precious source. Encapsulating this compound is also a practical idea to preserve its unique properties during storage. To achieve this goal, the extraction conditions of antioxidants from pomegranate waste were optimized and the physical properties of a nanostructured lipid carrier with wall materials were evaluated. Furthermore, the impact of the resulting nanostructures on the oxidative stability of soybean oil was examined through the measurement of peroxide. According to the approximation of the desired functions, the optimal conditions were 39.8 min and 63.4 °C. Under these conditions, the extraction yield, anthocyanin content, TPC, EC50, and FRAP were measured to be 17.12%, 39.74 mg/L, 41.45 mg GA/mL, 5.55 mg/mL, and 2227 μmol Fe2+/L, respectively. The experimental values agreed well with the predicted values. From the results, the size of the resulting nanoparticles ranged from 82.6 to 196.7 nm. Nanocarriers that contained pomegranate extract exhibited an Encapsulation Efficiency (EE) of 85.2-92.5 %. The highest EE was related to a sample containing 5% pomegranate extract, 4% glycerol distearate, 3% Tween 80, and 0.6% lecithin. This extract at 1000 ppm compared to BHT at 200 ppm could effectively prevent the formation of peroxides in soybean oil.

Kluyveromyces marxianus is a yeast species with various industrial applications. It's known for its ability to metabolize a wide range of substrates, including lactose, xylose, and cellobiose, which makes it useful in various biotechnological processes. In order to Design of Experiment (DOE) and design an optimized method for extracting and purification of mannoprotein using three homogenization, alkalinity, and bio-emulsifier extraction methods, as well as model data at three levels based on three factors: acidity, temperature, and the mannoprotein extraction method, this study looked at the growth of the yeast Kluyveromyces marxianus (IBRC-M 30114) in a 30-L fermentor to determine its optimized yield. Mannoprotein was extracted (in 27 runs with 3 parts) using QUALITEK-4 software and the Taguchi method. In the designed stage, various temperatures (25, 30, and 35 °C) and pHs (2, 5, and 7) were used in the homogenization, alkaline, and bio-emulsifier methods. The growth of the yeast K. marxianus in a fermenter (bioreactor) showed that the maximum biomass was obtained from the scale increase inside the reactor. This indicated that the maximum fermentation biomass 34.02 (g/L) was obtained from K. marxianus in 30 h at pH 4.6, 29 °C, 500 rpm, oxygen 19.7, inlet air volume 1 vvm3, and 36.6 DO. The maximum amount of mannoprotein 8.243 (mg 100 m/L) from 10 (g/L) yeast biomass was extracted by the alkaline method with pH 5. In the bio-emulsifier method, the mannoprotein extraction was maximized at pH 7. The homogenization approach fared better than the alkaline method overall in terms of performance. In contrast, the alkaline method outperformed the other two methods homogenization and bioemulsifier in terms of volume or quantity. Mannoproteins play important roles in various biological processes and have several applications in different industries. Mannoproteins have potential applications in drug delivery and as carriers for bioactive compounds due to their biocompatibility and ability to interact with cells and tissues.

The purpose of the current study is to design and optimize Rosuvastatin calcium orally fast disintegrating tablet (OFDT) with the assistance of an Artificial Neural Network (ANN) based Multi-layer Perceptron (MLP) model. Rosuvastatin calcium is commonly employed as a cholesterol-lowering agent. In our previous work established literature raw material data of OFDTs were collected from 92 research articles, which contain compositional and evaluation parameters and the data trained with Machine learning techniques (ML) to evaluate the optimal ingredients which helps further to develop and optimize Rosuvastatin calcium OFDTs using ANN based MLP. Rosuvastatin calcium OFDTs were formulated according to a 32-factorial design (randomized Box-Behnken method), and formulations were compressed using the direct compression method with varying compositions of superdisintegrant (Crospovidone) 2-4% binder microcrystalline cellulose (MCC) 5-20%, Mannitol as a diluent, magnesium stearate (Mg st) as a lubricant, and talc (1-3%) as a glidant. The developed formulations were assessed to determine their thickness, hardness, friability, disintegration time, and drug content. ANN was used for optimization, and the MLP model was trained using experimental data until a satisfactory R2 of 0.99 and normalized root mean square error (NRMSE) of 0.024 was reached. The compressed tablets (F19) exceeded the desired criteria in terms of thickness (2.6mm), hardness (2.8 kg), friability (0.6%), drug content (99%), and disintegration time (36 sec). The potential use of ANN in pharmaceutical formulation optimization to achieve desired performance characteristics is demonstrated by this work. This study shows the efficacy of ANN with MLP in the development of Rosuvastatin calcium OFDTs.

The effects of Dielectric Barrier Discharge (DBD) on crystal-sugar contaminated with Geobacillus  stearothermophilus   and Aspergillus niger was studied with combined variables of power (5–15 w), time (2-10 min), and voltage (15-22 kV). The total microbial loads of Gs (9×105) and An (9×104 CFU/g) loads were destructed (P ≤ 0.05) when the voltage and power were 22 Kv and ≥ 5 W. Additionally, their death values (D) were equal and below 1.18 min, respectively. Results showed that increasing voltage had at least 70% more effects on Gs sterilization than the time and power of DBD. Although the cold plasma has substantial destructive effects on the  cell membranes, DNA, and protein of microrganisms, Scanning Electron Microscopy (SEM) of A. niger,  and G.  stearothermophilus confirmed the disinfection process by changes happened in their sizes, configurations, and spores due to the cold plasma process. The DBD method (a non-thermal procedure) can be applied as a new antimicrobial practice to fully sterilized the purified crystal sugar and make it completely appropriate for pharmaceutical and baby food industry.

An accurate and standardized diagnosis is needed to detect microbial resistance and changes in an organism's genome. The main problems faced in detecting Mycobacterium tuberculosis from clinical samples are the quality of the primers and the specificity of a gene target. This study aims to determine the main characteristics when evaluating primers’ s fitness generated from in silico experiments using Thermo Fisher Scientific® software and optimization efforts to increase sensitivity to clinical samples, this study also objectively evaluates the potential of atpE as a detection target for MTB using sputum specimens from a clinical setting. A total of 25 clinical samples from pulmonary tuberculosis patients were extracted using the Zymo DNA Extraction® kit and 11 of them were also extracted using the boiling method. DNA isolates were tested for concentration and purity with Nanodrops®. The primer was designed using the open-access software Thermo Fisher Scientific Oligo Primer design tool ®. Reference primer of atpE was obtained from previous research in vitro. Primary validation was carried out using gel electrophoresis. The ROC curve analysis was carried out with GraphPad Prism version 8.4. The atpE primers designed with Thermo Fisher Scientific® showed a 100% detection rate against the positive control bacterial DNA of Mycobacterium tuberculosis H37Rv. The overall atpE primers from Thermo Fisher Scientific® had a sensitivity of 61.54% and a specificity of 100% compared to the reference primers against the clinical sample. In summary, the atpE gene is a good candidate for both species and drug-resistance genes targeted for PCR and genotype profiling in M. tuberculosis.

In a wind farm, the wake interference between wind turbines particularly upstream and downstream turbines is the main issue that leads to identifying the optimum configuration of the turbines. The two-dimensional CFD simulations of a solo wind turbine and turbine cluster were performed to determine turbine configurations that could boost the efficiency of wind farms. The efficiency of a turbine cluster is examined by arranging the two downstream turbines in eight relative positions to the upstream turbine in a V-shaped layout. The Kriging optimization technique was based on 8 design parameters that suggested optimum layout resulting in 21.96% augmentation in the cluster's average efficiency compared to the power coefficient (Cp) of a solo turbine. Furthermore, the optimum rotational direction of the downstream turbines in the optimized layout was examined through 4 sets of arrangements and it was revealed that the optimal rotational direction for the upstream turbine and the lower downstream turbine are clockwise rotating, whereas the best rotational direction for the upper downstream turbine is counterclockwise rotating. By analyzing the efficiency of five and seven turbine clusters at the optimum position, it was determined that the clusters of five and seven turbines, improve the average Cp by 22.6%, and 23.03%, respectively. Finally, the result of the HOMER-based economic analysis demonstrates that a 7-turbine cluster with more electrical production and lower Net Present Cost (NPC) than a 5-turbine cluster can be employed to meet the site load demand.

Considering the limitations of energy consumption and the increasing problems of pollution from low-quality fossil fuels and the need to increase the quality of these fuels by using oxygen additives such as Ethyl tert-butyl ether (ETBE) for their combustion, reviewing and optimizing the production processes of oxygen additives is of great importance. The goal of this study is to simulate-optimize the ETBE production which is used as an oxygenate gasoline additive in the production of gasoline from crude oil. The feed for the ETBE unit comprised two flows of hydrocarbon and ethanol. The Soave-Redlich-Kwong (SRK) equation of state for the vapor phase and the UNIQUAC activity coefficient model for the liquid phase have been used. In this work, at first, the reactive distillation process was simulated by HYSYS software for producing ETBE. Then, the coding was written using MATLAB software and the Genetic algorithm (GA). Both software have been linked simultaneously and the later optimization data was transferred and compared with HYSYS data. The objective function was reflected as the total annual income of ETBE production. The parameters of the objective function were optimized by GA. Optimization was made on decision variables of the objective function which included the output stream temperature of the heater (Tho), input stream temperature of the reactive distillation tower (Tti), output stream temperature of the cooler (Tco), and input stream feed pressure of the distillation tower (Pti). The results of GA optimization show that reboiler duty decreases by 10% as well as total annual profit increases by 15%. Additionally, the comparison of the present work with the findings of researchers reveals a good agreement.

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.

Ni / SiO2 heterogeneous nano catalyst was synthesized and characterized using different analytical tools including FT-IR, UV spectrophotometer, SEM equipped with an energy dispersive X-ray spectrometer (EDX), and XRD. The synthesized catalyst was used in the transesterification of methyl ester produced from mahogany seed oil. The reaction conditions for the transesterification process were optimized. The yield of 85% was achieved when the reaction was carried using Ni / SiO2 with concentration of 1.5% wt, volume ratio of methanol to oil of 5:1, reaction temperature of 60 °C, and a reaction time of 120 min. The Ni / SiO2 nano catalyst was regenerated from the mixture and was reused for various circles by applying the optimum conditions obtained during the present study. The results showed that the methyl ester yield decreased exponentially by increasing the cycle number when the regenerated catalyst was used. However, good conversion (>72%) was obtained up to the 4th cycles. It could be concluded that Ni / SiO2 nano catalyst is catalytically active and may serve as a potential catalyst for biodiesel production.

The extraction of keratin from natural feathers has been studied for its use in various cosmetics and drug delivery applications. There are various reducing agents to dissolve the hard keratin such as sodium dodecyl sulfate and 2-mercaptoethanol, in the present work, a novel extraction methodhas been developed using sodium sulphite, sodium bisulphite, and sodium dodecyl sulfate in the presence of urea, 2-mercaptoethanol, Ethylenediaminetetraacetic acid (EDTA), and thiourea. To increase extraction yield, the weight of feathers, time of incubation, pH, and temperature were investigated using a Central Composite Design and Mixture plan for Optimization. With the present process, we evaluated the apport of keratin treatment and extraction techniques utilizing sodium sulphite, sodium bisulphite, and sodium dodecyl sulfate in the presence of urea, 2-mercaptoethanol, Ethylenediaminetetraacetic acid (EDTA), and thiourea. The percentage yield and keratin concentration were measured using UV-Vis absorbance, Bradford, and Biuret assays. Then, the protein profile and their functional groups were characterized using Sodium Dodecyl Sulfate-Polyacrylamide Gel Electrophoresis (SDS-PAGE) and Fourier Transform Infrared Spectroscopy (FTIR). The purpose was to compare the different procedures in terms of keratin protein quality and quantity, as well as their cost-effectiveness, and to determine the optimum conditions for the keratin extraction process. The results proved that the yield of white chicken feathers keratin (81.2 %) increased using sodium sulphite (1M), sodium bisulphite (0.1 M), and Sodium Dodecyl Sulfate (0.1 M).  The highest protein production was measured at 80°C in 10 h with 5 g of feathers at pH 10. This process of keratin extraction can be used from the laboratory to industrial production with high recoverability and stable properties.

The plant-based extract can be used to synthesize silver nanoparticles (Ag NPs) as a reducing agent. In the present study, Oregano leaves’ extracts were extracted using ethanol to synthesize Ag NPs. The effects of different parameters such as the processing time, temperature, and stirring rate on the mean particle size, concentration, and zeta potential of the synthesized Ag NPs solutions were optimized using Response Surface Methodology (RSM). At the optimum condition, which includes processing time (30.48 min), temperature (70 ºC), and stirring rate (370.530 RPM), Ag NPs were obtained with 33 nm of the mean particle size, 76.109 ppm of concentration, and +17.2 mV of zeta-potential. In this condition, Ag NPs displayed high antibacterial activity against Gram-negative and Gram-positive bacteria. In addition, the maximum antioxidant activity of 11.7% was obtained at optimum synthesizing conditions.