Box-Behnken Design Methodology Research Articles

Preparation and Optimization of Gemcitabine Loaded PLGA Nanoparticle Using Box-Behnken Design for Targeting to Brain: In Vitro Characterization, Cytotoxicity and Apoptosis Study

Background: Treatment of glioma with conventional approaches remains a far-reaching target to provide the desired outcome. This study aimed to develop and optimize Gemcitabine hydrochloride- loaded PLGA nanoparticles (GNPs) using the Box-Behnken design methodology. The independent variables chosen for this study included the quantity of Polymer (PLGA) (X1), Tween 80 (X2), and Sonication time (X3), whereas the dependent variables were Particle size (Y1) EE % (Y2) and PDI (Y3). The optimized biodegradable nanoparticles were investigated for their anticancer effectiveness in U87MG human glioblastoma cells in vitro. Method: The formulation process involved two steps. Initially, emulsification was carried out by combining the organic polymer solution with the aqueous surfactant solution. Subsequently, in the second step, the organic solvent was evaporated, resulting in the precipitation of the polymer and the formation of nanoparticles. The quantity of PLGA, Tween 80, and PVA (at a constant concentration) was adjusted based on the experimental trial approach. Subsequently, the PLGA-based nanoparticles underwent characterization, wherein their particle size, encapsulation efficiency, polydispersity index (PDI), and cumulative release were assessed. The optimal formulation composition was determined as 200 mg of PLGA, 4 ml of Tween 80, and 2 mg of PVA. Further, the optimized GNPs were evaluated for their anti-cancer effectiveness on U87 MG cells by MTT and apoptosis assay. Results: The results demonstrated that the optimized GNPs exhibited an encapsulation efficiency of 81.66 %, a particle size of 140.1 nm, and a PDI of 0.37. The morphology of the Opt-GNPs was observed to be spherical through transmission electron microscopy (TEM). Conclusion: The Apoptosis study further confirmed the observations of MTT assay as the Opt- GNPs significantly enhanced the apoptosis in U-87 MG cells than the Standard marketed formulation.

ADVANCING TOPICAL POSACONAZOLE DELIVERY: BOX BEHNKEN DESIGN MICROSPONGE HYDROGEL OPTIMIZATION AND EXTENSIVE IN VIVO INVESTIGATION

Objective: The primary aim of this study was to develop a novel hydrogel formulation containing Posaconazole (PCZ) encapsulated within microsponges. Furthermore, the study aimed to assess the permeation properties of this formulation in vivo using a mouse model. Methods: To achieve this aim, a series of seventeen trials were conducted using the Box Behnken Design methodology. These trials were designed to optimize the production of PCZ Microsponges (PCZ MS), which were subsequently incorporated into a hydrogel matrix. Skin permeation studies were then performed to evaluate the ability of the PCZ microsponge-based hydrogel to deliver the drug across the skin barrier. These studies involved comparison with a standard hydrogel formulation lacking microsponges. Results: This study assessed the efficacy of microsponge gel formulation PM-3 for drug entrapment, yield, and sustained release compared to a conventional gel. PM-3 displayed the highest entrapment efficiency of 98.5% and a yield of 95.62%, indicating a direct correlation with the 1:1 drug-polymer ratio. Moreover, PM-3 exhibited sustained drug release over 12 h, releasing 83.82% of PCZ compared to 65.31% with the normal gel, suggesting its potential for prolonged therapeutic action. These findings underscore the promise of microsponge-based hydrogels, like PM-3, in enhancing therapeutic outcomes through sustained drug release, warranting further exploration for clinical applications. Conclusion: The findings of this study highlight the promising potential of microsponge-based hydrogels as effective carriers for localized drug delivery, particularly in the context of treating skin fungal infections.

Locally Acting Budesonide-Loaded Solid Self-Microemulsifying Drug Delivery Systems (SMEDDS) for Distal Ulcerative Colitis.

Budesonide (BUD) is a BCS class II medication with poor water solubility and limited oral bioavailability. In this study, innovative solid self-microemulsifying drug delivery systems (BUD-SMEDDS) were developed for effective local management of distal ulcerative colitis (UC). Based on solubility and emulsification tests, the components of the self-microemulsifying drug delivery system (SMEDDS) were Capryol™ 90, Tween 80, and Transcutol HP. The impacts of BUD-SMEDDS ingredients (as inputs) on the average globule size (AGS), polydispersity index (PDI), and self-emulsification time (SET) as responses were investigated using the Box-Behnken design methodology. Solid rectal systems were then fabricated using the optimized values of SMEDDS components in Lutrol® bases. The developed systems were evaluated for in vitro characteristics and in vivo efficacy using a rat colitis model. For all responses, the greatest impact was attributed to the oil content of SMEDDS. An optimized BUD-SMEDDS with AGS of 33 ± 2.9 nm, PDI of 0.29 ± 0.03 and SET of 25 ± 2.5 s) was selected for rectal formulations. The developed formulations demonstrated acceptable physical characteristics and mucoadhesive abilities. Differential scanning calorimetric (DSC) analysis revealed the absence of BUD crystallinity in the SMEDDS formulations. The drug release patterns could be regulated by selecting the grade and composition of the incorporated Lutrols. Clinical and histopathological assessments revealed considerable improvements in animals treated with BUD-SMEDDS formulations. Overall findings confirmed the superior capability of solid SMEDDS as BUD carriers to manage distal colitis in tested animals.

Experimental Design, Statistical Analysis, and Modeling of the Reduction in Methane Emissions from Dam Lake Treatment Using Agro-Industrial Biochar: A New Methane Capture Index

This study aimed to reduce the methane (CH4) emissions originating from dam lake treatment using malt dust-derived biochar, which is an agro-industrial byproduct of the brewery industry. Optimum operating and water quality parameters for CH4 reduction were determined using statistical analyses based on the Box–Behnken design method. Also, a Monte Carlo simulation was performed to determine the correlation between CH4 emissions and operating parameters. According to the simulation, dissolved oxygen (DO) and the oxidation–reduction potential (ORP) had the highest correlation with CH4 emissions, with values of 92.03% and 94.57%, respectively. According to the Box–Behnken design methodology, the optimum operating parameters were 4 mg/L of dissolved oxygen, −359 mV of ORP, and 7.5 pH for the minimum CH4 emissions. There was a reported reduction of up to 19.4% in CH4 emissions for the dam lake treatment using malt dust-derived biochar. Finally, a new methane capture index, based on the biochar application (MCI), was developed and validated. The largest methane capture capacity was related to the malt dust-derived biochar produced at the lowest temperature (M1).

Box-Behnken Design for Mitigation of Cadmium Bivalent Ions from Aqueous Medium.

Statistical analysis is essential for minimizing the time, cost, and number of experiments needed to get the maximum output. In this work, the removal of cadmium bivalent (Cd (II)) ions was optimized using Box-Behnken design methodology. The effects of pH, concentration, time, and temperature were investigated for the removal of cadmium. Maximum removal (85.70 %) was achieved at pH of 5.34, initial Cd(II) ions concentration 46.61,contact time 166.09 (min), and at 59.40 °C temperature on Punica Granatum carpellary membrane powder (PGCMP) and 88.61 % removal was achieved on its modified forms (MPGCMP) at pH of 5.79, initial Cd(II) ions concentration 65.70,contact time 178.96, and at 59.91 °C temperature. The model was validated by analyzing variance (ANOVA). The practical data was well fitted to the quadratic model. PGCMP and MPGCMP were found to be naturally occurring, environmentally friendly adsorbents for the mitigation of Cd (II) ions as well as other toxic heavy metals from drinkable or wastewater.

Intranasal delivery of doxepin: enhancing brain targeting efficiency utilizing nanostructured lipid carriers for a biopharmaceutics drug disposition classification system class-I drug

Doxepin, a Class-I Biopharmaceutics Drug Disposition Classification System (BDDCS) drug, exhibits poor bioavailability due to extensive first-pass metabolism. This research focuses on enhancing the delivery of doxepin by formulating nanostructured lipid carriers (NLCs) through the utilization of the Box–Behnken Design methodology. These optimized NLCs are intended for intranasal administration, with the ultimate goal of improving nose-to-brain drug delivery. NLCs were formulated using a high-speed homogenization technique. The optimized batch had a small particle size (75.80 ± 5.48 nm, PDI = 0.286), high entrapment efficiency (94.10 ± 0.16%), and sustained ex vivo release (82.25 ± 4.61% at 24 h). Characterization studies confirmed the conversion of doxepin from a crystalline to an amorphous state with uniform distribution in the lipid matrix. In vivo pharmacokinetic studies in rats showed significantly higher doxepin concentration in the brain tissue (Cmax = 16.77 µg/g, tmax = 30 min) after intranasal administration compared to intravenous administration (Cmax = 2.53 µg/g, tmax = 6 h). High-drug targeting efficiency (DTE = 284.3%) and direct transport percentage (DTP = 64.8%) suggested direct penetration of NLCs in the brain via olfactory and trigeminal pathways. In conclusion, the study highlights the potential of NLCs to improve the bioavailability of doxepin through nose-to-brain delivery and thereby potentially enable the treatment of neurological disorders.

Optimization and Modeling of a Dual-Chamber Microbial Fuel Cell (DCMFC) for Industrial Wastewater Treatment: A Box–Behnken Design Approach

Microbial fuel cells (MFCs) have garnered significant attention due to their capacity to generate electricity using renewable and carbon-neutral energy sources such as wastewater. Extensive experimental work and modeling techniques have been employed to dissect these processes and understand their respective impacts on electricity generation. The driving force is to enhance MFC performance for practical applications commercially. Among the various statistical modeling approaches, one particularly robust tool is the Design of Experiments (DoE). It serves to establish the relationships between different variables that influence MFC performance and allows for the optimization of the MFC configuration and operation for scaled-up performances in terms of bioelectricity generation. This study focused on optimizing microbial fuel cells (MFCs) for bioelectricity production using industrial wastewater treatment, employing the Box–Behnken design (BBD) methodology. Through an analysis of response surface models and ANOVA tests, it was found that a combined approach of reduced quadratic, reduced two-factor interaction, and linear models yielded sound results, particularly in voltage yield, COD removal, and current density. Second-order regression models predicted optimal conditions for various parameters, with surface area, temperature, and catholyte dosage identified as critical input variables for optimization. Under these conditions, conducted by the four-factor and three-level Box–Behnken design methodology in a double-chamber MFC unit considering eight output variables—CCV yield, % COD removal, current density, power density, % TSS removal, % CE, and % PO43−—the optimum values were 700 mV, 54.4%, 54.4 mA/m2, 73.7 mW/m2, 99%, 21.2%, and 100%, respectively. At optimum operating conditions, the results revealed a desirability of 76.6% out of a total of 92 iterations. The paper highlights the effectiveness of statistical ANOVA fit-statistics modeling and optimization in enhancing DCMFC performance, recommending its use as a sustainable bioenergy source. Furthermore, validation results supported the above optimization output response findings and confirmed the viability of biorefinery wastewater as an anolyte for scaling up DCMFC bioelectricity generation.

Optimization of metals and rare earth elements leaching from spent Ni-MH batteries by response surface methodology

ABSTRACT The rechargeable battery market has almost doubled in 15 years. Regardless of the type of batteries, their limited lifespan means that sooner or later they will constitute a mass of waste whose management is problematic as their content is high in elements and metals of high economic interest, but also toxic to the environment. This project is to optimize the solubilization conditions for rare earth elements (REEs) and other metals from waste nickel-metal hydride (Ni-MH) batteries. The Ni-MH battery powder used contained the following main elements: Ni (548 g/kg), La (45 g/kg), Co (32 g/kg), Zn (22 g/kg), Nd (15 g/kg), Sm (12 g/kg), and Ce (11 g/kg). The metals were solubilized in the presence of sulfuric acid. Acid concentration, solids concentration, leaching time, and temperature were optimized using the Box–Behnken design methodology. The optimal conditions identified are an H2SO4 concentration of 2 M, a S:L ratio of 10% (w:v), a leaching temperature of 60°C and a reaction time of 90 min. These conditions make it possible to solubilize 81% Ni, 99% Co, and 70% REEs, while the mathematical model predicted 83% Ni, 100% Co, and 80% REEs respectively. The process was also operated in counter-current leaching mode with the optimal parameters. The high solubilized yields obtained after five loops for all metals, REE and the significant reduction of water consumption confirm that this process leaching can be apply for industrial application.

An Evaluation of Glycerol Acetalization with Benzaldehyde over a Ferromagnetic Heteropolyacid Catalyst

Tungstophosphoric acid (H3PW12O40) supported on silica-coated magnetite nanoparticles has been prepared and used as a heterogeneous acid catalyst (Fe3O4@SiO2@HPW) in the condensation of benzaldehyde (B) with glycerol (Gly) for the production of cyclic acetals. Physicochemical techniques, including scanning electron microscopy (SEM), transmission electron microscopy (TEM), Fourier-transform infrared spectrometry (FTIR), X-ray diffraction (XRD), thermogravimetric analysis (TGA), and N2 physisorption were used to characterize the prepared catalyst. The effect of glycerol/benzaldehyde molar ratio (1/1 to 1/1.2), temperature (80–120 °C), and catalyst amount (1–5%) on glycerol conversion and the selectivity in main reaction products: benzoic acid, 2-phenyl-1,3-dioxolan-4-yl)methanol, 2-Phenyl-1,3-dioxan-5-ol, 2-phenyl-1,3-dioxolane, and methyl 2-hydroxy-3-phenylpropanoate was studied to evaluate the catalytic activity of the prepared Fe3O4@SiO2@HPW catalyst. The optimization of these process parameters was conducted using Box–Behnken design (BBD). Using the BBD methodology, the optimal parameters (120 °C, 1:1.15 glycerol: benzaldehyde, 5% catalyst) were determined, for a glycerol conversion of and cyclic acetals yield of 85.95% and 78.36%, respectively. The catalyst also exhibits excellent activity for glycerol acetalization with other aromatic aldehydes such as cinnamaldehyde, p-methyl-benzaldehyde, p-hydroxy-benzaldehyde, and vanillin.

Investigation of the mechanical and corrosion properties of Mg-Hydroxyapatite composite by addition of rare-earth oxide particulates for biomedical applications

Magnesium has gained much attention as advanced light-weight material and have been extensively used in orthopedic applications. Its bone-like properties and non-toxic behavior have established it as a splendid bone implant with excellent biodegradability and biocompatibility; however, its corrosion properties have exploited its usage and need to be addressed. The current study emphasized the influence of rare-earth oxide, that is, Neodymium oxide (Nd2O3/NdO) on the mechanical and corrosion properties of Mg-Hydroxyapatite (HAP) composite. In this work, Mg-HAP-xNdO ( x = 1%, 1.5%, and 2%) was fabricated via powder metallurgy route using Box-Behnken design methodology with different sintering temperatures (400°C, 450°C, and 500°C) and sintering time (1, 2, and 3 h). The results showed that the addition of NdO to the composite developed various intermetallic phases such as Mg12Nd and Nd0.5Ca0.5 as analyzed through FESEM, XRD, and EDS techniques, producing refined microstructure. It was formalized that Mg-HAP composites containing 1.5% NdO, sintered at 400°C for 2 h showed the lowest corrosion rates as compared to other samples. Moreover, the secondary β-phase developed provided necessary reinforcement to the Mg-HAP composites and prevented deformation, resulting in improved microhardness (48.50 HV), ultimate compressive (UCS) (116.57 MPa), tensile strength (UTS) (154.23 MPa) at 1.5% NdO (400°C-2 h). In addition, the statistical analysis performed via the ANOVA technique confirmed the experimental results by revealing significant effects of sintering temperature and combination of all the three parameters on the microhardness and compressive strength of the composites. Hence, these findings concluded that the Mg-HAP-NdO composite could be a promising candidate for orthopedic implant applications.

Taguchi method and Box-Behnken design approach for process parameter optimization of magnetite (Fe3O4) coating developed on stainless steel 410 grade by hot alkaline treatment

The blackening of materials is widely used in the automobile industry, defense applications, aerospace applications, and solar applications. Methods such as electroless chemical process, conversion coating, physical vapor deposition, chemical vapor deposition, and diamond-like carbon are some of the commonly employed techniques to produce black coatings on various metals. Hot aqueous alkaline treatment is a chemical conversion coating process. In this study, hot alkaline treatment is used to blacken surgical equipment made of stainless steel 410, which is a novel approach. The effect of process variables such as immersion time, salt solution temperature, and wt% of sodium dichromate on the anti-reflective property of ferrous ferric oxide (magnetite, Fe3O4) coating has been optimized using the Taguchi method and response surface methodology. The experiments were designed using a Taguchi orthogonal array and a Box-Behnken design. The influences of coating parameters on average percentage reflectance were quantified by the signal-to-noise ratio, main effect plot, analysis of variance, and two-dimensional and three-dimensional plots. The comparison of experimental and confirmatory tests shows that both procedures optimized the parameters successfully. The lowest average percentage reflectance value of 8.013% was obtained at 56.976 min immersion time, 124.998°C salt solution temperature, and 348.689 g/l wt% of sodium dichromate in the composition by Box-Behnken design methodology.

Experimental Investigation on the Effect of Laser Welding Parameters for P91 Steel Welding with Varying Shielding Gas Using Box–Behnken Design Methodology

Experimental Investigation on the Effect of Laser Welding Parameters for P91 Steel Welding with Varying Shielding Gas Using Box–Behnken Design Methodology

Optimal Factor Evaluation for the Extraction of Alumina from Clays by Sulfuric Acid Leaching Process Using Box–Behnken Design Methodology

Optimal Factor Evaluation for the Extraction of Alumina from Clays by Sulfuric Acid Leaching Process Using Box–Behnken Design Methodology

A hybrid GA-ANFIS and F-Race tuned harmony search algorithm for Multi-Response optimization of Non-Traditional Machining process

The present study focuses on development of prediction models with respect to various cut quality characteristics such as material removal rate, kerf taper and surface roughness for a well-known non-traditional machining process namely abrasive aqua jet cutting (AAJC) of natural fibre composite laminates through combined taguchi-genetic algorithm (TGA) and adaptive neuro fuzzy inference system (ANFIS). The AAJC experiments are conducted based on box-behnken design methodology by considering jet pressure, stand-off distance, traverse speed and wt% of nano clay inclusion in composites as input parameters. The ANFIS parameters are optimized using a hybrid taguchi-genetic training algorithm. The statistical results of hybrid TGA-ANFIS models shows that they are outperformed in prediction of AAJC parameters when compared with the results of multiple-linear regression models. Further, the optimization of AAJC parameters is carried out using a trained ANFIS network and the F-race tuned harmony search algorithm (HSA). The superlative responses such as MRR of 76.9 g/min, KT of 2.23° and Ra of 3.17 µm are forecasted at the optimum cutting conditions such as jet pressure of 303.08 MPa, stand-off distance of 2.16 mm, traverse speed of 375.64 mm/min, and nano clay wt% of 1.27, respectively. The experimental results show that the error between predicted and actual results are lower than 6%, indicating the feasibility of adopting the proposed F-race parametric tuned HSA in optimization of AAJC process.

Statistical Modeling and Optimization of Reducing Sugar Production for Enzymatic Digestibility of Bamboo Grass by Box-Behnken Design Methodology

Bamboo plants are plants that can grow quickly and easily, and is an abundant and renewable resource plants analogous to deciduous tree and conifer. In this study, bamboo species of Yushania alpina was pretreated with sodium hydroxide (NaOH) and hydrolyzed by dilute sulfuric acid to produce reducing sugar. Phenol-sulphur acid method was used to determine the response. Seventeen experimental runs were carried out at temperature range (110-128oC), concentration of H2SO4 range of (1-7%) and residence time range of (30-60 min) respectively. The effect of the parameters was measured by concentration of reducing sugar produced for each, and the optimization of glucose production was done by using Box-Behnken design methodology. The results reveal that, the temperature, concentration and time significantly affected the glucose production. At range of low temperature, concentration and time, the yield was decreased while at high value of factors the yield of reducing sugar increased. At 113.17oC, 3.43wt%, 33.65min and desirability of 0.71 the optimum reducing sugar of 19.9 found.

Effect of co-liquefaction of lignin and laminaria saccharina on optimization of bio-oil yield

• Co-liquefaction of Laminaria saccharina with lignin is studied. • The synergistic effect is negative in most mild and lignin-rich conditions. • The synergistic effect is positive in severe and lignin-poor conditions. • Residence time showed an impact on bio-oil quality. • Co-liquefaction synergistically enhanced the bio-oil quality at specific conditions. Hydrothermal liquefaction (HTL) is a valuable technology to convert and use wet biomass feedstocks. Lignin, waste from the paper industry and the main component of lignocellulosic biomass, is co-liquefied with laminaria saccharina, a commonly available seaweed in Norway. The aim is to conduct statistical analysis and investigate the possibility of increasing bio-oil yield while lowering the char yield through a synergistic effect. The bio-oil and char yields are measured with different operating temperatures, residence times, and blending ratios (mass ratio of laminaria saccharina to the total mass) to find out the optimized process conditions for better outputs statistically. Response surface methodology (RSM) with a Box Behnken design methodology is used to optimize the liquefaction yields of laminaria saccharina, lignin, and the different blends of the two biomasses. The results explicitly revealed that the biomass blend's optimal bio-oil and char yields are 0.2513 (w/w 0 ) and 0.1791 (w/w 0 ) respectively at 573 K, 20 min with the blending mass ratio of 0.2. The synergistic effects on the bio-oil yield are detected at comparatively severe reaction conditions. According to the RSM, residence time does not affect bio-oil and char yields as much as the operating temperature and the blending ratio. Nevertheless, temperature, residence time, and blending ratio have different impacts on the functional groups. The temperature increase has helped increase the alcohol and phenolic compounds production while the residence time consumes the C-O bonds. The increase of laminaria saccharina mass ratio in the feedstock has improved the phenolic compounds, long-chain aliphatic hydrocarbons, carboxylic acids, ketones, aldehydes, and esters in the bio-oils. Co-liqueafctio has produced bio-oil with significantly lower N content than from bio-oil produced from laminaria saccharina liquefaction.

Effective Pretreatment of Corn Straw Biomass Using Hydrothermal Carbonization for Co-Gasification with Coal: Response Surface Methodology–Box Behnken Design

Effective Pretreatment of Corn Straw Biomass Using Hydrothermal Carbonization for Co-Gasification with Coal: Response Surface Methodology–Box Behnken Design

A switch-on xanthene-triphenylamine based fluorescent and colorimetric sensor for the detection of ultra-trace Hg2+ in food samples and living cells

A novel colorimetric and fluorescent “switch-on” probe based on xanthene-triphenylamine was developed for detection of Hg2+, which threatens public health, food safety and the environment. The probe displayed superior colorimetric and fluorescent selectivity/sensitivity toward Hg2+ over a series of metal ions via Hg2+-triggered deprotection reaction. Hg2+ induced a ∼18-fold enhancement in emission intensity of probe TXS with yellow fluorescence (λem = 558 nm) and led to distinct color transition from light yellow to blue or yellow under daylight depending on solvent mixture. Detection parameters were optimized and examined for the influence that they exerted on the detection which involved the usage of the Box-Behnken design methodology. The sensing pathway was also examined theoretically by DFT and TD-DFT calculations. The probe was successfully utilized for the detection of Hg2+ in several food and water samples with good recoveries. Cell imaging studies demonstrated that the probe was suitable for Hg2+ detection in live cells.

Application of Box-Behnken Design for Ultrasonic-assisted Extraction of Glycyrrhiza Polysaccharide and Antioxidant Activity Analysis

In the present paper, Glycyrrhiza was selected as raw materials, and ultrasonic-assisted water bath extraction method was used to investigate crushed particle size, liquid-material ratio, ultrasonic temperature and ultrasonic time. The ultrasonic-assisted extraction technology of polysaccharide from Glycyrrhiza was optimized by Box-Behnken design methodology and the quadratic polynomial regression equation of the prediction model was established, then the antioxidant activity of the polysaccharide in vitro was determined. According to the model regression analysis, the optimum conditions were as follows: particle size of 127 μm, liquid-material ratio of 19.32 mL/g, ultrasonic temperature of 65 ℃ and ultrasonic time of 30.2 min. Under these conditions, the yield of polysaccharide reached 10.867%. Glycyrrhiza polysaccharide showed ability to scavenge both DPPH· and ABTS+· with IC50 values of 2.80 mg/mL and 1.96 mg/mL, respectively, and there was a certain dose-effect relationship between the scavenging rate of two different free radicals and the concentration of crude polysaccharide extract. The model established in this study can analyze and predict the yield of Glycyrrhiza polysaccharide to determine the natural antioxidant activity, which can provide an experimental basis for the development and utilization of Glycyrrhiza resources.

Bio-Synthesized Silver Nanoparticles For Effective Photo- catalytic Degradation of Congo Red Dye in Aqueous Solutions: Optimization Studies Using Response Surface Methodology

The focus of the project is the new, low cost and simple nature mediated formation of silver nanoparticles (Ag-NPs) using leaf extract of Anisomeles malabarica. The shape and size, structure, element composition, and functional groups of green synthetic Ag-NPs have been studied by scanning electron microscopy (SEM), X-ray diffraction (XRD), energy dispersive X-ray (EDX), and Fourier Transform Infrared (FTIR), respectively. BET analysis has been used to calculate the specific surface area of the particles, and GC- MS analysis has been used to confirm the presence of biologically active components in leaf extracts. Based on the observed results, the possible formation mechanism of AgNPs has been given. The obtained Ag-NPs have the physical property of spherical shape and nature of crystallinity, with an average size of about 63 nm. Ag- NPs have shown promising potential in the removal of organic pollutants Congo red (CR) dyes. Dye removal as a function of contact time has also been carefully studied. The experimental value of the dye degradation study was fitted with a first-order linear kinetic model to understand the reaction rate. The response surface methodology is used to study the effect of catalyst concentration, dye concentration, and irradiation time on the percentage of dye degradation and process optimization based on Box-Behnken Design Methodology (RSM). The result of the RSM model value R2 = 99.97 % gives a satisfactory correlation between the experimental and predicted value for dye removal. After 15 minutes of reaction time, maximum degradation of 99.97 % was achieved under optimal conditions (1 mM dye concentration, 1 mg photocatalyst concentration). Therefore, we were able to produce the photocatalyst using Anisomeles malabarica leaf extract that can degrade azo dyes.