The Influence of Tartaric Acid in the Silver Nanoparticle Synthesis Using Response Surface Methodology

Silver nanoparticles(AgNPs)synthesized using tartaric acid as a capping agent have a great impact on the reaction kinetics and contribute significantly to the stability of AgNPs.The protective layer formed by tartaric acid is an important factor that protects the silver surface and reduces potential cytotoxicity problems.These attributes are critical for assessing the compatibility of AgNPs with biological systems and making them suitable for drug delivery applications.The aim of this research is to conduct a comprehensive study of the effect of tartaric acid concentration,sonication time and temperature on the formation of silver nanoparticles.Using Response Surface Methodology(RSM)with Face-Centered Central Composite Design(FCCD),the optimization process identifies the most favorable synthesis conditions.UV-Vis spectrum regression analysis shows that AgNPs stabilized with tartaric acid are more stable than AgNPs without tartaric acid.This highlights the increased stability that tartaric acid provides in AgNP ssssynthesis.Particle size distribution analysis showed a multimodal distribution for AgNPs with tartaric acid and showed the smallest size peak with an average size of 20.53 nm.The second peak with increasing intensity shows a dominant average size of 108.8 nm accompanied by one standard deviation of 4.225 nm and a zeta potential of−11.08 mV.In contrast,AgNPs synthesized with polyvinylpyrrolidone(PVP)showed a unimodal particle distribution with an average particle size of 81.62 nm and a zeta potential of−2.96 mV.The more negative zeta potential of AgNP-tartaric acid indicates its increased stability.Evaluation of antibacterial activity showed that AgNPs stabilized with tartaric acid showed better performance against E.coli and B.subtilis bacteria compared with AgNPs-PVP.In summary,this study highlights the potential of tartaric acid in AgNP synthesis and suggests an avenue for the development of stable AgNPs with versatile applications.

Optimizing Bucket Elevator Performance through a Blend of Discrete Element Method, Response Surface Methodology, and Firefly Algorithm Approaches

This research introduces a novel approach to enhancing bucket elevator design and operation through the integration of discrete element method(DEM)simulation,design of experiments(DOE),and metaheuristic optimization algorithms.Specifically,the study employs the firefly algorithm(FA),a metaheuristic optimization technique,to optimize bucket elevator parameters for maximizing transport mass and mass flow rate discharge of granular materials under specified working conditions.The experimental methodology involves several key steps:screening experiments to identify significant factors affecting bucket elevator operation,central composite design(CCD)experiments to further explore these factors,and response surface methodology(RSM)to create predictive models for transport mass and mass flow rate discharge.The FA algorithm is then applied to optimize these models,and the results are validated through simulation and empirical experiments.The study validates the optimized parameters through simulation and empirical experiments,comparing results with DEM simulation.The outcomes demonstrate the effectiveness of the FA algorithm in identifying optimal bucket parameters,showcasing less than 10%and 15%deviation for transport mass and mass flow rate discharge,respectively,between predicted and actual values.Overall,this research provides insights into the critical factors influencing bucket elevator operation and offers a systematic methodology for optimizing bucket parameters,contributing to more efficient material handling in various industrial applications.

Optimization of Preparation of Oregano Oil Microspheres by Box-Behnken Response Surface Methodology

[Objectives]To optimize the formulation and preparation of oregano oil microspheres by Box-Behnken response surface methodology.[Methods]Chitosan was used as the carrier material to prepare oregano oil microspheres by emulsion crosslinking method.The encapsulation efficiency,drug loading and ID 50 were used as the evaluation indicators,and the comprehensive score(OD)obtained by"coefficient of variation-AHP comprehensive weighting method"was used as the final evaluation indicator.The formulation design and preparation process were optimized by single factor experiment and Box-Behnken response surface methodology,and the optimal process parameters were determined.[Results]The optimal formulation and preparation process parameters of oregano oil microspheres were as follows:the ratio of oregano oil to chitosan was 2∶1,the emulsifying speed of double emulsion was 200 r/min,the amount of emulsifier in the colostrum was 4%,and the volume of curing agent was 1.0 mL.The average encapsulation efficiency was 45.33%±1.32%,the average drug loading was 30.59%±2.45%,and the median diameter(ID 50)was 52.596μm±0.023%.[Conclusions]The encapsulation efficiency,drug loading and ID 50 of oregano oil chitosan microspheres prepared by emulsion crosslinking method met the requirements.The drug-loaded microsphere not only can be used as a preparation finished product for direct application,but also be used as a product intermediate to lay a foundation for the research and development of subsequent dosage forms.

Optimization of Methylene Blue Dye Adsorption onto Coconut Husk Cellulose Using Response Surface Methodology: Adsorption Kinetics, Isotherms and Reusability Studies

In this study, coconut husk cellulose was employed as a cost-effective and environmentally friendly adsorbent to eliminate methylene blue (MB) dye from aqueous solutions. The successful development of response surface methodology paired with a central composite design (RSM-CCD) enabled the optimization and modelling of the adsorption process. The study investigated the individual and combined effects of three variables (pH, contact time, and initial MB dye concentration) on the adsorption of MB dye onto coconut husk cellulose. The developed RSM-CCD model exhibited a remarkable degree of precision in predicting the removal efficiency of MB dye within the specified experimental parameters. This was demonstrated by the strong regression parameters, with an R2 value of 99.79% and an adjusted R2 value of 99.6%. The study depicted that the optimal parameters for attaining a 98.8827% removal of MB dye using coconut husk cellulose were as follows: an initial MB dye concentration of 30 mg∙L−1, contact time of 120 minutes, and pH 7 at a fixed adsorbent dose of 0.5 g. The Freundlich isotherm model provided the most satisfactory description of the equilibrium adsorption isotherms, suggesting that MB dye adsorption onto coconut husk cellulose occurs on a heterogeneous surface. The experimental results demonstrated a strong agreement with the pseudo-second-order kinetics model, indicating that the number of active sites present on the cellulose adsorbent predominantly influences the adsorption process of MB dye. Additionally, the adsorbent made from coconut husk cellulose exhibited the potential to be reused, as it retained its efficiency for a maximum of three cycles of adsorption of MB dye. The results of this study show that coconut husk cellulose has the potential to be an effective and sustainable adsorbent for removing MB dye from aqueous solutions.

Optimization of Cellulose Nanocrystal Isolation from Ayous Sawdust Using Response Surface Methodology

This study focuses on the extraction of cellulose nanocrystals (CNC), from microcrystalline cellulose (MCC), derived from Ayous sawdust. The process involves multiple steps and a large amount of chemical products. The objective of this research was to determine the effects of factors that impact the isolation process and to identify the optimal conditions for CNC isolation by using the response surface methodology. The factors that varied during the process were the quantity of MCC, the concentration of sulfuric acid, the hydrolysis time and temperature, and the ultrasonic treatment time. The response measured was the yield. The study found that with 5.80 g of microcrystalline cellulose, a sulfuric acid concentration of 63.50% (w/w), a hydrolysis time of 53 minutes, a hydrolysis temperature of 69˚C, and a sonication time of 19 minutes are the ideal conditions for isolation. The experimental yield achieved was (37.84 ± 0.99) %. The main factors influencing the process were the sulfuric acid concentration, hydrolysis time and temperature, with a significant influence (p < 0.05). Infrared characterization results showed that nanocrystals were indeed isolated. With a crystallinity of 35.23 and 79.74, respectively, for Ayous wood fiber and nanocrystalline cellulose were observed by X-ray diffraction, with the formation of type II cellulose, thermodynamically more stable than native cellulose type I.

Effects of main ecological factors on the growth of marine green alga Caulerpa sertularioides using the response surface methodology

Caulerpa sertularioides is an invasive potential blooming green alga in China but it remains poorly studied.We studied the effects of ecological factors on its growth.Optimum conditions of ecological factors,i.e.,irradiance,temperature,and salinity,for the growth of its fragments were determined in the response surface methodology(RSM).The specific growth rates(SGR)of the fragments were determined in single-factor experiment.The results show that the SGR of C.sertularioides peaked under the conditions of irradiance 37.5μmol/(m~2·s),temperature25℃,and salinity 30.Meanwhile,using the Box-Behnken design,the conditions were further optimized and verified to be:irradiance 39.03μmol/(m~2·s),temperature 25.29℃,and salinity 30.06,under which the SGR reached 4.66%.The results provide new theoretical data and solutions for the cultivation,invasion prediction,and monitoring of Caulerpa species in China and the world.The RSM method may have great potential applications in the environmental adaptation characteristics of new macroalgal cultivars,intensive orientation cultured germplasm,and environmental hazard analysis of cultivated species in the field.

Optimization of Mortar Compressive Strength Prepared with Waste Glass Aggregate and Coir Fiber Addition Using Response Surface Methodology

Waste Glass(WGs)and Coir Fiber(CF)are not widely utilized,even though their silica and cellulose content can be used to create construction materials.This study aimed to optimize mortar compressive strength using Response Surface Methodology(RSM).The Central Composite Design(CCD)was applied to determine the optimization of WGs and CF addition to the mortar compressive strength.Compressive strength and microstructure testing with Scanning Electron Microscope(SEM),Fourier-transform Infrared Spectroscopy(FT-IR),and X-Ray Diffraction(XRD)were conducted to specify the mechanical ability and bonding between the matrix,CF,and WGs.The results showed that the chemical treatment of CF produced 49.15%cellulose,with an average particle size of 1521μm.The regression of a second-order polynomial model yielded an optimum composition consisting of 12.776%WGs and 2.344%CF with a predicted compressive strength of 19.1023 MPa.C-S-H gels were identified in the mortars due to the dissolving of SiO_(2) in WGs and cement.The silica from WGs increased the C-S-H phase.CF plays a role in preventing,bridging,and branching micro-cracks before reaching maximum stress.WGs aggregates and chemically treated CF are suitable to be composited in mortar to increase compressive strength.

Response Surface Methodology as an Approach for Optimization of Vinegar Fermentation Conditions Using Three Different Thermotolerant Acetic Acid Bacteria

This study aimed to investigate optimal fermentation conditions of biological acetic acid fermentation for vinegar production. Optimization was performed on 3 acetic acid bacteria strains namely VMA1, VMA7 and VMAO using Response Surface Methodology (RSM). A Box-Behnken-Design (BBD) was achieved with three different independent process parameters involving: fermentation temperature, original alcohol concentration and original acetic acid concentration and one dependent variable (acetic acid yield). The results showed that the mathematical models describe correctly the relationship between responses and factors (F values of the models (p R2 (coefficient of correlation) respectively 0.96, 0.94, 0.98, and adjusted R2 0.95, 0.92, 0.98). The maximum acidity was obtained respectively at fermentation temperatures, original alcohol concentrations and original acetic acid concentrations ranging from [37.5°C - 45°C], [16% - 20% (v/v)], [1.5% - 2% (w/v)] for VMA1, [40°C - 45°C], [14.5% - 20% (v/v)], [1.7% - 2% (w/v)] for VMA7 and [42°C - 45°C], [17% - 20% (v/v)], [1.5% - 2% (w/v)] for VMAO. The use of these acetic strains in the production of vinegar may seriously lead to a decrease or even an ablation of the costs related to the cooling of bioreactors especially in warm and hot countries, in the context of global warming.

Response Surface Methodology-Based SERS for Determination of Gymnodimine

Gymnodimine (GYM), a fast-acting marine toxin, is destructive to aquaculture and human health through contaminated shellfish. The current detection methods in GYM have definite drawbacks in operation, such as the demand for delicate instruments and the consumption of time. Therefore, silver colloid was utilized as a surface-enhanced Raman scattering (SERS) desirable substrate for sensitive and rapid detection of GYM in lake and shellfish samples. The theoretical spectrum of GYM is calculated by density functional theory (DFT), and the substrate performance is evaluated by a rhodamine 6 G probe. Under the optimal SERS experimental condition calculated by the response surface methodology, the low limit of detection of 0.105 μM with R2 of 0.9873 and a broad linearity range of 0.1 - 10 μM was achieved for GYM detection. In addition, the substrate was satisfyingly applied to detect gymnodimine in the lake and shellfish matrix samples with LOD as low as 0.148 μM and 0.170 μM, respectively. These results demonstrated a promising SERS platform for detecting marine toxins in seafood for food safety and pharmaceutical research.

Optimization of Preparation Conditions of Modified Oyster Shell Powder/Ce-N-TiO2 by Response Surface Methodology (RSM)

A new composite photocatalyst of modified oyster shell powder/Ce-N-TiO2 was prepared by sol-gel method. Based on single factor experiment, Ce doping rate, N doping rate and calcination temperature were taken as input variables. Based on the central composite design (BBD) response surface model, two functional relationship models between three independent variables and glyphosate removal rate were established to evaluate the influence degree of independent variables and interaction on catalyst. The significance of the model and regression coefficient was tested by variance analysis. The analysis of the obtained data showed that the degradation performance of the composite photocatalyst was significantly affected by the calcination temperature and the rate of N doping, while the rate of Ce doping had little effect;at the calcination temperature of 505.440°C, the degradation rate of glyphosate reached the maximum of 82.15% under the preparation conditions of 17.057 mol% N doping and 0.165 mol% Ce doping, respectively.

Optimization for Microbial Degumming of Ramie with Bacillus subtilis DZ_(5) in Submerged Fermentation by Orthogonal Array Design and Response Surface Methodology

As a kind of natural fiber,ramie fiber has distinctive advantages in textile application,but the application is limited due to the traditional degumming mode.Compared with the traditional degumming process,the microbial degumming process has many advantages.To obtain the optimal conditions for degumming ramie with Bacillus subtilis DZ_(5)(BS DZ_(5)),a combined statistical approach of orthogonal array design(OAD)and response surface methodology(RSM)was used.The influences of initial pH of the bacteria medium,culture temperature,shaking speed,degumming time and inoculum size on submerged fermentation degumming were evaluated by using fractional factorial design.The main factors in the analysis were culture temperature,shaking speed and initial pH.The residual gum mass fraction was used as the optimization index,and the optimal conditions for degumming were determined by central composite design and RSM.Thus with only a limited number of experiments,an optimal ramie microbial degumming condition was found as the culture temperature of 40℃,the initial pH in the culture medium of 8.5,the shaking speed of 205 r/min,the degumming time of 96 h and the inoculum size of 5%.After microbial degumming of ramie under the optimal conditions,there was only 10.6%residual gum by mass in the fiber.In addition,the effective degumming of BS DZ_(5)was also confirmed by a scanning electron microscope(SEM).

Optimization of Solid-state Fermentation Conditions of Sophora japonica cv.jinhuai by Response Surface Methodology

[Objectives]To optimize the solid-state fermentation process of Flos Sophorae Immaturus by Penicillium with Sophora japonica cv.jinhuai as raw material.[Methods]The fermentation conditions were optimized by single factor experiment and response surface methodology with quercetin content as the dependent variable.[Results]According to the established model,the optimal fermentation process of Flos Sophorae Immaturus was obtained as follows:temperature 29.97℃,time 6.88 d,rotation speed 180.86 rpm,inoculation amount 3.93 mL,and the expected content of quercetin was 34.8053 mg/g.Based on this,the fermentation parameters were adjusted,and the actual content was 33.67 mg/g,which was close to the predicted value.[Conclusions]The optimization of fermentation process of Flos Sophorae Immaturus by response surface methodology provides a reference for the development and utilization of this medicinal material.

Catalytic Hydrothermal Liquefaction of Water Hyacinth Using Fe3O4/NiO Nanocomposite: Optimization of Reaction Conditions by Response Surface Methodology

This research aimed at optimizing the reaction conditions for the catalytic hydrothermal liquefaction (HTL) of water hyacinth using iron oxide/nickel oxide nanocomposite as catalysts. The iron oxide/nickel oxide nanocomposite was synthesized by the co-precipitation method and used in the hydrothermal liquefaction of water hyacinth. The composition and structural morphology of the synthesized catalysts were determined using X-ray diffraction (XRD), transmission electron microscopy (TEM), scanning electron microscopy (SEM), and atomic absorption spectroscopy (AAS). The particle size distribution of the catalyst nanoparticles was determined by the Image J software. Three reaction parameters were optimized using the response surface methodology (RSM). These were: temperature, residence time, and catalyst dosage. A maximum bio-oil yield of 59.4 wt% was obtained using iron oxide/nickel oxide nanocomposite compared to 50.7 wt% obtained in absence of the catalyst. The maximum bio-oil yield was obtained at a temperature of 320°C, 1.5 g of catalyst dosage, and 60 min of residence time. The composition of bio-oil was analyzed using gas chromatography-mass spectroscopy (GC-MS) and elemental analysis. The GC-MS results showed an increase of hydrocarbons from 58.3% for uncatalyzed hydrothermal liquefaction to 88.66% using iron oxide/nickel oxide nanocomposite. Elemental analysis results revealed an increase in the hydrogen and carbon content and a reduction in the Nitrogen, Oxygen, and Sulphur content of the bio-oil during catalytic HTL compared to HTL in absence of catalyst nanoparticles. The high heating value increased from 33.5 MJ/Kg for uncatalyzed hydrothermal liquefaction to 38.6 MJ/Kg during the catalytic HTL. The catalyst nanoparticles were recovered from the solid residue by sonication and magnetic separation and recycled. The recycled catalyst nanoparticles were still efficient as hydrothermal liquefaction (HTL) catalysts and were recycled four times. The application of iron oxide/ nickel oxide nanocomposites in the HTL of water hyacinth increases the yield of bio-oil and improves its quality by reducing hetero atoms thus increasing its energy performance as fuel. Iron oxide/nickel oxide nanocomposites used in this study are widely available and can be easily recovered magnetically and recycled. This will potentially lead to an economical, environmentally friendly, and sustainable way of converting biomass into biofuel.

Optimizing aerobic biodegradation of dichloromethane using response surface methodology

Response surface methodology （RSM） was employed to evaluate the optimum aerobic biodegradation of dichloromethane （DCM） in pure culture. The parameters investigated include the initial DCM concentration, glucose as an inducer and hydrogen peroxide as terminal electron acceptor （TEA）. Maximum aerobic biodegradation efficiency was predicted to occur when the initial DCM concentration was 380 mg/L, glucose 13.72 mg/L, and H202 115 mg/L. Under these conditions the aerobic biodegradation rate reached up to 93.18%, which was significantly higher than that obtained under original conditions. Without addition of glucose degradation efficiencies were ≤ 80% at DCM concentrations ≤ 326 mg/L. When concentrations of DCM were more than 480 rag/L, the addition of hydrogen peroxide did not help to significantly increase DCM degradation efficiency. When DCM concentrations increased from 240 to 480 rag/L, the overall DCM degradation efficiency decreased from 91% to 60% in the presence of HaO2 for 120 mg/L.

Optimizing electrocoagulation process for the treatment of biodiesel wastewater using response surface methodology

The production of biodiesel through a transesterification method produces a large amount of wastewater that contains high levels of chemical oxygen demand （COD） and oil and grease （O＆G）. Currently, flotation is the conventional primary treatment for O＆G removal prior to biological treatments. In this study, electrocoagulation （EC） was adopted to treat the biodiesel wastewater. The effects of initial pH, applied voltage, and reaction time on the EC process for the removal of COD, O＆G, and suspended solids （SS） were investigated using one factor at a time experiment. Furthermore, the Box-Behnken design, an experimental design for response surface methodology （RSM）, was used to create a set of 15 experimental runs needed for optimizing of the operating conditions. Quadratic regression models with estimated coefficients were developed to describe the pollutant removals. The experimental results show that EC could effectively reduce COD, O＆G, and SS by 55.43%, 98.42%, and 96.59%, respectively, at the optimum conditions of pH 6.06, applied voltage 18.2 V, and reaction time 23.5 min. The experimental observations were in reasonable agreement with the modeled values.

Optimization of process parameters for the bioconversion of activated sludge by Penicillium corylophilum, using response surface methodology

The optimization of process parameters for the bioconversion of activated sludge by Penicillium corylophilum was investigated using response surface methodology （RSM）. The three parameters namely temperature of 33℃, agitation of 150 r/min, and pH of 5 were chosen as center point from the previous study of fungal treatment. The experimental data on chemical oxygen demand （COD） removal （%） were fitted into a quadratic polynomial model using multiple regression analysis. The optimum process conditions were determined by analyzing response surface three-dimensional surface plot and contour plot and by solving the regression model equation with Design Expert software. Box-Behnken design technique under RSM was used to optimize their interactions, which showed that an incubation temperature of 32.5℃, agitation of 105 r/min, and pH of 5.5 were the best conditions. Under these conditions, the maximum predicted yield of COD removal was 98.43%. These optimum conditions were used to evaluate the trail experiment, and the maximum yield of COD removal was recorded as 98.5%.

Extraction of seed oil from Diospyros lotus optimized using response surface methodology

Oil from seeds of Diospyros lotus was extracted using a conventional method with two different solvents:hexane and petroleum ether. A central composite design with response surface methodology were used to optimize the process. A second-order polynomial equation was employed, and ANOVA was applied to evaluate the impact of various operating parameters including extraction temperature(x_1; 44.9–70.1 °C), extraction time(x_2;5.0–10.0 h) and solvent to solid ratio(x_3;11.6–28.4 mL g^(-1)), on oil yield. Experiments to validate the model showed decent conformity between predicted and actual values. Extraction conditions for optimal oil yield were 61 °C, 8.75 h extraction duration and 19.25 mL g^(-1) solvent to solid ratio. Under these conditions, the oil yield was predicted to be 5.1340%. Oil samples obtained were then analyzed using gas chromatography. The fatty acid composition revealed the major fatty acids to be oleic acid(C18:1) and linoleic acid(C18:2). The analysis of oil also demonstrated a decent ratio between omega-3 and omega-6 fatty acids. The structure of seeds was imaged using scanning electron microscopy. Oil quality was analyzed thermogravimetrically and by Fourier transform infrared spectroscopy. The assigned nutritional features of the D. lotus oil suggested that it can be used as an edible oil in pharmaceutical and food industry in the future.

Application of response surface methodology in optimizaing thesulfation-roasting-leaching process of nickel laterite

Nickel was recovered from nickel laterite using a sulfation-roasting-leaching process and the effects of operation parameters in- cluding acid addition, roasting temperature, and roasting time on nickel extraction and iron dissolution were investigated using response sur- face methodology （RSM）. Two second-order polynomial models of high significance were presented to show the relationship between the responses and the variables. The analysis of variance （ANOVA） showed high coefficients of determination （R2） of 0.894 and 0.980 for the two models, respectively. Optimum areas of 〉-80% Ni extraction and 〈5% Fe dissolution were obtained by the overlaid contours. Verification experiments in the optimum areas were conducted and the results indicate a close agreement with the predicted values obtained from the models.

The Optimization of Ultrasonic Extraction Technology of Total Flavonoids in Leaves of Mallotus apelta by Response Surface Analysis Methodology

[Objectives] Response surface analysis methodology was used to optimize the extraction technology of total flavonoids from Mallotus apelta leaves. [Methods] The total flavonoids were extracted using ultrasonic assisted ethanol extraction,and extraction rate of total flavonoids was taken as evaluation index. On the basis of single-factor experiment,Box-Behnken response surface methodology was employed for selecting the optimum extraction process. [Results]The optimum extraction conditions of total flavonoids were as follows: 75% of ethanol concentration,1∶ 25 of ratio of material to liquid,31 min of ultrasonic time. Under these conditions,the extraction rate of total flavonoids was 1. 115%.[Conclusions] The extraction process obtained by response surface methodology was stable,reasonable,accurate and reliable. It was a feasible method to extract the total flavonoids from M. apelta leaves.

Optimization of Inactivation Conditions of High Hydrostatic Pressure Using Response Surface Methodology

Response surface methodology (RSM) was employed in the present work and a second orderquadratic equation for high hydrostatic pressure (HHP) inactivation was built. Theadequacy of the model equation for predicting the optimum response values was verifiedeffectively by the validation data. Effects of temperature, pressure, and pressureholding time on HHP inactivation of Escherichia coli ATCC 8739 were explored. Byanalyzing the response surface plots and their corresponding contour plots as well assolving the quadratic equation, the optimum process parameters for inactivation E. coliof six log cycles were obtained as: temperature 32.2℃, pressure 346.4 MPa, and pressureholding time 12.6min.