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.

Optimization of Photo-Fenton Catalyst Preparation Based Bamboo Carbon Fiber by Response Surface Methodology

In this paper,the residue from bamboo factory has been used to design photo-Fenton catalyst,which has the advantages of low cost and magnetic recycling.The photo-Fenton catalytic performance of the biocarbon-based catalyst was excellent and its optimal preparation process was also explored by response surface methodology.First,bamboo-carbon fiber was selected as the photo-Fenton catalyst carrier.Subsequently,the surface of the car-bon fiber was modified,with which dopamine,nano-Fe_(3)O_(4) and nano-TiO_(2) were successively loaded by hydro-thermal method.After the single factor tests,four factors including dopamine concentration,ferric chloride mass,P25 titanium dioxide mass and liquid-solid ratio were selected as the characteristic values.The degradation efficiency of photo-Fenton catalyst to methylene blue(MB)solution was treated as the response value.After the analysis of the response surface optimization,it was shown that the significance sequence of the selected 4 factors in terms of the MB degradation efficiency was arranged as follows:dopamine concentration>liquid-solid ratio>P25 titanium dioxide quality>ferric chloride quality.The optimal process parameters of fiber-carbon catalyst were affirmed as follows:the 1.7 mg/mL concentration of dopamine,the 1.2 g mass of ferric chloride,the 0.2 g mass of P25 titanium dioxide and the liquid-solid ratio of 170 mL/g.The experiment-measured average MB degra-dation efficiency performed by the optimized catalyst was 99.3%,which was nearly similar to the model-predicted value of 98.9%.It showed that the prediction model and response surface model were accurate and reliable.The results from response surface optimization could provide a good reference to design bamboo-based Fenton-like catalyst with excellent catalytic performance.

Mechanical and Permeability Analysis and Optimization of Recycled Aggregate Pervious Concrete Based on Response Surface Method

In this paper,the effects of different influencing factors and factor interaction on the compressive strength and permeability of recycled aggregate pervious concrete(RAPC)were studied based on the response surface method(RSM).By selecting the maximum aggregate size,water cement ratio and target porosity as design variables,combined with laboratory tests and numerical analysis,the influences of three factors on the compressive strength and permeability coefficient of RAPC were revealed.The regression equation of compressive strength and permeability coefficient of recycled aggregate pervious concrete were established based on RSM,and the response surface model was optimized to determine the optimal ratio of RAPC under the conditions of meeting the mechanical and permeability properties.The results show that the mismatch item of the model is not significant,the model is credible,and the accuracy and reliability of the test are high,but the degree of uncorrelation between the test data and the model is not obvious.The sensitivity of the three factors to the compressive strength is water cement ratio>maximum coarse aggregate particle size>target porosity,and the sensitivity to the permeability coefficient is target porosity>maximum coarse aggregate particle size>water cement ratio.The absolute errors of the model prediction results and the model optimization results are 1.28 MPa and 0.19 mm/s,and the relative errors are 5.06%and 4.19%,respectively.With high accuracy,RSM can match the measured results of compressive strength and permeability coefficient of RAPC.

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.

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).

Response Surface Optimization of Ultrasound-assisted Aqueous Two-phase Extraction of Sweet Potato Leaf Polysaccharides

[Objectives]The ultrasound-assisted aqueous two-phase extraction of sweet potato leaf polysaccharides was studied.[Methods]With the yield of sweet potato leaf polysaccharides as the index,the aqueous two-phase extraction system was determined,and the optimal extraction conditions were optimized by single-factor experiments and response surface methodology.[Results]The optimal parameters were ethanol concentration 25.68%,liquid-to-material ratio 55.83,and ultrasonic treatment time 38.33 min.Under these conditions,the yield of sweet potato leaf polysaccharides could reach 20.646 mg/g.[Conclusions]The ethanol/ammonium sulfate aqueous system is a rapid and efficient method for extracting sweet potato leaf polysaccharides,which is of great significance for the application of sweet potato leaf extract as a natural food additive.

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.

INTEGRATION SHAPE AND SIZING OPTIMIZATION OF COMPOSITE WING STRUCTURE BASED ON RESPONSE SURFACE METHOD

An effective optimization method for the shape/sizing design of composite wing structures is presented with satisfying weight-cutting results. After decoupling, a kind of two-layer cycled optimization strategy suitable for these integrated shape/sizing optimization is obtained. The uniform design method is used to provide sample points, and approximation models for shape design variables. And the results of sizing optimization are construct- ed with the quadratic response surface method （QRSM）. The complex method based on QRSM is used to opti- mize the shape design variables and the criteria method is adopted to optimize the sizing design variables. Compared with the conventional method, the proposed algorithm is more effective and feasible for solving complex composite optimization problems and has good efficiency in weight cutting.

SCRAMJET INLET MULTI-OBJECTIVE OPTIMIZATION BASED ON RESPONSE SURFACE METHODOLOGY

The uniform design and response surface methodology （RSM） are applied to the multi-objective optimization of a 2-D mixed compression scramjet inlet. The set of experimental design points on the design space is selected by the uniform design, and the inlet performance is analyzed by computational fluid dynamics （CFD）. Then complete quadratic polynomial response surface approximation models are constructed based on the performance analysis results and then used to replace theoriginal complex inlet performance model. The optimization is conducted using a multi-objective genetic algorithm NSGA-Ⅱ, and the Pareto optimal solution set is obtained. Results show that the uniform design and RSM can reduce the computational complexity of numerical simulation and improve the optimization efficiency.

Optimization of the biphasic release of indomethacin from HPMC/pectin/calcium chloride matrix tablet by response surface methodology

We studied the effect of two independent variables, the pectin/calcium chloride weight ratio and the overall matrix weight in HPMC/pectin/calcium matrix tablet, on the release of indomethacin. A two-factor 5-level central composite experimental design was employed. Responses of the Peppas correlation parameters n and K and the 10% release time （T0.1） were optimized by response surface methodology. Significant effect of the independent variables on the biphasic release parameters, n and K, was observed. N, K and T0.1 were well fitted with the second-order quadratic equations rather than linear equations. Moreover, the mathematic fitting and the response surfaces showed significant cross-interaction between the pectin/calcium chloride ratio and the overall matrix weight. The optimal formulation with larger n, longer T0.1 and smaller K consisted of medium pectin/calcium chloride ratio around 1.0 and medium matrix weight around 200 mg. Validation studies on the optimal formulations showed good predictability of the n, K and T0.1 values with biases within the range of-7.33% and 6.26%. Our results support that central composite design can be used to optimize drug release from HPMC/pectin/calcium matrix tablet with high predictability.

Composite Structural Optimization by Genetic Algorithm and Neural Network Response Surface Modeling

Neural-Network Response Surfaces （NNRS） is applied to replace the actual expensive finite element analysis during the composite structural optimization process. The Orthotropic Experiment Method （OEM） is used to select the most appropriate design samples for network training. The trained response surfaces can either be objective function or constraint conditions. Together with other conven- tional constraints, an optimization model is then set up and can be solved by Genetic Algorithm （GA）. This allows the separation between design analysis modeling and optimization searching. Through an example of a hat-stiffened composite plate design, the weight response surface is constructed to be objective function, and strength and buckling response surfaces as constraints; and all of them are trained through NASTRAN finite element analysis. The results of optimization study illustrate that the cycles of structural analysis ean be remarkably reduced or even eliminated during the optimization, thus greatly raising the efficiency of optimization process. It also observed that NNRS approximation can achieve equal or even better accuracy than conventional functional response surfaces.

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%.

SIX SIGMA OPTIMIZATION IN SHEET METAL FORMING BASED ON DUAL RESPONSE SURFACE MODEL

Iterations in optimization and numerical simulation for the sheet metal forming process may lead to extensive computation. In addition, uncertainties in materials or processing parameters may have great influence on the design quality. A six sigma optimization method is proposed, by combining the dual response surface method （DRSM） and six sigma philosophy, to save computation cost and improve reliability and robustness of parts. Using this method, statistical technology, including the design of experiment and analysis of variance, approximate model and six sigma philosophy are integrated together to achieve improved quality. Two sheet metal forming processes are provided as examples to illustrate the proposed method.

Application of response surface methodology in medium optimization for pyruvic acid production of Torulopsis glabrata TP19 in batch fermentation

Response surface methodology (RSM) was used to optimize the fermentation medium for enhancing pyruvic acid production by Torulopsis glabrata TP19. In the first step of optimization, with Plackett-Burman design, ammonium sulfate, glucose and nicotinic acid were found to be the important factors affecting pyruvic acid production significantly. In the second step, a 23 full factorial central composite design and RSM were applied to determine the optimal concentration of each significant variable. A second-order polynomial was determined by the multiple regression analysis of the experimental data. The optimum values for the critical components were obtained as follows: ammonium sulfate 0.7498 (10.75 g/L), glucose 0.9383 (109.38 g/L) and nicotinic acid 0.3633 (7.86 mg/L) with a predicted value of maximum pyruvic acid production of 42.2 g/L. Under the optimal conditions, the practical pyruvic acid production was 42.4 g/L. The determination coefficient (R2) was 0.9483, which ensures adequate credibility of the model. By scaling up fermentation from flask to jar fermentor, we obtained promising results.

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.

Optimization of Fermentation Process for Human-like Collagen Production of Recombinant Escherichia coli Using Response Surface Methodology

In order to improve the production of human-like collagen III(HLC III)by fed-batch culture of recombinant Escherichia coli BL21,the Plackett-Burman and Box-Behnken design were applied to optimize the fermentation process parameters.Three variables(induction time,inoculum age and pH),which have significant effects on HLC III production,were selected from eight variables by Plackett-Burman design.With the regression coefficient analysis in the Box-Behnken design,a relationship between HLC III production and three significant factors was obtained,and the optimum levels of the three variables were as follows:induction time 3.2h,inoculum age 12.6 h and pH 6.7.The 3D response surface plots and 2D contour plots created by the Box-Behnken design showed that the interaction between induction time and pH and that between innoculum age and pH were significant.An average 9.68 g·L1HLC III production was attained in the validation experiment under optimized condition,which was 80%higher than the yield of 5.36 g·L1before optimization.

Modeling and optimization of low-grade Mn bearing ore leaching using response surface methodology and central composite rotatable design

The application of leaching process to extracting Mn from a low-grade manganese ore was investigated using a software based design of experiments. Four main parameters, i.e. sulfuric acid concentration, oxalic acid concentration, time and temperature were considered in a central composite response surface design. The recoveries of Mn and Fe were selected as response of design. The optimum conditions under which the Mn and Fe recoveries were the highest and the time and temperature were the lowest were determined using statistical analysis and analysis of variance （ANOVA）. The results showed that Mn and Fe recoveries were 93.44% and 15.72% under the optimum condition, respectively. Also, sulfuric acid concentration was the most effective parameter affecting the process. The amounts of sulfuric and oxalic acid were obtained to be 7% and 42.50 g/L in optimum condition and the best time and temperature were 65 min and 63 ℃.

Extraction of Total Phenolic Compounds, Flavonoids, Anthocyanins and Tannins from Grape Byproducts by Response Surface Methodology. Influence of Solid-Liquid Ratio, Particle Size, Time, Temperature and Solvent Mixtures on the Optimization Process

The current work concerns the optimization process of phenolic compounds solid liquid extraction from grape byproducts at high temperatures and short incubation times. The effect of five experimental parameters (solidliquid ratio, particle size, time, temperature and solvent mixture) mostly believed to affect the extraction process was undertaken. A first response surface methodology experimental design was used to optimize the solid-liquid ratio and milling time parameters. A second design was used for the optimization of the quantitative and qualitative parameters. The quantitative parameters studied are: total phenolic compounds, flavonoid content, total monomeric anthocyanin composition and tannin concentration. The qualitative parameters analyzed are: antiradical activity and antioxidant capacity. The second design was based on the use of time, temperature and solvent mixture as optimization parameters. The assays were first conducted separately revealing the best experimental conditions for the maximization of each response variable alone. A simultaneous response surface methodology of all the responses taken together was then conducted, showing the optimal extraction conditions to be: 93 minutes at 94?C and in 66% ethanol/water solvent. The maximal response values obtained for each parameter are: Total Phenolic Compounds yield (5.5 g GAE/100g DM), Flavonoid Content (5.4 g GAE/100g DM), Total Monomeric Anthocyanin yield (70.3 mg/100g DM), Tannin Concentration (12.3 g/L), Antiradical Activity (67.3%) and Total Antioxidant Capacity (393 mgAAE/L). All of the optimal values were acquired at 3 mL/g solid-liquid ratio and 6.8 min milling time. The obtained extracts could be used as natural bioactive compounds in several industrial applications.

Optimization of Formula of Matsutake Highland Barley Biscuit by Response Surface Methodology

Taking refined flour,matsutake powder,and highland barley powder as main raw materials,this experiment studied the optimal formula of matsutake highland barley biscuit. Besides,single factor experiment was carried out for the amount of highland barley powder,white granulated sugar,and shortening. Then,the response surface optimization analysis was made on crispness and sensory score of the biscuit. The experiment indicates that taking the refined flour as the base 100 g( 100%),the formula of 20% highland barley powder,25% white granulated sugar,and 26% shortening can bake crisp biscuit with complete shape,pure flavor and high quality.