Interactive Effects Of Process Variables Research Articles

Biofabrication of TiO2 nanoparticles via Aspergillus niger DS22 supernatant: bioreactor optimization and multi-activity profiling

AbstractThe study presents a safe and eco-friendly green synthesis of titanium dioxide nanoparticles (TiO2 NPs) using Aspergillus niger DS22 (ON076463.1) cell-free filtrate, focusing on optimizing factors affecting nitrate reductase enzyme production within the framework TiO2 NP biosynthesis. Maximum enzyme activity was accomplished by growing A. niger DS22 in a modified MYGP medium at pH 6, 0.5% peptone, 0.15% yeast extract, 0.25% KNO3, 2% glucose, and 200 rpm for 4 days at 30 °C. Statistical optimization takes place, where a central composite design was employed for testing the reaction variables. The individual and interactive effects of process variables lead to optimal biosynthesis conditions with 10−4 M (K2TiF6) concentration, for 96 h, 28 °C, pH 9, and Ti+4 salt solution:filtrate ratio (10%, v/v). Kinetic conversion rates in 1-L shake flask and 10-L stirred tank bioreactor were calculated and compared. Current findings revealed that the yield coefficient of biomass dry weight (Yx/s) and the yield coefficient of TiO2 NP dry weight (Y pn/s) in the bioreactor exceed those of the shake flask (0.85 g/L and 0.51 g/L; 0.04 g/L and 0.11 g/L, respectively). TiO2 NPs showed anticancer activities with high biocompatibility (at 1000 µg/mL) against MCF-7 and HepG-2 cell lines, with 97.35% and 97.71% cytotoxicity, respectively. TiO2 NPs had a moderate antioxidant activity of 57.8% recorded by DPPH assay. Moreover, TiO2 NPs had anticoagulant activities and decolorization efficiency for methyl orange dye. The current study paves the way for maximizing TiO2 NP production, which can be used in industrial and medical sectors. Graphical Abstract

Nitrate removal from groundwater using chemically modified coconut husk based granular activated carbon: characterization of the adsorbent, kinetics and mechanism

In this study, a highly porous chemically activated granular activated carbon (GAC) was prepared from coconut husk and tested as an adsorbent to remove nitrate from contaminated groundwater. The prepared GAC was characterized by Fourier-transform infrared spectroscopy (FTIR), thermogravimetric and differential thermal analysis (TGA/DTA), scanning electron microscopy (SEM) and the Brunauer–Emmett–Teller (BET) surface area (SBET) analysis. The effects of various process parameters such as initial nitrate concentration, contact time and adsorbent dose on nitrate removal efficiency (response) by the modified GAC were investigated using the statistically significant response surface methodology and Box–Behnken design of experiments. The experimental data were fitted to well-known adsorption isotherms and kinetic models to ascertain the mechanism of the adsorption process. Analysis of variance (ANOVA) was performed to determine the significance of the individual and the interactive effects of process variables on the response. The BET surface area (SBET) and micropore volume of the prepared GAC from coconut husk was 1120 m2/g and 0.392 cm3/g, respectively. The experimental results showed that physisorption was the main adsorption mechanism governing the process, while the rate of adsorption was limited at initial nitrate concentrations > 10 mg/L. The Langmuir mono-layer adsorption isotherm best fitted the experimental data with a maximum adsorption capacity of 6.0 ± 1.3 mg/g (~ 92.5%) with an adsorbent dose of 0.1 g/50 mL, an equilibrium time of 6 h at 28 ± 2 °C, and at pH 7.6 (± 0.2). Among the tested process variables, the adsorbent dose and initial nitrate concentration showed significant effects on the nitrate removal efficiency.

Delamination and surface roughness analysis of jute/polyester composites using response surface methodology: Consequence of sodium bicarbonate treatment

The present research work explores the consequence of eco-friendly sodium bicarbonate treatment on drilling behavior of jute fiber reinforced polyester composites. The fiber surface treatment was done by immersing the jute fibers in sodium bicarbonate solution (10 wt.%) for five days at room temperature. The raw and treated jute fiber composites were produced through compression molding process. The drilling behavior was expressed in terms of delamination factor (at entry and exit) and surface finish. The response surface methodology coupled with three factors—three levels Box–Behnken Design was used to study the interactive effects of process variables (drill diameter, feed, and cutting speed) on delamination factor and surface finish. Furthermore, the significance of the developed model was examined through analysis of variance. The chip morphology of the fabricated composites was examined to assess the quality of the drilled hole. The fractography analysis of the machined surface has also been carried using scanning electron microscopy. The outcomes revealed that the sodium bicarbonate treatment of jute fiber improved the machinability of the composites.

Modeling and Optimization of Mitragyna speciosa Extraction using Box Behnken Design

The extraction of kratom (M. speciosa) leaf powder was optimized with preliminary extraction to be further optimized with the Box-Behnken experimental design. The individual and interactive effects of process variables (sample-to-solvent ratio, extraction time, solvent concentration) were assessed. The preliminary extraction results showed that ultrasound-assisted extraction (UAE) and methanol were chosen for further optimization. The experimental data were analyzed by Pareto analysis of variance (ANOVA) and second-order polynomial models were developed using multiple regression analysis. The model developed showed a good fit with the experimental data with a high coefficient of correlation (R2) and predictive ability (predicted R2). An optimization study was performed and the optimal extraction conditions were sample-to-solvent ratio value 1.5:10; extraction time of 10 minutes, and methanol concentration of 100%.

Influence of Process Parameters on the Gas Phase Polymerization of Ethylene: RSM or ANN Statistical Methods?

AbstractThe direct and interactive effects of process variables, including the use of iso‐pentane as an inert condensing agent, on the rate of polymerization and main physical properties of linear low‐density polyethylene are studied using two different statistical methods. Response surface methodology (RSM) based on a three level five factor Box–Behnken design is used to generate the number of experimental runs. The generated dataset is used to develop the RSM and artificial neural network (ANN) models. The effect of the input on the dependent variables is studied using the 3D response surface of the developed RSM model. The developed models are statistically analyzed and compared to determine their performance capability. The ANN model marginally outperforms the RSM model based on the computed statistical parameters but provides less information on the variable interactions.

Effects of extrusion parameters on physicochemical properties of third generation corn snacks expanded by microwave heating

Corn grits were extruded then extrudates were expanded by microwave-heating. Effects of addition of xanthan gum (XG) (0%–1%), feed moisture content (37%–47%) and screw speed (100–300 rpm) level on physicochemical properties of snacks were evaluated with response surface methodology (RSM). All suspensions of expanded samples exhibited shear-thinning behavior. Apparent amylose content of samples ranged from 22.47% to 37.97%. Screw speed and feed moisture content had positive effect on apparent viscosity and amylose content but XG level had negative effect on them. Increasing screw speed increased expansion and luminosity but decreased browning index and total color difference. Increasing feed moisture content resulted in reduced expansion, luminosity but increased browning index. In contrast to the initial effect, expansion and browning index decreased when XG addition level was above 0.5%. Optimum conditions were determined to obtain the maximum values for expansion index and luminosity and minimum value for the total color difference by desirability function. They were found as 300-rpm screw speed, 47% feed moisture content and 0.34% XG level. Practical applications Extrusion process occupies an important place in the food industry for production of snacks and breakfast cereals. This technology is especially preferred due to its versatility, high productivity, relative low cost energy efficiency for snack production. However, extrusion process conditions (feed moisture, screw speed, and barrel temperature) and additives used in this process have critical importance for snack characteristics. Gum addition provides lubrication during extrusion process. Expansion and color characteristics of product may be change according to gum addition level. Response surface methodology (RSM) can be used as an optimization tool to achieve a better product considering multiple quality characteristics for snacks. A better evaluation of simultaneous interactive effects of process variables on the products can be achieved with RSM technique. Application of RSM in this study may be employed as baseline information for further scale-up of third generation snack production with several additives and under different production conditions.

Modeling and optimization of pectin extraction from banana peel using artificial neural networks (ANNs) and response surface methodology (RSM)

In the present study, the extraction of pectin from banana peel (Musa sp.) was optimized using artificial neural network and response surface methodology on the yield and degree of esterification obtained using microwave-assisted extraction methods. The individual, quadratic and interactive effect of process variables (temperature, time, liquid–solid ratio and pH) on the extracted pectin yield and DE of the extract were studied. The results showed that properly trained artificial neural network model was found to be more accurate in prediction as compared to response surface model method. The optimum conditions were found to be temperature of 60 °C, extraction time of 102 min, liquid–solid ratio of 40% (v/w) and pH of 2.7 and within the desirable range of the order of 0.853. The yield of pectin and degree of esterification under these optimum conditions were 14.34% and 63.58, respectively. Temperature, time, liquid–solid ratio and pH revealed a significant (p < 0.05) effect on the pectin yield and degree of esterification. Based on the value of methoxyl content and degree of esterification the extracted pectin was categorized as high methoxyl pectin. Generally, the findings of the study show that banana peel can be explored as a promising alternative for the commercial production of pectin.

Application of Response Surface Method to Copper Cementation by Metallic Aluminum Particles

In the present study, the interactive effects of the process variables containing copper concentration, temperature, and time on the efficiency of copper cementation by metallic aluminum particles were examined by using response surface methodology (RSM). It was observed that the efficiency of cementation increased with an increase in the initial concentration of copper, temperature and time. The multiple regression analysis to the experimental data was applied to see the interactive effects of process variables. The second-order polynomial equation was obtained. The optimal values were found to be 0.075 mol/l, 303 K, and 90 min to maximize the amount of the deposited copper.

Regression and mathematical modeling of fluoride ion adsorption from contaminated water using a magnetic versatile biomaterial & chelating agent: Insight on production & experimental approaches, mechanism and effects of potential interferers

Fluoride is one of the chemicals that enter the human body through drinking water and, at higher concentrations, can cause various long-term health effects. Owing to remove the pollutant from aqueous solutions on large-scale, researchers are always exploring efficient, inexpensive, and easily recoverable adsorbents. In this research study, a versatile magnetic biomaterial & chelating agent (Chitosan) is used as an adsorbent for fluoride removal. In the present research, chitin was extracted from discarded shrimp shells. The obtained Chitosan was characterized based on its yielding, moisture and ash content, degree of acetylation and water binding capacity according to standard protocols. Also, in this study, differential evolution optimization is used to evaluate isotherm and kinetic model parameters using nonlinear model expressions, thus depicting inherent mechanisms. The isotherm and kinetic studies revealed that the adsorption process follows Langmuir and the pseudo 2nd order kinetic model. The interactive effect of process variables is investigated, and their optimal conditions for higher removal efficiency are estimated using response surface methodology. A quadratic model was used to predict removal efficiency at different operating conditions, which resulted in R2 of 0.9949. Optimum adsorption efficiency (93.1%) was observed at an adsorbent rate of 1 g/L, initial concentration of 1 mg/L, pH of 3, and contact time of 25 min. The thermodynamic study is indicating that the process is exothermic and spontaneous. The effect of interventions such as chloride, acidic, and sulfate on fluoride removal was also investigated, and results indicated that Chitosan-Fe3O4 is also efficient in their presence. A hybrid model of ANN and GA predicted the fluoride removal at different operating conditions, and results indicated that prediction values result in R2 of 0.9825. Thus, these results confirm the remarkable ability of Chitosan-Fe3O4 nanocomposite for fluoride removal.

Quality characteristics of composite biodegradable films for food packaging

Purpose The physical, biomechanical and chemical properties of the composite biodegradable films are examined by their chemical composition, structure, processing conditions and economics. Therefore, the purpose of the study was to develop standard composite biodegradable films by optimizing the process (drying time and temperature) and composition (whey protein concentrate; WPC and sodium alginate; SA). Design/methodology/approach Composite WPC–SA films were developed using the Box–Behnken design of response surface methodology (RSM), with individual and interactive effects of process variables on the response variables (quality characteristics). Three independent factors at three different levels (WPC: 5–7 g, SA: 0.1–0.5 g and drying temperature: 35°C–45°C) were evaluated for their effects on physical and biomechanical properties, namely, thickness, penetrability, moisture content, water vapor transmission rate (WVTR), density, solubility, transmittance and color variables. The results were analyzed using ANOVA. For each response, second-order polynomial regression models and resulting equations were developed. Findings The response surface plots were constructed for representing a relationship between process parameters and responses. All responses were optimized as the best and desired, namely, thickness (180 µm), penetrability (7.63 N), moisture (28.05%), WVTR (1.87 mg/m2t), solubility (36.12%), density (1.33 g/ml), transmittance (40.55%), L* value (52.50), a* value (0.35) and b* value (13.70). The regression models exhibited “good fit” of experimental data with a high coefficient of determination. A close agreement was found between experimental and predicted values. Practical implications These biodegradable films can be promisingly used in the food packaging system without the problem of disposability. Originality/value The composite films with proteins and polysaccharides can be developed, which have improved physical and biomechanical properties.

An Investigation into the Tribological Properties of Bidirectional Jute/Carbon Fiber Reinforced Polyester Hybrid Composites

ABSTRACT In this work, the tribological performance of bidirectional jute/carbon fiber reinforced polyester composites was investigated using response surface methodology. The effects of three factors namely fiber weight fraction, load, and sliding velocity on the wear and friction values were examined. The composites were fabricated by using compression molding technique and the dry sliding test was conducted using pin-on-disk machine. The response surface methodology coupled with three factors – three-level Box-Behnken design was employed to examine the interactive effects of process variables on wear loss and coefficient of friction. Moreover, Analysis of Variance technique was used to inspect the statistical significance of the developed model. The outcomes revealed that the wear loss increased with the increase in sliding velocity and load and decreased with the increase in weight volume fraction due to diminishing contact between the polyester matrix and rotating disk. However, the coefficient of friction decreased with the increase in process variables. Furthermore, the morphology of worn-out samples was examined using scanning electron microscopy to understand wear mechanisms.

Studies on fast and green biodiesel production from an indigenous nonedible Indian feedstock using single phase strontium titanate catalyst

Strontium titanate was synthesized by polymer precursor method and its catalytic activity as heterogeneous basic catalyst was tested in transesterification reaction for high-quality biodiesel production form Madhuca indica oil. The synthesized strontium titanate was characterized by powder X-ray Diffraction (XRD), X-Ray Photoelectron Spectroscopy (XPS), Field Emission Scanning Electron Microscopy (FESEM) attached with Energy Dispersive X-ray Spectroscopy (EDS), Transmission Electron Microscopy (TEM), Fourier Transform Infrared Spectroscopy (FTIR). Surface area and basicity were also determined using Brunauer-Emmett-Teller (BET)surface area analyzer and Hammett indicator method. The structural characterizations of catalyst enunciated the single perovskite phase formation of well-assorted strontium titanate nanospheres. The transesterification reaction was optimized using one variable at a time (OVAT) and Response Surface Methodology (RSM) using Box Behnkehn Design (BBD) to comprehend the linear effect and interactive effect of process variables on biodiesel production. The optimized reaction condition through OVAT was obtained as: catalyst dose (1.3 wt%), methanol to oil molar ratio (18:1), reaction temperature (65 °C), reaction time (120 min), and agitation speed (600 rpm) while RSM predicted the highest methyl ester conversion at optimum catalyst dose (1.19 wt%), methanol to oil molar ratio (21.5:1), reaction temperature (71 °C), and reaction time (97.7 min). The confirmatory experiment noticed the highest 98% FAME conversion at following reaction conditions catalyst dose (1.2 wt%), methanol to oil molar ratio (22:1), reaction temperature (65 °C), and reaction time (100 min). Confirmatory experiment showed its close agreement with the predicted values from RSM instead OVAT. According to RSM, catalyst dose, reaction temperature, reaction time, and methanol to oil molar ratio were influencing process parameters for transesterification in descending order of their strength. Furthermore, a pseudo-first-order kinetic model was established with the activation energy (Ea) of 65.95 kJ mol−1. The Environmental Factor (E-factor) and Turn Over Frequency (TOF) were also determined and demonstrated the prepared catalyst as a sustainable and potential heterogeneous base catalyst. The physicochemical properties of produced biodiesel were evaluated to check its compatibility with conventional diesel fuel.

Treatment of fracturing wastewater using microalgae‐bacteria consortium

AbstractThe symbiotic relationships between Chlorella vulgaris and Bacillus bacteria in fracturing wastewater treatment were investigated under different conditions, including varying dilution ratios of fracturing wastewater (2‐4), dosages of bacteria (20 mg/L‐80 mg/L), and pH (6.5‐8.5). The effects of process variables on the response of algal density were optimized and investigated via the Box‐Behnken response surface design. The individual and interactive effects of process variables on the response were studied by a second‐order polynomial model and three‐dimensional response surface plots. The optimal treatment conditions were a dilution ratio of 2, bacteria dose of 72.13 mg/L, and pH of 6.5, and the maximum biomass concentration of Chlorella vulgaris was 2.23 g/L. Moreover, Bacillus bacteria can increase the activity of superoxide dismutase (SOD) and acetyl‐CoA carboxylase (ACCase) of Chlorella vulgaris. Compared to the free Chlorella vulgaris, the co‐cultivation of Chlorella and Bacillus bacteria can improve the algal growth and degradation of organic pollutants.

Improved Bioactive Metabolite Production by Saccharopolyspora halotolerans VSM-2 Using Response Surface Methodology and Unstructured Kinetic Modelling

Background: This study targets to optimize and analyse the interactive effects of process variables for improved bioactive metabolite production using RSM and unstructured kinetic modelling by S. halotolerans VSM 2. Materials and Methods: RSM was applied to optimize the interactive effects of five variables, viz., time of incubation, pH, temperature, concentration of maltose and meat extract on bioactive metabolite production and its effect against the five responses viz., S. flexneri, S. marcescens, P. vulgaris, P. aeruginosa and E. coli. Models of Logistic and Luedeking-Piret were used to simulate the cellular increase and bioactive metabolite production. Results: RSM optimal conditions for the bioactive metabolite production recorded were incubation time (12days), pH (8), and temperature (250C), concentrations of maltose and meat extract (1 % w/v) (each). The effect of the bioactive metabolite produced (zone of inhibition) against the responses were found to be 17 mm for S. flexneri, 17 mm for S. marcescens, 16 mm for P. vulgaris, 17 mm for P. aeruginosa and 18 mm for E coli. The data obtained from experimental values are in close agreement with the predicted values of RSM. Model adequacy was evaluated using ANOVA variance where the quadratic effect of p<0.0001 which imply the significance of the model. The unstructured-, mathematical- kinetic models provided a better approximation of profiles of S. halotolerans VSM 2 growth, optimized media utilization and bioactive metabolite production. Conclusion: Optimization of the independent variables for the production of the bioactive metabolite using RSM by S. halotolerans VSM 2 and its effect against the five responses were documented. The predicted values are in good agreement with the experimental values. Unstructured models provided a better approximation of kinetic profiles for bioactive metabolite production by S. halotolerans VSM 2.

Biodiesel production from Cholrella minutissima microalgae: Kinetic and mathematical modeling

ABSTRACTIn the present work, a new and pioneering hybrid technology, called hydrodynamic-cavitation reactor, was established and investigated to proof the feasibility for the biodiesel production from Chlorella minutissima microalgae. The process parameters such as inlet pressure (A), molar ratio (B), catalyst concentration (C), and reaction time (D) have been investigated over the biodiesel yield from Chlorella minutissima microalgae. Box–​Behnken design was applied to develop the second- order polynomial model. The error between experimental values and model prediction was found to be less than 10%. Interactive effects of process variables on the biodiesel yield from Chlorella minutissima microalgae was studied using contour graphs. Inlet pressure of 4 bar, molar ratio of 1: 30, catalyst concentration of 1.3%, and reaction time of 40 min produced 99% of biodiesel yield. Further, a kinetic model has also been developed and considers the transesterification reaction to be a second-order reversible, first order with respect to each of the reactants and products. Estimated values of kinetic constants are k1 = 0.00014 L min/mol and k2 = 0.035 L min/mol.

Hydrogen gas production from sago industry wastewater using electrochemical reactor: Simulation and validation

ABSTRACTThis study describes the production of hydrogen gas from sago industry wastewater under varying operating conditions, such as time of electrolysis, electrode surface area, and current intensity. The process was investigated by employing a four-factor three-level Box–Behnken statistical design (BBD). The results were examined using analysis of variance (ANOVA). This study developed a second-order polynomial model and utilized three-dimensional (3D) response graphs to study the interactive effect of process variables on the production of hydrogen gas. The optimum conditions for maximum hydrogen gas production were determined and found to be 45 cm2 for electrode surface area, 22 min for time of electrolysis, and 13 A for current intensity. The predicted hydrogen gas output in optimum conditions was 1.12 mL/L. These results show that it is possible to achieve efficient hydrogen gas production, by electrochemically processing in sago industry wastewater.

Modelling and optimization of Ag-nanoparticle biosynthesis mediated by walnut green husk extract using response surface methodology

In biogenic synthesis of nanoparticles, plant extracts can be implemented as a source for electrons and stabilizers during chemical reduction of metallic ions in order to form nanoparticles. Experimental conditions of this procedure play vital roles in the synthesis rate of the product. Here, a response surface methodology was employed for the optimization of Ag-conjugated nanoparticles biosynthesis mediated by Persian walnut (Juglans regia) green husk extract. The individual and interactive effects of process variables (temperature, time, concentration and pH) on the production rate of the final product were monitored and the best second-order polynomial model with high coefficient of determination (R2) value was constructed. Later, optimal reaction conditions for the maximum production rate were found at the reaction temperature of 51.27°C, duration of 71.45min, pH of 6.82 and concentration of 8%. These data can be employed in large scale production of nanoparticles mediated by walnut green husk extract.

Preparation of Chitosan based Nanofibers: Optimization and Modeling

Abstract The main objective of the present study is to prepare a chitosan based nanofiber and model the electrospinning process using response surface methodology (RSM). The electrospinning parameters such as collector distance, polymer solution concentration and applied voltage were optimized by using three-variable-three-level Box–Behnken design (BBD). Based on RSM analysis, second order polynomial equation was formed and it indicated good correspondence between experimental and predicted values. 3D response surface plots were used to study the individual and interactive effects of process variables on chitosan based nanofiber diameter. The optimum process conditions for the minimum chitosan based nanofiber diameter (0.3 µm) were found to be collector distance of 12 cm, polymer solution concentration of 25% and applied voltage of 6 kV.

Removal of ecotoxicological matters from tannery wastewater using electrocoagulation reactor: modelling and optimization

This study investigated the possibilities of electrocoagulation reactor to reduce the colour, oil and grease and chemical oxygen demand (COD) from tannery industry wastewater using stainless steel electrodes. Effects of pH, electrolysis time, current density and NaCl dose were investigated using four factors three-level Box–Behnken response surface design coupled with response surface methodology. From the experimental results, second-order polynomial mathematical models were developed to describe the treatment process statistically. Analysis of variance was used to evaluate the adequacy of developed mathematical models. Three-dimensional (3D) response surface plots were constructed to study the interactive effects of process variables on the treatment efficiency. Optimum operating conditions such as pH of 9, electrolysis time of 40 min, current density 20 mAcm−2 and sodium chloride (NaCl) dose of 1,016 mg l−1 show 92, 95 and 80% of colour, oil and grease, and COD removal, respectively. The electrical energy consumption of the present treatment process in optimum condition was found to be 6 KWhm−3. The obtained results indicate that EC reactor is the best option to treat tannery industry wastewater in terms of removal efficiency and operating cost.

Response surface optimization of ultrasound assisted extraction of pectin from pomegranate peel

Ultrasound assisted extraction of pectin from waste pomegranate peel was investigated and optimized using Box–Behnken response surface design coupled with numerical optimization technique. The individual and interactive effect of process variables (solid-liquid ratio, pH, extraction time and temperature) on the pectin yield was studied. The experimental data obtained were analyzed by Pareto analysis of variance (ANOVA) and second-order polynomial models were developed using multiple regression analysis. The models developed from the experimental design were predictive and good fit with the experimental data with high coefficient of determination (R2) value. The optimal extraction condition was found to be 1:17.52g/ml of solid-liquid ratio, 1.27 of pH, 28.31min of extraction time and 61.90°C of extraction temperature respectively. Under the optimal conditions, experimental yield was very close to the predicted values.