Second-order Polynomial Regression Equation Research Articles

Waste-derived activated carbons for effective adsorptive removal of strontium, barium, and binary pollutants: A response surface methodology study

A double-pronged approach to pollution management is proposed by sustainably managing solid wastes and converting them to activated carbons that are then utilized for water treatment. In this study, gas-to-liquids (GTL) derived biosolids, carboard and their mixed samples are used to produce the activated carbons. In a laboratory batch study, a Box-Behnken experimental design was used with four factors and three levels to optimize the removal of single component strontium and barium, and the binary system of pollutants from an aqueous solution. The design incorporated response surface modeling (RSM) techniques with a total of 29 different experimental data points collected and analyzed in this study. The study was conducted considering four parameters: the initial pH of the solution (ranging from 4.0 to 8.0), temperature (ranging from 20 to 40 ℃), the percentage of cardboard (fixed at 0 %, 50 %, and 100 %), and the amount of adsorbent (between 0.05 and 0.5 g). These factors were assigned three levels, represented as −1, 0, and 1. A second-order polynomial regression equation was then developed to estimate the responses. The statistical significance of the independent variables and their interactions was assessed using analysis of variance (ANOVA) with a 95 % confidence level (α = 0.05). The results revealed that only temperature and dosage show significant effects on the responses and that optimum values of the selected parameters were obtained by solving the prediction equations, which were validated with less than 4 % error %. In an attempt to optimize the factors, a pH of 5.5, temperature of 40 ℃ and dose of 0.3 g is found for all three samples. Validation results for optimization also proved that varying the percentage cardboard showed little difference in the percentage removal of all the pollutants. The results from this study can be directly applied for any such systems trying to optimize these parameters and the prediction equations can be utilized effectively.

An Optimization Study of Advanced Fenton Oxidation Methods (UV/Fenton–MW/Fenton) for Treatment of Real Epoxy Paint Wastewater

The use of various advanced oxidation methods in the treatment of wastewater has become the subject of many studies published in recent years. In particular, it is exceedingly significant to compare these treatment methods for industrial wastewater to reduce environmental effects and optimize plant operations and economics. The present study is the first to deal with the treatability of real epoxy paint wastewater (EPW) using MW- and UV-assisted Fenton processes within an optimization framework. A three-factor, three-level Box–Behnken experimental design combined with response surface methodology (RSM) was conducted for maximizing the chemical oxygen demand (COD) and color removal efficiencies of ultraviolet (UV)/Fenton and microwave (MW)/Fenton processes in the treatment of the real epoxy paint wastewater (EPW, initial COD = 4600 ± 90 mg/L, initial color = 114 ± 4 Pt-Co), based on 15 different experimental runs. Three independent variables (reaction time ranging from 20 to 60 min (UV) and from 5 to 15 min (MW), power ranging from 20 to 40 W (UV) and from 300 to 600 W (MW), and H2O2/Fe2+ ratio ranging from 0.2 to 0.6 (for both UV and MW)) were consecutively coded as A, B, and C at three levels (−1, 0, and 1), and four second-order polynomial regression equations were then derived to estimate the responses (COD and color removals) of two distinct systems. The significance of the independent model components and their interrelations were appraised by means of a variance analysis with 99% confidence limits (α = 0.01). The standardized differences of the independent variables and the consistency between the actual and predicted values were also investigated by preparing normal probability residual plots and experiment-model plots for all processes. The optimal operating conditions were attained by solving the quadratic regression models and analyzing the surface and contour plots. UV/Fenton and MW/Fenton processes, which constitute combined Fenton processes, were performed using advanced oxidation methods, while Fenton processes were utilized as the standard method for wastewater treatment. When UV/Fenton and MW/Fenton processes were applied separately, the COD removal efficiencies were determined to be 96.4% and 95.3%, respectively. For the color parameter, the removal efficiencies after the application of both processes were found to exceed 97.5%. While these efficiencies were achieved in 1 h with a 38 W UV unit, they were achieved in 15 min with a MW power of 570 W. According to the RSM-based regression analysis results, the R2 values for both processes were greater than 0.97 and p values were less than 0.003.

Effects of Sodium Butyrate Supplementation in Milk on the Growth Performance and Intestinal Microbiota of Preweaning Holstein Calves.

The aim of the present study was to investigate the effects of sodium butyrate (SB) supplementation on the growth and intestinal microbiota of preweaning dairy calves. Eighty newborn Holstein calves (56 female and 24 male) were randomly allocated to four treatment groups with 20 calves each (14 female and 6 male). The suckling milk for the four treatments was supplemented with 0, 4.4, 8.8, or 17.6 g/d SB. During the 6-week experiment, dry matter intake was recorded daily, body weight was measured weekly, and rectal fecal samples were collected in the 2nd week. The V3-V4 hypervariable regions of the microbial 16S rRNA were amplified and then sequenced. SB supplementation elevated average daily gains (ADGs) in the first and second weeks. The optimal SB supplementation level for the whole preweaning period was 8.78 g/d, as revealed by analyzing the whole preweaning period ADG using second-order polynomial regression (quadratic) equations. The alpha diversity (Shannon diversity index), beta diversity, core phyla and genera, and function of the intestinal microbiota were affected by SB supplementation. In addition, the Shannon diversity index and core phyla and genera of the intestinal microbiota were correlated with calf growth-related indices. Overall, SB supplementation in suckling milk improved the growth performance and intestinal microbiota development of dairy calves in a quadratic manner, and regression analysis indicated an optimal supplementation level of 8.78 g/d.

Development of a potassium-based soil washing solution using response surface methodology for efficient removal of cesium contamination in soil

The overuse of chelating soil washing agents for removal of heavy metal can release soil nutrients and negatively affect organisms. Therefore, developing novel washing agents that can overcome these shortcomings is necessary. In this study, we tested potassium as a main solute of novel washing agent for cesium-contaminated field soil, owing to the physicochemical similarities between potassium and cesium. Response surface methodology was combined with a four-factor, three-level Box–Behnken design to determine the superlative washing conditions of the potassium-based solution for the removal of cesium from the soil. The parameters that were considered were the following: potassium concentration, liquid-to-soil ratio, washing time, and pH. Twenty-seven sets of experiments were conducted using the Box–Behnken design, and a second-order polynomial regression equation model was obtained from the results. Analysis of variance proved the significance and goodness of fit of the derived model. Three-dimensional response surface plots displayed the results of each parameter and their reciprocal interactions. The washing conditions that achieved the highest cesium removal efficiency (81.3%) in field soil contaminated at 1.47 mg/kg were determined to be the following: a potassium concentration of 1 M, a liquid-to-soil ratio of 20, washing time of 2 h, and a pH of 2.

Leaching of Ibute-Nze kaolin iron-oxide impurity with oxalic acid process optimization of dissolution conditions using response surface methodology

The goal of this research was to remove iron oxide from Ibute-Nze kaolin by dissolving the clay mineral in an aqueous oxalic acid solution and optimizing the process. The chemical composition of the raw and modified clay was determined using x-ray fluorescence, and the morphology of the solid sample was determined using a scanning electron microscope. The best conditions for the oxalic acid leaching of iron-oxides impurity from Ibute-Nze kaolin were determined using response surface methodology based on Box-Behnken design. The studies were carried out within the following process parameter ranges: 40–90 leaching temperature; 0.075-0.355mm particle size; 1–6 mol/dm3 acid concentration; 0.02–0.12 g/cm3 kaolin sample to acid ratio and 30-240 min contact time. The characterization revealed that Ibute-Nze clay is kaolinitic in nature and calcination at 750 opens more pores for its leaching. According to the analysis of variance, a second-order polynomial regression equation provided the best fitting for the experimental data. The predicted and experimental response values were shown to be correlated (R2 = 0.9276) in the experimental runs. The following were found to be the best conditions for the leaching process variables: 83.2051 leaching temperature, 0.0827mm particle size, 3.6179mol/dm3 acid concentration; 0.0287g/cm3 kaolin to acid ratio and 217.932min reaction time. The chemical leaching process was 92.6035 per cent under these conditions, which made the clay good for industrial applications.

Friction coefficient calibration of corn stalk particle mixtures using Plackett-Burman design and response surface methodology

The accuracy of the particle parameter settings directly affects the reliability of the simulation results. The discrete element method used a repose angle test to address incorrect particle parameter settings when throwing straw particles thrown by a chaff cutter. The tests calibrated the static and rolling friction coefficients using the repose angle of a mixture of maize stalk internodal tissue, pith, and nodal tissue particles as response indicators. Physical tests measured particle materiality parameters and contact parameters to provide data for the simulation tests. A Plackett-Burman design was performed to test the significance of the parameters to be calibrated. The results show that the static friction coefficient of Rind-Node, the rolling friction coefficient of Rind-Rind, the rolling friction coefficient of Pith-Pith, and the rolling friction coefficient of Pith-Iron have a significant effect on the repose angle. The purpose of the steepest ascent test is to narrow down the optimization range of the parameters. The central composite design was used to determine the DEM parameters' levels and quantify their effects. The central composite design test modeled a second-order polynomial regression equation for the repose angle and significance parameters. The physical test values were used as the target values for the optimization solution to obtain a calibrated and better combination of simulation parameters. The two-sample heteroskedasticity t-test showed no significant difference between the simulated and experimental values. The maximum relative error was 1.75%, the mean relative error was only 0.29%, verifying the reliability and authenticity of the simulation test. These parameters provide a basis for future work, such as the design of a corn stalk processing machine and the discrete-element study on the motion of corn stalk particles inside such machines.

Response surface modeling with Box-Behnken design for strontium removal from soil by calcium-based solution.

Owing to its physicochemical similarity to strontium (Sr), calcium (Ca) was tested as a key component of a soil washing solution for Sr-contaminated soil collected near a nuclear power plant. A four-factor, three-level Box-Behnken experimental design combined with response surface modeling was employed to determine the optimal Sr washing condition for Ca-based solution. The Ca concentration (0.1-1M), liquid-to-soil ratio (5-20), washing time (0.5-2h), and pH (2.0-7.0) were tested as the independent variables. From the Box-Behnken design, 27 sets of experimental conditions were selected, and a second-order polynomial regression equation was derived. The significance of the independent parameters and interactions was tested by analysis of variance. Ca concentration was found to be the most influential factor. To determine whether the four variables were independent, three-dimensional (3D) response surface plots were established. The optimal washing condition was determined to be as follows: 1M Ca, L/S ratio of 20, 1h washing, and pH=2. Under this condition, the highest Sr removal efficiency (68.2%) was achieved on a soil contaminated with 90.1mg/kg of Sr. Results from five-step sequential extraction before and after washing showed that 84.0% and 82.9% of exchangeable and carbonate-bound Sr were released, respectively. In addition, more tightly bound Sr, such as Fe/Mn oxides-bound and organic matter-bound Sr, were also removed (86.2% and 64.5% removal, respectively).

The results of applying the method of mathematical statistics to predict technological effectiveness of hydraulic fracturing

The article discusses the apparatus of mathematical statistics for predicting the technological effectiveness of hydraulic fracturing. The authors made an attempt to improve the methods for processing experimental data in the conditions of a small sampling. The main method used for solving this problem was the second-order regression equation in the form of a polynomial. The comparison of calculated and actual data on technological results for hydraulic fracturing based on the solution of second-order polynomial regression equations for different fields showed a high level of convergence, which allows us to conclude that the proposed methodology for constructing a regression equation in the form of a power polynomial is acceptable.

Optimization and quality attributes of novel toast breads developed based on the antistaling watermelon rind powder

In the current research, production of watermelon rind (WMR) powder was studied as a promising additive to improve the quality characteristics of toast breads. The main formulation (WMR (4.6–11.4%)), and bread-baking process (temperature (166–233 °C) and time (17–33 min)) parameters using response surface methodology (RSM) were optimized to retard the acceleration of staling rate in toast breads. The second-order polynomial regression equations (R2 > 0.939) were adequately fitted for all response variables. The highest moisture (22%), volume (1431 cm3), and organoleptic acceptability (8.10) values and the lowest firmness (10.50 N) and total color difference (9.80) values were achieved under the following conditions: WMR concentration of 9.06%, baking temperature of 206.66 °C and baking time of 20 min. The analysis of dough farinographic and extensographic characteristics showed a significant more water absorption (72.5%), development (6.7 min) and stability (7.8 min) time, and extensibility (143 mm) values for the optimal sample compared to the control. Scanning electron microscopy demonstrated that the thicker cell wall induced by WMR in the optimal bread (183.54 μm) than the control (78.39 μm) was able to maintain air bobbles during the storage time. A negligible staling rate was also found for the optimal breads with the lowest moisture, textural, color and sensory changes.

Mapping of Wear Mechanism for Mechanical Alloyed Aluminum Carbon Nanotube Composites—An In Situ Analysis

AbstractThis research work investigates the root causes of wear on the tribo surface of mechanically alloyed Aluminum/CNT composite through a simulated in situ analysis. The wear maps are developed using the second-order polynomial regression equation for the Aluminum/CNT composite to discriminate the wear mechanisms at different levels of their influencing factors and milling parameters. As a result, the predominant wear mechanism is identified as surface fatigue for Aluminum/CNT composite under high loading dry sliding condition. This study also reveals the modes for eliminating the severe wear at the tribo-surfaces. Aluminum/CNT1 wt% composite fabricated with the mechanical alloying parameters above 6 h of milling time and above 5 rps of milling speed eliminates the delamination under low level of tribological parameters, and it achieves the minimal wear-rate of 30.5 × 10−6 g/m and coefficient of friction (CoF) of 0.346.

Exploration of nature inspired Grey wolf algorithm and Grey theory in machining of multiwall carbon nanotube/polymer nanocomposites

The nanosize of reinforcement creates a better synergistic effect in epoxy composites. This effect enhances the desired properties of multifunctional components used in aircraft, automotive, sports, biomedical, sensors, etc. In this series, MWCNT/epoxy nanocomposites possess high strength, reduced weight, moisture and chemical resistant properties. The machining performance of MWCNT nanocomposites is remarkably distinct from metallic materials. This article explores the machining aspects of MWCNT composites using Grey relation analysis and relatively advanced nature-inspired Grey wolf optimization (GWO). Machining (milling) experiments consider a real-world problem framed on Taguchi L27 OA. The second-order polynomial regression equation shows a desirable agreement between experimental and predicted values. The average surface roughness, cutting force and MRR significantly achieved the desired enhancements. The optimal setting of GRA based Grey wolf optimizer are found as 0.5 wt.% MWCNT, 1500 rpm spindle speed, 50 mm/min feed rate and 3 mm depth of cut. It was noticed that the depth of cut plays a prominent role in affecting the machining characteristics. The outcomes of the confirmatory test show that GRA-GWO is more feasible than the traditional GRA method.

Response Surface Methodology (RSM) for Statistical Optimization of Cd2+ Removal Using Modified Zn2Al-layer Double Hydroxide by Quinoline Yellow

Modified Zn2Al-layered double hydroxide (LDH) intercalated with Quinoline Yellow (Q) (Zn2Al-LDH/Q) was prepared by a facile and simple method and then used to remove of Cd2+ ions from water. The chemical composition and morphology of Zn2Al-LDH/Q was investigated by X-ray diffraction (XRD), Brunauer-Emmett-Teller (BET), Field emission Scanning electron microscopy (FE-SEM) and Energy-dispersive X-ray spectroscopy. Response surface methodology was employed to optimize the adsorption parameters of Cd2+ Such optimization was undertaken to ensure a high efficiency over the experimental ranges employed and to evaluate the interactive effects of the initial concentration of Cd2+, pH, adsorbent dosage, temperature and contact time in order to improve the conditions employed in the batch process. The analysis of variance (ANOVA) indicated that a second-order polynomial regression equation was the most appropriate polynomial for fitting the experimental data. The experimental confirmation tests showed a correlation between the predicted and experimental responses (R2). The optimum adsorption parameters were predicted as an initial Cd2+ concentration of 35 mg l-1, a pH value of 4.17, the adsorbent dosage of 0.03 g/L, a temperature of 32.5 °C and contact time of 51 min. Under optimum conditions, the highest adsorption efficiency and maximum adsorption capacity were 45% and 12.18 mg/g, respectively.

Multi-factorial Analysis on Vault Stability of an Unsymmetrically Loaded Tunnel Using Response Surface Method

This study investigated the vault settlement characteristics of an unsymmetrically loaded tunnel which was excavated by annular excavation via core rock support method. Response surface methodology (RSM) was employed to design the experiments, evaluate the results with the purpose of optimizing the value of design parameters for reducing the vault settlement. The parameters such as horizontal distance, step length, tunneling depth, width of core rock, strength of surrounding rocks and support strength were firstly examined, and a second-order polynomial regression equation was then derived to predict the responses of vault settlement. The percentage contribution, validity of model and effects of different parameters as well as their interactions were assessed by analysis of variance (ANOVA). In the order from high to low effect, these parameters are strength of surrounding rocks, support strength, horizontal distance, width of core rock, tunneling depth, and step length. The results indicated that the influence of uncontrollable factors (i.e. strength of surrounding rocks, tunneling depth, and horizontal distance) on the vault settlement can be reduced through the adjustment of controllable factors (i.e. Width of core rock, step length, and support strength). Moreover, the proposed method in this paper was validated with results of field test measurement and simulation calculation which verified its feasibility.

Response Surface Methodology for Optimizing Adsorption Process Parameters of Amaranth Removal Using Magnetic Layer Double Hydroxide (Fe3O4/ZnFe-LDH)

ABSTRACT Response surface methodology was employed to optimize the adsorption parameters of Amaranth onto magnetic layer double hydroxide (Fe3O4/ZnFe-LDH). Such optimization was undertaken to ensure a high efficiency over the experimental ranges employed, and to evaluate the interactive effects of the initial concentration of Amaranth, pH, adsorbent dosage, temperature and contact time on the adsorption process in order to improve the conditions employed in the batch process. A total of 32 desorption experimental runs were carried out employing the detailed conditions designed by response surface methodology based on the Box–Behnken design. The analysis of variance (ANOVA) indicated that a second-order polynomial regression equation was the most appropriate polynomial for fitting the experimental data. The experimental confirmation tests showed a correlation between the predicted and experimental responses (R2). The optimal point obtained was located in the valid region and the optimum adsorption parameters were predicted as an initial Amaranth concentration of 70.93 mg/L, a pH value of 3.6, adsorbent dosage of 0.01 g, a temperature of 31.82°C and contact time of 16.83 min.

Diaphragmatic shear modulus at various submaximal inspiratory mouth pressure levels

This study assessed the shear modulus of the diaphragm at various submaximal inspiratory mouth pressure levels by ultrasound shear wave elastography. In 14 healthy male subjects, diaphragmatic shear moduli were assessed at end expiration during resting breathing and at submaximal inspiratory tasks at 15, 30, 45, 60, and 75% of the maximal inspiratory mouth pressure. The shear modulus increased along with mouth pressure, and the mouth-pressure–shear-modulus relationship fit the second-order polynomial regression equation (r2 = 0.99 ± 0.01; all subjects, r2 ≥ 0.95) better than it did the simple linear regression equation (r2 = 0.94 ± 0.05; 8/14 subjects, r2 ≥ 0.95). The second regression coefficient in the second-order polynomial equation was a negative value in 10 of 14 subjects, which indicates that the second-order polynomial regression equation opened downwards. These findings suggest that the diaphragmatic shear modulus increases along with inspiratory mouth pressure, but the rate of increase slows when the pressure reaches higher levels.

Single-Parameter Thin-Layer Drying Equations for Long-Grain Rice

Abstract. The use of multiple parameters in thin-layer drying equations makes it difficult to compare and quantify the impact of drying air temperature, relative humidity, and other factors on the drying characteristics of an agricultural crop. In this study, two single-parameter equations are proposed to quantify thin-layer drying characteristics of contemporary long-grain rice cultivars grown in the Mid-South U.S. Drying runs were first performed to obtain drying curves for cultivar ‘Roy J’ under 18 air conditions; several drying equations were evaluated for their fit to each drying curve. The proposed single-parameter equations (modified Page equation and infinite-series diffusion equation) described the experimental drying data very accurately; the root mean square errors in moisture ratio obtained for the modified Page and infinite-series diffusion equations varied in the ranges of 0.2 to 1.4 and 0.3 to 1.5 percentage points, respectively. The dependence of drying air temperature and relative humidity on drying parameters of the modified Page and infinite-series diffusion equations was described by second-order polynomial regression equations. The impact of harvest moisture content on the drying characteristics of rice was observed to be negligible. The validity of the developed single-parameter equations was also evaluated for five other long-grain rice cultivars; for these cultivars, the maximum errors in the moisture ratio prediction using the modified Page and infinite-series diffusion equations were 2.9 and 3.4 percentage points, respectively. This study provides thin-layer drying data for contemporary rice cultivars in the Mid-South U.S. The resulting thin-layer drying equations are expected to improve the accuracy of deep-bed drying models. While the proposed single-parameter equations were tested only for long-grain rice, the methodology presented in this research could be used to develop similar single-parameter thin-layer drying equations for short-grain and medium-grain rice, as well as other agricultural crops. As such, these equations could be readily used in quantifying the impacts of air and rice variables on drying rates. Keywords: Mathematical modeling, Rice, Thin-layer drying.

Parametric Optimization of Biohydrogen Production from Potato Waste and Scale-Up Study Using Immobilized Anaerobic Mixed Sludge

Response surface methodology (RSM) using the central composite design (CCD) approach was used in the parametric optimization of biohydrogen production from potato waste and the scale-up study was investigated using immobilized anaerobic mixed sludge. A two-level-four-factor (24)-CCD obtained via a statistical software (STATISTICA 8 release 7) was used to generate 26 fermentation experiments. The experimental results were used to generate a second-order polynomial regression equation relating the biohydrogen production to the parameters considered (potato waste concentration, pH, temperature, and fermentation time). The optimum conditions for biohydrogen production were 39.56 g/L, 7.86, 37.87 °C and 82.58 h for potato waste concentration, pH, temperature, and fermentation time, respectively with a corresponding biohydrogen yield of 68.54 mL H2/g total volatile solids (TVS). A coefficient of determination (R2) of 0.99 was obtained by solving the polynomial regression equation. The obtained optimized conditions were further validated experimentally resulting in biohydrogen yield of 79.43 mL H2/g TVS, indicating a 15.9% biohydrogen increase. Scale-up conducted at the validated optimized conditions with the immobilized bacteria generated 298.11 mL H2/g TVS with maximum fraction of 56.38%. Therefore, these results demonstrate the potential of up-scaling biohydrogen production using immobilized bacteria which could be instrumental towards its large-scale production.

Optimization of adsorption process parameters by response surface methodology for hexavalent chromium removal from aqueous solutions using Annona reticulata Linn peel microparticles.

Fruit peel microparticles of Annona reticulata Linn were used as biosorbent for the sequestration of hexavalent chromium (CR(VI)). Characterization of the biosorbent was done using scanning electron microscopy-energy dispersive X-ray spectroscopy (SEM-EDXS), Fourier transfer infrared spectroscopy (FTIR), gas chromatography-mass spectrometry (GCMS), carbon, hydrogen, nitrogen and sulphur (CHNS) elemental analysis, mercury intrusion porosimetry and point of zero charge. Influential parameters were optimized using response surface methodology (RSM) with a total of 17 experimental runs based on the Box-Behnken design and found to be pH 1.0, temperature 25 °C and 100 mg/L initial chromium concentration. pH and concentration were found to be more influential than temperature. The analysis of variance indicated that a second-order polynomial regression equation was the most suitable for fitting the experimental data. The experimental runs showed a good correlation with the predicted responses (R2 = 0.9956). The biosorption process fitted well with the Langmuir isotherm with an adsorption capacity of 108. 32 mg/g out of the other isotherms such as Freundlich and Dubinin-Radushkevich that were analyzed. Non linear pseudo first order, pseudo second order, and intraparticle diffusion kinetics were applied to describe the interaction between the biosorbent and Cr(VI). Desorption and regeneration performances showed that fruit peels of Annona reticulata Linn can be an environmental friendly option for hexavalent chromium removal from aqueous solutions.

Optimization of carpet waste fibers and steel slag particles to reinforce expansive soil using response surface methodology

Expansive soils exhibit great volume change with any moisture variation. In this paper, using carpet waste fibers and steel slag as an environmental friendly additives were taken into account to overcome the swelling and weakness of the expansive soil. Response surface methodology (RSM) was employed to design the experiments, evaluate the results and finally optimize the content of slag-fiber mixture for achieving appropriate values of swell percent, swelling pressure and unconfined compressive strength (UCS). Three independent variables including slag content (0–25% by dry weight of the soil), carpet waste fiber (0.2–3% by dry weight of the soil) and aspect ratio of fibers L/d (5–45) were considered and transformed to coded value, and a second-order polynomial regression equation was then derived to predict responses. The percentage contribution, validity of model and significance of independent variables and their interaction were assessed by analysis of variance (ANOVA). The optimum values of three independent variables was suggested as 14% slag and 0.78% fiber with fiber aspect ratio of 45 to improve swell percent, swelling pressure and UCS 89%, 84%, and 111%, respectively. The results showed that both chemical modification and mechanical reinforcement by adding fibers and slag are efficient methods to improve general properties of expansive clayey soil.

Optimization of process variables and mechanism of arsenic (V) adsorption onto cellulose nanocomposite

Optimization of process variables for arsenic (V) adsorption onto some novel adsorbent, the cerium loaded cellulose nanocomposite bead, was made using response surface methodology, a popular statistical design for chemical experiments. The adsorbent was characterized for its physicochemical, spectral, surface and thermal nature. The influence and significance of experimental variables viz. pH, initial arsenic (V) concentration, adsorbent dose, contact time and temperature on the adsorption capacity (response) was estimated from fractional factorial design (25–1). The interactive and combined effects of significant variables were evaluated from central composite design and subsequent analysis of variance (ANOVA). The guiding parameters such as F- (58.45) and P-value (<0.0001) indicate that the design is statistically significant. A second-order polynomial regression equation is developed to predict the response at the optimized condition. A high value of regression coefficient (R2=0.9832) implies the validity of the model. Kinetic study reveals that the adsorption follows first order pathway. Diffusion phenomenon, particularly film diffusion prevails over the mass transport in governing the overall rate having activation energy of 19.34kJmol−1. Desorption of arsenic was found effective with NaOH (10−2N) and 98% elution was achieved. The regenerated adsorbent bead can be reused for As(V) adsorption up to four successive cycles. The mechanism of As(V) adsorption is assessed to be electrostatic rather than ion exchange as evaluated from mean free energy change of adsorption using Dubinin Raduskevich model. The method has been successfully applied for removal and estimation via recovery of arsenic (V) from different water samples.