scholarly journals Developing A New Empirical-Computational Method, for Accurate Acid- Base Quantitative Analysis

2019 ◽  
Vol 26 (3) ◽  
pp. 19-30
Author(s):  
Owolabi Rasheed Uthman ◽  
Akinjide Akinola ◽  
Mohammed Awwal Usman ◽  
Abubakar Adepitan
Keyword(s):  
Experimental Data ◽  
Regression Analysis ◽  
Response Surface ◽  
Polynomial Equation ◽  
Second Order ◽  
Computational Method ◽  
Interactive Effects ◽  
Coefficient Of Determination ◽  
Acid Base ◽  
Order Polynomial

The mole ratio of an acid base reaction is one of the important values to state the stoichiometric relationship between acids and bases. However, solving acid-base problems based on stoichiometry is still challenging for new chemists.This issue renders the use of a model for predicting the volume of the acid used an exciting endeavour in academia. This work was to study the individual and interactive effects of the titration parameters such as acid concentration, base concentration and the number of the indicator drops on the volume of acid used in the titration process, using methyl orange as an indicator.We also aimed to study the central composite design (CCD) model of response surface methodology (RSM) for experimental design and modelling of the process. The experimental data were analysed using analysis of variance (ANOVA) and fitted to a second-order polynomial equation using multiple regression analysis. The regression analysis showed a good fit of the experimental data to the second-order polynomial model with a coefficient of determination (R2) value of 0.9751 and model F-value of 43.37. The response surface and contour plots were generated from RSM tool for the interactive effects of the studied parameters on the volume of acid used. The developed model was further validated using existing acid-base titration problems from the Senior Secondary Certificate Examination (SSCE) past questions over 30 years. All observations indicated that the developed model was only valid for a monobasic acid.

scholarly journals Combined Surfactant and Enzyme-Assisted Extraction of Pectin from Hawthorn (Crataegus monogyna Jacq.) Fruits

2022 ◽  
Vol 51 (4) ◽  
pp. 733-742
Author(s):  
Anastasia Novikova ◽  
Liubov Skrypnik
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Polynomial Regression ◽  
Polynomial Equation ◽  
Second Order ◽  
Wild Fruits ◽  
Assisted Extraction ◽  
Order Polynomial ◽  
Extraction Parameters ◽  
Enzyme Assisted Extraction

Introduction. Commercial pectin is usually obtained from apples or citrus fruits. However, some wild fruits, such as hawthorn, are also rich in pectin with valuable nutritional and medical properties. The research objective was to study and improve the process of combined surfactant and enzyme-assisted extraction of pectin from hawthorn fruits. Study objects and methods. The study involved a 1% solution of Polysorbate-20 surfactant and a mix of two enzymes, namely cellulase and xylanase, in a ratio of 4:1. The response surface methodology with the Box-Behnken experimental design improved the extraction parameters. The experiment featured three independent variables – temperature, time, and solvent-to-material ratio. They varied at three levels: 20, 40, and 60°C; 120, 180, and 240 min; 15, 30, and 45 mL per g. Their effect on the parameters on the pectin yield was assessed using a quadratic mathematical model based on a second order polynomial equation. Results and discussion. The response surface methodology made it possible to derive a second order polynomial regression equation that illustrated the effect of extraction parameters on the yield of polyphenols. The regression coefficient (R2 = 98.14%) and the lack-of-fit test (P > 0.05) showed a good accuracy of the model. The optimal extraction conditions were found as follows: temperature = 41°C, time = 160 min, solvent-to-material ratio = 32 mL per 1 g. Under the optimal conditions, the predicted pectin yield was 14.9%, while the experimental yield was 15.2 ± 0.4%. The content of galacturonic acid in the obtained pectin was 58.5%, while the degree of esterification was 51.5%. The hawthorn pectin demonstrated a good complex-building ability in relation to ions of copper (564 mg Cu2+/g), lead (254 mg Pb2+/g), and cobalt (120 mg Co2+/g). Conclusion. Combined surfactant and enzyme-assisted extraction made improved the extraction of pectin from hawthorn fruits. The hawthorn pectin can be used to develop new functional products.

scholarly journals Application of response surface methodology for ultrasound-assisted rapid ‎adsorption of meso-tetrakis(4-sulfonatophenyl) porphyrin by copper ‎nanowire-loaded in activated carbon: Characterization, equilibrium and ‎kinetic modeling

2015 ◽  
Vol 17 (4) ◽  
pp. 756-770 ◽  
Keyword(s):  
Experimental Data ◽  
Response Surface Methodology ◽  
Activated Carbon ◽  
Response Surface ◽  
Polynomial Equation ◽  
Extraction Yield ◽  
Second Order ◽  
Ultrasonic Assisted ◽  
Isotherm And Kinetic Models ◽  
The Individual

<div> <p>The combined ultrasonic assisted/nanoparticle based procedure was described for an economical and rapid removal of meso-tetrakis (4-sulfonatophenyl) porphyrin (TSPP) by copper nanowires loaded on activated carbon (Cu-NW-AC). The synthesized Cu-NW-AC was investigated by scanning electron microscopy (SEM) and X-ray diffraction (XRD). Response surface methodology (RSM) combined with central composite design (CCD) give useful information about the individual contribution and interaction amoung variables correspound to above adsorption. In CCD, the effects of variables in the following range, pH (X<sub>1</sub>: 5.0-7.0), adsorbent dosage (X<sub>2</sub>: 0.021-0.051 g), initial TSPP concentration (X<sub>3</sub>: 3-15 mg l<sup>-1</sup>) and ultrasound time (X<sub>4</sub>: 2-10 min.) was investigated to obtain maximum adsorption effeciency. The experimental data were subsequently fitted to a second-order polynomial equation using multiple regression analysis by appropriate statistical methods. According to the results, the optimum adsorption conditions were found to be Cu-NW-AC = 0.04 g, TSPP = 6 mg l<sup>-1</sup>, pH = 5.5 and ultrasound time = 8.0 min. The experimental extraction yield under optimal conditions was found to be 97.60% which confirmed by three replicate at optimum conditions leading to removal percentage of 98.16%. The adsorption equilibrium isotherm and kinetic models investigation revealed the suitability of Langmuir isotherm and pseudo-second-order model for best predication of experimental data. Maximum monolayer capacity (Q<sub>m</sub>) calculated from Langmuir model was found to be 26.385 mg g<sup>-1</sup>.</p> </div> <p>&nbsp;</p>

The Optimization of Pb(II),Cu(II),Zn(II) and Cd(II) Ions Removal by Micro-Electrolysis Using Response Surface Methodology

2013 ◽  
Vol 800 ◽  
pp. 537-545
Author(s):  
Jian Ping Xu ◽  
Zhi Huang ◽  
Yan Ling Gao
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Mine Drainage ◽  
Polynomial Equation ◽  
Interactive Effects ◽  
Quadratic Model ◽  
Design Matrix ◽  
Box Behnken Design ◽  
Operating Variables ◽  
Order Polynomial

In this study, the Box–Behnken design matrix and response surface methodology (RSM) have been applied in the experiments to evaluate the interactive effects of four most important operating variables: pH (2.0–4.0), temperature (30–40°C )，iron/carbon ratio（1/2–3/2）and iron carbon amounts (2-4) on the removal of Pb (II), Cu(II)，Zn (II) and Cd (II) ions in acid mine drainage with micro-electrolysis (ME) . The total 29 experiments were conducted in the present study for the construction of a quadratic model. The independent variables have significant value 0.0001, which indicates the importance of these variables in the ME process. The values of “Prob > F” less than 0.0500 indicate that model terms are significant for the removal of Cr (VI), Ni (II) and Zn (II) ions. The regression equation coefficients were calculated and the data fitted to a second-order polynomial equation for removal of Pb (II), Cu(II)，Zn (II) and Cd (II) ions with ME.

Optimized Formulation of APN Toothpaste with Biochemical Materials Using Response Surface Methodology

2013 ◽  
Vol 676 ◽  
pp. 108-113
Author(s):  
Ting Kong ◽  
Chao Yan Zhang ◽  
Bin Bao ◽  
Long Sha ◽  
Zhen Wang ◽  
...  
Keyword(s):  
Experimental Data ◽  
Response Surface Methodology ◽  
Response Surface ◽  
Panax Notoginseng ◽  
Second Order ◽  
Polynomial Model ◽  
Composite Score ◽  
Optimum Formulation ◽  
Order Polynomial ◽  
Addition Amount

Response surface methodology(RSM) was used to optimize the formulation of one toothpaste with aglycone extracted from Panax notoginseng(APN). Biochemical materials are important components in toothpastes. The addition amount of APN, thickener, different ratios of humectant and friction agent were selected as three factors for the design. Our results showed that the experimental data could be adequately fitted into a second-order polynomial model. Addition amount of thickener and humectant : friction agent had a significant effect on the composite score. The optimum formulation for preparing APN toothpaste was predicted to be: APN, 0.12%; thickener, 1.58%; humectant : friction agent, 1.01.

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

2020 ◽  
Vol 14 (4) ◽  
pp. 590-596
Author(s):  
Nizamettin Demirkɪran ◽  
◽  
G. Deniz Turhan Özdemir ◽  
Merve Dardağan ◽  
◽  
...  
Keyword(s):  
Response Surface ◽  
Copper Concentration ◽  
Polynomial Equation ◽  
Interactive Effects ◽  
Metallic Aluminum ◽  
Process Variables ◽  
Aluminum Particles ◽  
Surface Method ◽  
Order Polynomial ◽  
Optimal Values

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.

Optimization of Manufacturing Process of Traditional Algerian Jben Cheese Using Response Surface Methodology (RSM)

2018 ◽  
Vol 8 (1) ◽  
pp. 31-42
Author(s):  
M. Amimour ◽  
T. Idoui ◽  
A. Cheriguene
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Manufacturing Process ◽  
Milk Powder ◽  
Statistical Design ◽  
Polynomial Equation ◽  
Enzymatic Extract ◽  
Traditional Cheese ◽  
Order Polynomial ◽  
Predicted Values

The Aim of this study was to develop an optimized method for manufacturing process of traditional Algerian Jben cheese, using response surface methodology (RSM). In order to develop the objective method of making this traditional cheese, several factors have been studied and a Plackett-Burman statistical design was applied. The effects of the four screened factors (enrichment with milk powder, 10 - 20 g/l; pH of milk, 5.75 - 6.75, enzymatic extract dose, 0.5 - 1.5 ml and coagulation temperature 40 - 60 °C) on the response were investigated, using a Box-Behnken statistical design. Multiple regression analysis was used so that experimental data fits to a second-order polynomial equation. This multiple analysis showed that the model explains about 90.73% of the variation. Based on statistical results, it can be noticed that enrichment with milk powder and pH of milk (Ë‚0.0001***) were highly significant factor influincing cheese yield. The optimal production parame-ters that maximized cheese product (20 g/l enrichment with milk powder, 5.75 pH of milk, 1.29 ml enzymatic extract dose and 60°C coagulation temperature) and the maximal predicted cheese yield (52.68 % ) were found out through response surface methodology. Under these conditions, a verification experiment was carried out and cheese yield was found to be 49.46 %. The overall percentage of agreement for the experimental results (more than 93 % validity) with the predicted values indicates the validation of the statistical model and the success of the optimization process.

scholarly journals Modeling of rose coco beans using twenty four points optimum second order rotatable design

2017 ◽  
Vol 5 (2) ◽  
pp. 96
Author(s):  
Isaac Tum ◽  
John Mutiso ◽  
Joseph Koske
Keyword(s):  
Response Surface ◽  
Maximum Yield ◽  
Second Order ◽  
Three Dimensions ◽  
Coefficient Of Determination ◽  
Yield Response ◽  
Efficient Production ◽  
Phosphorus And Potassium ◽  
Nitrogen Phosphorus ◽  
Rotatable Design

The response surface methodology (RSM) is a collection of mathematical and statistical techniques useful for the modeling and analysis of problems in which a response of interest is influenced by several variables, and the objective is to optimize the response. The objective of the study was to model the rose coco beans (Phaseolus vulgaris) through an existing A-optimum and D-efficient second order rotatable design of twenty four points in three dimensions in a greenhouse setting using three inorganic fertilizers, namely, nitrogen, phosphorus and potassium. Thus, the objective of the study was accomplished using the calculus optimum value of the free/letter parameter f=1.1072569. This was done by estimating the parameters via least square's techniques, by making available for the yield response of rose coco beans at calculus optimum value design for the first time. The results showed that, the three factors: nitrogen, phosphorus, and potassium contributed significantly on the yield of rose coco beans (p<0.05). In GP3G, the second-order model was adequate for 1% level of significance with p value of 0.0034. The analysis of variance (ANOVA) of response surface for rose coco yield showed that this design was adequate due to satisfactory level of a coefficient of determination, R2, 0.8066 and coefficient variation, CV was 10.30. This study demonstrated the importance of statistical methods in the optimal and efficient production of rose coco beans. We do recommend a randomize screening of all the fertilizer components with which it has influence on rose coco beans be done to ascertain the right initial amount of each fertilizer that could achieve maximum yield than this study realized.

Enhanced Alkali Pretreatment of Narrow Leaves Cattail by Response Surface Methodology

2014 ◽  
Vol 875-877 ◽  
pp. 1637-1641
Author(s):  
Arrisa Sopajarn ◽  
Chayanoot Sangwichien
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Residence Time ◽  
Preliminary Test ◽  
Polynomial Equation ◽  
Alkali Concentration ◽  
Pretreatment Condition ◽  
Order Polynomial ◽  
Optimized Conditions ◽  
Central Composite

The purpose of this work is to develop a pretreatment process of lingo-cellulosic ethanol production from narrow leaves cattail (Typha angustifolia) by using alkali catalysis with the response surface methodology (RSM) as a central composite design (CCD). The first step, LiOH, NaOH, and KOH were used as catalytic alkali for preliminary test. Second, the suitable alkali from first step was selected to optimize of pretreatment condition of three independent variables (alkali concentration, temperature, and residence time) that varies at CCD five codes (-2, -1, 0, 1, 2). Sodium hydroxide (NaOH) is the proper alkali because it could increase cellulose more than KOH and nearby LiOH while it is cheapest. RSM result shows the optimized pretreatment condition based on cellulose increased which obtained from this study that is NaOH 5 % w/v at 100 °C and residence time for 120 min. Beside, this condition was analyzed using an ANOVA with a second order polynomial equation after eliminated non-significant terms. At the optimized conditions, cellulose increased, hemicellulose decreased and weight recovery were achieved 77.81%, 80.59, and 41.65%, respectively. Moreover, the model was reasonable to predict the response of strength with less than 5% error.

Soil-line vegetation indices for corn nitrogen content prediction

2012 ◽  
Vol 26 (2) ◽  
pp. 103-108 ◽  
Author(s):  
N. Bagheri ◽  
H. Ahmadi ◽  
S. Alavipanah ◽  
M. Omid
Keyword(s):  
Nitrogen Content ◽  
Vegetation Indices ◽  
Polynomial Equation ◽  
Measured Data ◽  
Second Order ◽  
Soil Line ◽  
Order Polynomial ◽  
Canopy Nitrogen ◽  
Order Polynomial Equation ◽  
Corn Canopy

Soil-line vegetation indices for corn nitrogen content prediction The soil-line vegetation indices for prediction of corn canopy nitrogen content were investigated. Results indicated that the vegetation indices applied were correlated with corn canopy nitrogen content and the wavelengths between 630-860 nm are suitable for nitrogen diagnosis. The second-order polynomial equation was the best model for nitrogen content prediction among different regression types. Analyses based on both predicted and measured data were carried out to compare the performance of existing vegetation indices.

scholarly journals On-Board Georeferencing Using FPGA-Based Optimized Second-Order Polynomial Equation

2019 ◽  
Vol 11 (2) ◽  
pp. 124 ◽  
Author(s):  
Dequan Liu ◽  
Guoqing Zhou ◽  
Jingjin Huang ◽  
Rongting Zhang ◽  
Lei Shu ◽  
...  
Keyword(s):  
Real Time ◽  
Spatial Data ◽  
Coordinate Transformation ◽  
Polynomial Equation ◽  
Remotely Sensed ◽  
Second Order ◽  
Bilinear Interpolation ◽  
Remotely Sensed Imagery ◽  
Order Polynomial ◽  
Mean Square Errors

For real-time monitoring of natural disasters, such as fire, volcano, flood, landslide, and coastal inundation, highly-accurate georeferenced remotely sensed imagery is needed. Georeferenced imagery can be fused with geographic spatial data sets to provide geographic coordinates and positing for regions of interest. This paper proposes an on-board georeferencing method for remotely sensed imagery, which contains five modules: input data, coordinate transformation, bilinear interpolation, and output data. The experimental results demonstrate multiple benefits of the proposed method: (1) the computation speed using the proposed algorithm is 8 times faster than that using PC computer; (2) the resources of the field programmable gate array (FPGA) can meet the requirements of design. In the coordinate transformation scheme, 250,656 LUTs, 499,268 registers, and 388 DSP48s are used. Furthermore, 27,218 LUTs, 45,823 registers, 456 RAM/FIFO, and 267 DSP48s are used in the bilinear interpolation module; (3) the values of root mean square errors (RMSEs) are less than one pixel, and the other statistics, such as maximum error, minimum error, and mean error are less than one pixel; (4) the gray values of the georeferenced image when implemented using FPGA have the same accuracy as those implemented using MATLAB and Visual studio (C++), and have a very close accuracy implemented using ENVI software; and (5) the on-chip power consumption is 0.659 W. Therefore, it can be concluded that the proposed georeferencing method implemented using FPGA with second-order polynomial model and bilinear interpolation algorithm can achieve real-time geographic referencing for remotely sensed imagery.

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