scholarly journals Preparation of High-Performance Adsorbent From Low-Cost Agricultural Waste (Peanut Husk) Using Full Factorial Design: Application to Dye Removal

2020 ◽  
Vol 10 (6) ◽  
pp. 6619-6628 ◽  
Keyword(s):  
Activated Carbon ◽  
Factorial Design ◽  
Removal Efficiency ◽  
Large Scale ◽  
Dye Removal ◽  
Low Cost ◽  
Agricultural Waste ◽  
Full Factorial Design ◽  
Adsorbent Dosage ◽  
Full Factorial

Dye pollution becomes one of the significant environmental concerns nowadays. The adsorption technique is a potent method for the removal of the dye from wastewater effluents. Conventional activated carbon is one of the best adsorbents for dye removal. However, it is constraint due to high cost, and problems with regeneration hamper large scale applications. The alternative method using low-cost adsorbent is being introduced to replace the activated carbon since they are available in large quantities, renewable and inexpensive. Hence, peanut husk (Canavalia Ensiformis) as absorbent was investigated for its potential in Malachite Green (MG) dye removal. The effects of dye concentration (25 and 100 mg/L), temperature (30 and 60 °C), and adsorbent dosage (25 and 100 mg) on MG dye removal percentage were designed and optimized using two levels full factorial design. Based on the optimization process, it was determined that the 25 mg/L of dye concentration, 60 °C of temperature, and 100mg of adsorbent dosage resulted in the highest removal efficiency of 84.85 % and 91.83 % for untreated and treated adsorbent, respectively. In conclusion, treated peanut husk has shown its great potential as low-cost adsorbent based on the removal efficiency.

scholarly journals Full Factorial Experimental Design Analysis of Reactive Dye Removal by Carbon Adsorption

2013 ◽  
Vol 2013 ◽  
pp. 1-13 ◽  
Author(s):  
N. Özbay ◽  
A. Ş. Yargıç ◽  
R. Z. Yarbay-Şahin ◽  
E. Önal
Keyword(s):  
Activated Carbon ◽  
Experimental Design ◽  
Sunflower Seed ◽  
Dye Removal ◽  
Factorial Experimental Design ◽  
Adsorbent Dosage ◽  
Seed Cake ◽  
Pseudo Second Order ◽  
Full Factorial Experimental Design ◽  
Full Factorial

The objective of this study was to investigate the removal of Remazol Yellow dye from aqueous solutions by adsorption on activated carbon prepared by chemical activation of sunflower seed cake. It was found that the carbon content of biomass increases up to 65.12% after activation and carbonization processes. The maximum percentage dye removal was obtained as 82.12% with 0.4 g/50 mL adsorbent dosage at 313 K. The Langmuir model showed the best fit with equilibrium isotherm data. The interactions were evaluated with respect to both pseudo-first-order and pseudo-second-order reaction kinetics. The adsorption process was found to follow the pseudo-second-order model. To optimize the operating conditions, the effects of pH, adsorbent dosage, and initial dye concentration were investigated by full factorial experimental design method; adsorbent dosage was found as the most significant factor with lower than 95% confidence level. The obtained results are very promising since (i) the utilization of sunflower seed cake activated carbon (SSCAC) played a critical role in the adsorption of dye; (ii) sunflower seed cake was an intriguing, low-cost, and easily available material. It can be an alternative adsorbent precursor for more expensive adsorbents used for Remazol Yellow (RY) removal.

scholarly journals Study of Montmorillonite Clay for the Removal of Copper (II) by Adsorption: Full Factorial Design Approach and Cascade Forward Neural Network

2013 ◽  
Vol 2013 ◽  
pp. 1-11 ◽  
Author(s):  
Nurdan Gamze Turan ◽  
Okan Ozgonenel
Keyword(s):  
Neural Network ◽  
Factorial Design ◽  
Removal Efficiency ◽  
Contact Time ◽  
Cost Effective ◽  
Adsorbent Dosage ◽  
Initial Ph ◽  
Network Structure Optimization ◽  
Main Effects ◽  
Full Factorial

An intensive study has been made of the removal efficiency of Cu(II) from industrial leachate by biosorption of montmorillonite. A 24factorial design and cascade forward neural network (CFNN) were used to display the significant levels of the analyzed factors on the removal efficiency. The obtained model based on 24factorial design was statistically tested using the well-known methods. The statistical analysis proves that the main effects of analyzed parameters were significant by an obtained linear model within a 95% confidence interval. The proposed CFNN model requires less experimental data and minimum calculations. Moreover, it is found to be cost-effective due to inherent advantages of its network structure. Optimization of the levels of the analyzed factors was achieved by minimizing adsorbent dosage and contact time, which were costly, and maximizing Cu(II) removal efficiency. The suggested optimum conditions are initial pH at 6, adsorbent dosage at 10 mg/L, and contact time at 10 min using raw montmorillonite with the Cu(II) removal of 80.7%. At the optimum values, removal efficiency was increased to 88.91% if the modified montmorillonite was used.

Application of 32 Full Factorial Design and Desirability Function for Optimizing The Manufacturing Process for Directly Compressible Multi-Functional Co-Processed Excipient

2020 ◽  
Vol 17 (6) ◽  
pp. 523-539
Author(s):  
Jalpa Patel ◽  
Dhaval Mori
Keyword(s):  
Factorial Design ◽  
Spray Drying ◽  
Desirability Function ◽  
Full Factorial Design ◽  
Angle Of Repose ◽  
P Value ◽  
Independent Variables ◽  
Full Factorial ◽  
32 Full Factorial Design ◽  
Response Variables

Background: Developing a new excipient and obtaining its market approval is an expensive, time-consuming and complex process. Compared to that, the co-processing of already approved excipients has emerged as a more attractive option for bringing better characteristic excipients to the market. The application of the Design of Experiments (DoE) approach for developing co-processed excipient can make the entire process cost-effective and rapid. Objective: The aim of the present investigation was to demonstrate the applicability of the DoE approach, especially 32 full factorial design, to develop a multi-functional co-processed excipient for the direct compression of model drug - cefixime trihydrate using spray drying technique. Methods: The preliminary studies proved the significant effect of atomization pressure (X1) and polymer ratio (microcrystalline cellulose: mannitol - X2) on critical product characteristics, so they were selected as independent variables. The angle of repose, Carr’s index, Hausner’s ratio, tensile strength and Kuno’s constant were selected as response variables. Result: The statistical analysis proved a significant effect of both independent variables on all response variables with a significant p-value < 0.05. The desirability function available in Design Expert 11® software was used to prepare and select the optimized batch. The prepared co-processed excipient had better compressibility than individual excipients and their physical mixture and was able to accommodate more than 40 percent drug without compromising the flow property and compressibility. Conclusion: The present investigation successfully proved the applicability of 32 full factorial design as an effective tool for optimizing the spray drying process to prepare a multi-functional co-processed excipient.

Formulation of Extended-Release Beads of Lamotrigine Based on Alginate and Cassia fistula Seed Gum by QbD Approach

2020 ◽  
Vol 17 (5) ◽  
pp. 422-437
Author(s):  
Dixita Jain ◽  
Akshay Sodani ◽  
Swapnanil Ray ◽  
Pranab Ghosh ◽  
Gouranga Nandi
Keyword(s):  
Drug Release ◽  
Factorial Design ◽  
Extended Release ◽  
Polymer Concentration ◽  
Green Manufacturing ◽  
Full Factorial Design ◽  
Cassia Fistula ◽  
Negative Environmental Impact ◽  
Seed Gum ◽  
Full Factorial

Aim: This study was focused on the formulation of the multi-unit extended-release peroral delivery device of lamotrigine for better management of epilepsy. Background: The single-unit extended-release peroral preparations often suffer from all-or-none effect. A significant number of multi-unit delivery systems have been reported as a solution to this problem. But most of them are found to be composed of synthetic, semi-synthetic or their combination having physiological toxicity as well as negative environmental impact. Therefore, fabrication and formulation of multi-unit extended-release peroral preparations with natural, non-toxic, biodegradable polymers employing green manufacturing processes are being appreciated worldwide. Objective: Lamotrigine-loaded extended-release multi-unit beads have been fabricated with the incorporation of a natural polysaccharide Cassia fistula seed gum in calcium-cross-linked alginate matrix employing a simple green process and 23 full factorial design. Methods: The total polymer concentration, polymer ratio and [CaCl2] were considered as independent formulation variables with two different levels of each for the experiment-design. The extended-release beads were then prepared by the ionotropic gelation method using calcium chloride as the crosslinkerions provider. The beads were then evaluated for drug encapsulation efficiency and drug release. ANOVA of all the dependent variables such as DEE, cumulative % drug release at 2h, 5h, 12h, rate constant and dissolution similarity factor (f2) was done by 23 full factorial design using Design-Expert software along with numerical optimization of the independent variables in order to meet USP-reference release profile. Results: The optimized batch showed excellent outcomes with DEE of 84.7 ± 2.7 (%), CPR2h of 8.41± 2.96 (%), CPR5h of 36.8± 4.7 (%), CPR12h of 87.3 ± 3.64 (%) and f2 of 65.9. Conclusion: This approach of the development of multi-unit oral devices utilizing natural polysaccharides might be inspiring towards the world-wide effort for green manufacturing of sustained-release drug products by the QbD route.

scholarly journals Shear strength optimization for FSSW AA6060-T5 joints by Taguchi and full factorial design

2020 ◽  
Vol 9 (6) ◽  
pp. 16072-16079
Author(s):  
C.A.G. Aita ◽  
I.C. Goss ◽  
T.S. Rosendo ◽  
M.D. Tier ◽  
A. Wiedenhöft ◽  
...  
Keyword(s):  
Shear Strength ◽  
Factorial Design ◽  
Full Factorial Design ◽  
Full Factorial
Sign in / Sign up

Export Citation Format

Share Document