Mathematical modeling and optimization by the application of full factorial design and response surface methodology approach for decolourization of dyes by a newly isolated Photobacterium ganghwense

2021 ◽  
Vol 44 ◽  
pp. 102429
Author(s):  
Hisham N. Altayb ◽  
Bochra Kouidhi ◽  
Othman A.S. Baothman ◽  
Jawaher Abdualbaqi Abdulhakim ◽  
Lamia Ayed ◽  
...  
Keyword(s):  
Mathematical Modeling ◽  
Response Surface Methodology ◽  
Factorial Design ◽  
Response Surface ◽  
Full Factorial Design ◽  
Modeling And Optimization ◽  
Full Factorial

Supercritical CO2 Extraction of Plumula nelumbinis Oil Rich in γ-Sitosterol Using Response Surface Methodology

2013 ◽  
Vol 864-867 ◽  
pp. 213-216
Author(s):  
Dong Dong Jia ◽  
Rong Lan ◽  
Yong Yue Sun
Keyword(s):  
Response Surface Methodology ◽  
Factorial Design ◽  
Response Surface ◽  
Surface Analysis ◽  
Full Factorial Design ◽  
Response Surface Analysis ◽  
Optimal Conditions ◽  
Full Factorial

Supercritical CO2extraction ofPlumula nelumbinisoil rich in γ-sitosterol was investigated with a 42full factorial design and response surface analysis. At optimal conditions (P=35 MPa,T=55 C,dp=0.22 mm,Q=2.0 L/min), the yield of the extracted oil was up to 12.2%, in which the concentration of γ-sitosterol was 7.38%, indicating that the γ-sitosterol contents inPlumula nelumbinisand its oil were much higher than that in other vegetables.

scholarly journals Optimization of pyrocatechol violet biosorption by Robinia pseudoacacia leaf powder using response surface methodology: kinetic, isotherm and thermodynamic studies

2015 ◽  
Vol 6 (2) ◽  
pp. 333-344 ◽  
Author(s):  
Neda Khorshidi ◽  
Ali Niazi
Keyword(s):  
Response Surface Methodology ◽  
Factorial Design ◽  
Response Surface ◽  
Robinia Pseudoacacia ◽  
Freundlich Isotherm ◽  
Second Order ◽  
Full Factorial Design ◽  
Order Kinetic ◽  
Pyrocatechol Violet ◽  
Full Factorial

We have investigated the biosorption of pyrocatechol violet (PCV) from aqueous solutions by Robinia pseudoacacia tree leaves as a low-cost and eco-friendly biosorbent. A full factorial design was performed for screening the main variables and their interactions, which reduces the large total number of experiments. Results of the full factorial design (24) based on an analysis of variance (ANOVA) demonstrated that the initial PCV concentration, contact time, pH and temperature are statistically significant. Box-Behnken design, a response surface methodology, was used for further optimization of these selected factors. The ANOVA and some statistical tests such as lack-of-fit and coefficient of determination (R2) showed good fit of the experimental data to the second-order polynomial model. The Langmuir and Freundlich isotherm models were used to describe the equilibrium isotherms. Equilibrium data fitted well with the Freundlich isotherm model (R2 > 0.97). In addition, thermodynamic parameters (ΔG°, ΔH° and ΔS°) were calculated, these parameters show that the biosorption process was spontaneous (ΔG° = −2.423) and exothermic (ΔH° = −9.67). The biosorption kinetic data were fitted with the pseudo-second-order kinetic model (R2 > 0.999). These results confirm that R. pseudoacacia leaves have good potential for removal of PCV from aqueous solution.

Three-level response surface full-factorial design: advanced chemometric approach for optimizing diclofenac sodium-imprinted polymer

2013 ◽  
Vol 71 (1) ◽  
pp. 19-30 ◽  
Author(s):  
Nasim Salimraftar ◽  
Saeed Noee ◽  
Majid Abdouss ◽  
Gholamhossein Riazi ◽  
Zahra Monsef Khoshhesab
Keyword(s):  
Factorial Design ◽  
Response Surface ◽  
Diclofenac Sodium ◽  
Full Factorial Design ◽  
Imprinted Polymer ◽  
Chemometric Approach ◽  
Full Factorial

Earphone terminal quality improvement through sequential experimental design

2015 ◽  
Vol 32 (7) ◽  
pp. 693-702 ◽  
Author(s):  
Zhen He ◽  
Xu-tao Zhang ◽  
Gui-qing Xie ◽  
Min Zhang
Keyword(s):  
Factorial Design ◽  
Response Surface ◽  
Response Surface Model ◽  
Full Factorial Design ◽  
Fractional Factorial ◽  
Surface Model ◽  
Quality Performance ◽  
Content Type ◽  
Input Variables ◽  
Full Factorial

Purpose – The purpose of this paper is to improve the key quality performance of the terminal of earphone in an electronic company. Design/methodology/approach – Sequential experimental designs are employed. Significant input variables are found through a full factorial design. Then a response surface model is constructed considering curvature in the linear model. Findings – Optimized key input variables’ parameters are found using the response surface model. The key quality performance, coplanarity of the terminal of earphone has been improved. Research limitations/implications – Instead of running a full factorial design in the first stage, a fractional factorial may be used to reduce experimental runs. Practical implications – The paper presents a good solution for reducing defects caused by large coplanarity of a kind of earphone terminal. Originality/value – The methodology used in this case can be easily extended to similar cases.

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.

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