Application of response surface methodology to tailor the surface chemistry of electrospun chitosan-poly(ethylene oxide) fibers

Bösiger, P.; Richard, Isabelle; Gat, Luce Le; Michen, Benjamin; Schubert, Mark; Rossi, René M.; Fortunato, Giuseppino

doi:10.1016/j.carbpol.2018.01.038

Cited by 27 publications

(12 citation statements)

References 91 publications

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“…y is the response value, xi and x are various operating variables, k is the number of variables; β 0 , β, β i i, and β i (i = 0, 1, 2, … k; j = 0, 1, 2, … k) are the regression coefficients of the intercept, linear, quadratic and interaction terms, respectively, and ∑ is the statistical error. 23…”

Section: Methodsmentioning

confidence: 99%

Modeling and Optimization of Durable Press Finishing of Cotton Fabric with BTCA by Response Surface Methodology

Chu¹,

Wang²,

Sui³

et al. 2020

AATCC Journal of Research

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Durable press (DP) finishing process of cotton fabric with 1,2,3,4-butanetetracarboxylic acid (BTCA) was investigated and optimized using the Box-Behnken design (BBD) with a response surface methodology (RSM). BBD experimental data were fitted to create the response surface regression models describing wrinkle recovery angle (WRA) and breaking strength of the finished cotton fabric. Analysis of variance (ANOVA) revealed that the concentration of BTCA was the most significant variable affecting the WRA, followed by the curing time, curing temperature, and concentration of sodium hypophosphite (SHP). Regarding breaking strength, curing time was the most significant variable, followed by the curing temperature, concentration of BTCA, and concentration of SHP. After optimal treatment, the WRA of the finished fabric was 252°, while the retention rate of breaking strength was 69%.

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Section: Methodsmentioning

confidence: 99%

Modeling and Optimization of Durable Press Finishing of Cotton Fabric with BTCA by Response Surface Methodology

Chu¹,

Wang²,

Sui³

et al. 2020

AATCC Journal of Research

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“…The equations obtained can describe the effects of multiple controllable input variables and their interactions for one or many observable output responses. To date, only a few studies have used such a multivariate approach to investigate the potential of their experimental design for the development of nanofibers [38].…”

Section: Introductionmentioning

confidence: 99%

Effect of Solution Composition Variables on Electrospun Alginate Nanofibers: Response Surface Analysis

2019

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Alginate is a promising biocompatible and biodegradable polymer for production of nanofibers for drug delivery and tissue engineering. However, alginate is difficult to electrospin due to its polyelectrolyte nature. The aim was to improve the ‘electrospinability’ of alginate with addition of exceptionally high molecular weight poly(ethylene oxide) (PEO) as a co-polymer. The compositions of the polymer-blend solutions for electrospinning were varied for PEO molecular weight, total (alginate plus PEO) polymer concentration, and PEO proportion in the dry alginate–PEO polymer mix used. These were tested for rheology (viscosity, complex viscosity, storage and loss moduli) and conductivity, and the electrospun nanofibers were characterized by scanning electron microscopy. One-parameter-at-a-time approach and response surface methodology (RSM) were used to optimize the polymer-blend solution composition to obtain defined nanofibers. Both approaches revealed that the major influence on nanofiber formation and diameter were total polymer concentration and PEO proportion. These polymer-blend solutions of appropriate conductivity and viscosity enabled fine-tuning of nanofiber diameter. PEO molecular weight of 2–4 million Da greatly improved the electrospinnability of alginate, producing nanofibers with >85% alginate. This study shows that RSM can be used to design nanofibers with optimal alginate and co-polymer contents to provide efficient scaffold material for regenerative medicine.

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“…RSM revealed the chitosan/PEO ratio and MW of chitosan as the main factors influencing the variation of accessible surface nitrogen concentrations between 0% and 6.4%. The model showed good adequacy, thereby providing a tool for tailoring the surface properties of chitosan/PEO blends by addressing the amount of accessible chitosan [14].…”

Section: The Influence Of the Process Parametersmentioning

confidence: 96%

“…Fibers produced by an electrospinning process can, therefore, have diameters related to the process parameters [9] and to the properties of the initial polymers and their solutions [13]. The electrospinning process is frequently optimized by response surface methodology (RSM) [14][15][16], which allows determination of the influence of several factors and their interaction simultaneously by compact experiment design. RSM is, therefore, less time-consuming than the conventional one-factor-at-a-time approach [17,18] and can be used when the quantitative evaluation of response parameters is possible.…”

Section: Introductionmentioning

confidence: 99%

Needleless Electrospinning of a Chitosan Lactate Aqueous Solution: Influence of Solution Composition and Spinning Parameters

et al. 2019

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The biological activity of chitosan determines its broad application as a biopolymer for non-woven wound dressings fabricated by electrospinning. The electrospinning process is affected by a large number of different factors that complicate its optimization. In the present work, the electrospinning of chitosan lactate was carried out using a needleless technique from water solutions of different compositions. Surface response methodology was used to evaluate the effects of the concentration of chitosan, polyethylene oxide, and ethanol on solution properties, such as viscosity, surface tension, and conductivity, as well as the process characteristics and fiber quality. The viscosity of the spinning solution is determined by the polymer concentration as well as by the interpolymer interactions. The addition of ethanol to the spinning solutions effectively decreases the solution surface tension and conductivity, while increasing the volatility of the solvent, to provide more intense fiber spinning. Atomic force microscopy revealed that the chitosan lactate fibers were obtained without defects and with a narrow thickness distribution. The spinning parameters, voltage, distance between electrodes, and rotation speed of the spinning electrode had insignificant influences on the fiber diameter during needleless electrospinning.

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Application of response surface methodology to tailor the surface chemistry of electrospun chitosan-poly(ethylene oxide) fibers

Cited by 27 publications

References 91 publications

Modeling and Optimization of Durable Press Finishing of Cotton Fabric with BTCA by Response Surface Methodology

Modeling and Optimization of Durable Press Finishing of Cotton Fabric with BTCA by Response Surface Methodology

Effect of Solution Composition Variables on Electrospun Alginate Nanofibers: Response Surface Analysis

Needleless Electrospinning of a Chitosan Lactate Aqueous Solution: Influence of Solution Composition and Spinning Parameters

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