Abstract

The aim of the present work was to investigate how the molecular weight (MW) of poly(ethylene oxide) (PEO), a synthetic polymer able to improve alginate (ALG) electrospinnability, could affect ALG-based fiber morphology and mechanical properties. Two PEO grades, having different MWs (high, h-PEO, and low, l-PEO) were blended with ALG: the concentrations of both PEOs in each mixture were defined so that each h-PEO/l-PEO combination would show the same viscosity at high shear rate. Seven ALG/h-PEO/l-PEO mixtures were prepared and characterized in terms of viscoelasticity and conductivity and, for each mixture, a complex parameter rH/rL was calculated to better identify which of the two PEO grades prevails over the other in terms of exceeding the critical entanglement concentration. Thereafter, each mixture was electrospun by varying the process parameters; the fiber morphology and mechanical properties were evaluated. Finally, viscoelastic measurements were performed to verify the formation of intermolecular hydrogen bonds between the two PEO grades and ALG. rH/rL has been proved to be the parameter that better explains the effect of the electrospinning conditions on fiber dimension. The addition of a small amount of h-PEO to l-PEO was responsible for a significant increase in fiber mechanical resistance, without affecting the nano-scale fiber size. Moreover, the mixing of h-PEO and l-PEO improved the interaction with ALG, resulting in an increase in chain entanglement degree that is functional in the electrospinning process.

Highlights

  • In the last two decades, electrospinning has been recognized as a simple, low-cost, and versatile method to obtain submicron fibers for a variety of biomedical applications, such as tissue engineering [1,2,3], drug delivery [4], and wound healing [5,6]

  • Viscoelastic measurements were performed to verify the formation of intermolecular hydrogen bonds between the two poly(ethylene oxide) (PEO) grades and ALG. rH/rL has been proved to be the parameter that better explains the effect of the electrospinning conditions on fiber dimension

  • The mixing of h-PEO and l-PEO improved the interaction with ALG, resulting in an increase in chain entanglement degree that is functional in the electrospinning process

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Summary

Introduction

In the last two decades, electrospinning has been recognized as a simple, low-cost, and versatile method to obtain submicron fibers for a variety of biomedical applications, such as tissue engineering [1,2,3], drug delivery [4], and wound healing [5,6]. An ALG aqueous solution starts to gel at concentrations equal to or greater than 2% w/v; concentrations lower than 2% w/v are too low for the production of continuous fibers, while an increase in ALG concentration generates solutions with a viscosity so high as to clog the spinneret Another factor hindering the electrospinning process is that ALG is a polyelectrolyte: ALG aqueous solutions are characterized by a high conductivity, which prevents the ejection of a stabilized jet through the needle. It seems interesting to evaluate whether the use of mixtures of different PEO grades (having different MWs) could modulate fiber morphology and mechanical properties Given these premises, the aim of the present work was to investigate how the MW of PEO, when blended with ALG, could affect electrospun fiber morphology and mechanical properties; in particular, in order to design ALG-containing fibers with a nano-scale diameter, PEO with high MW (h-PEO), successfully used in a previous work to obtain micro-scale fibers [26], was substituted by PEO with low MW (l-PEO). Viscoelastic measurements were performed to assess the influence of PEO MW on the polymer capability to interact with ALG, increasing the chain entanglement and, in turn, improving the electrospinning process

Materials
Preparation of the Polymer Solutions for Electrospinning
Rheological Analysis
Fiber Preparation and Morphological Characterization
Assessment of Fiber Mechanical Properties
Assessment of the Rheological Interaction between ALG and PEOs
Findings
H L M1 M3 M5 M7

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