An In Situ Characterisation Method for 3-D Electrospun Foams

Three-dimensional electrospun foams are emerging in a diversity of applications. However, their characterisation involves procedures to calculate fibre diameter and porosity, which take considerable time. Hence, in this paper, an in situ characterisation method is presented based on signal features of the grounding voltage. These features are combined into the in situ evaluation parameter <b>S</b><sub>r</sub> for each run r. The L9 Taguchi method was utilised to minimise the total number of experiments. Moreover, to prove the accuracy of this method, the traditional post-fabrication analysis was conducted, and the post-fabrication evaluation parameter was retrieved <b>Q</b><sub>r</sub> for each run r. The analysis shows that both parameters detected the same experiment run as the optimal one (with an adjusted R<sup>2</sup> = 0.84) for polystyrene electrospun foams for two solution concentrations: 15%wv (run 3 with mean <b>S</b><sub>3</sub> = 54.49 and mean <b>Q</b><sub>3</sub> = 0.248) and 20%wv (mean <b>S</b><sub>5</sub> = 2.49 and <b>Q</b><sub>5</sub> = 0.248), respectively. Also, the statistical analysis shows low standard deviations for the optimal and near-optimal runs, proving the method's repeatability. Furthermore, a theoretical explanation is provided for selecting signal features based on the Maxwellian equivalent circuit approach for the electrospun jet. Finally, this fast in situ evaluation method can replace the post-fabrication time-consuming one. It can be used as a fundamental step for an intelligent artificial intelligence tool that predicts optimal foam formation.

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Publication Details

Journal
Nanomaterials
Published
2025-02-22
DOI
https://doi.org/10.3390/nano15050339
Primary Topic
Electrospun Nanofibers in Biomedical Applications
Type
article
Field-Weighted Citation Impact
0.00

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article

An In Situ Characterisation Method for 3-D Electrospun Foams

Vlad Stolojan, Chloe Jayne Howard, Kyriakos Almpanidis
Nanomaterials
Electrospun Nanofibers in Biomedical Applications
article

An In Situ Characterisation Method for 3-D Electrospun Foams

Vlad Stolojan, Chloe Jayne Howard, Kyriakos Almpanidis
article en

Abstract

Three-dimensional electrospun foams are emerging in a diversity of applications. However, their characterisation involves procedures to calculate fibre diameter and porosity, which take considerable time. Hence, in this paper, an in situ characterisation method is presented based on signal features of the grounding voltage. These features are combined into the in situ evaluation parameter <b>S</b><sub>r</sub> for each run r. The L9 Taguchi method was utilised to minimise the total number of experiments. Moreover, to prove the accuracy of this method, the traditional post-fabrication analysis was conducted, and the post-fabrication evaluation parameter was retrieved <b>Q</b><sub>r</sub> for each run r. The analysis shows that both parameters detected the same experiment run as the optimal one (with an adjusted R<sup>2</sup> = 0.84) for polystyrene electrospun foams for two solution concentrations: 15%wv (run 3 with mean <b>S</b><sub>3</sub> = 54.49 and mean <b>Q</b><sub>3</sub> = 0.248) and 20%wv (mean <b>S</b><sub>5</sub> = 2.49 and <b>Q</b><sub>5</sub> = 0.248), respectively. Also, the statistical analysis shows low standard deviations for the optimal and near-optimal runs, proving the method's repeatability. Furthermore, a theoretical explanation is provided for selecting signal features based on the Maxwellian equivalent circuit approach for the electrospun jet. Finally, this fast in situ evaluation method can replace the post-fabrication time-consuming one. It can be used as a fundamental step for an intelligent artificial intelligence tool that predicts optimal foam formation.

NanomaterialsVol. 15(5)
University of Surrey (GB)
Engineering and Physical Sciences Research Council
Openalex Percentile: Top 98%
Electrospun Nanofibers in Biomedical Applications
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An In Situ Characterisation Method for 3-D Electrospun Foams — Vlad Stolojan, Chloe Jayne Howard, et al. · Nanomaterials (2025) | TGRS Research Map | TGRS