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...
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MDPI AG
2025-02-01
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| Series: | Nanomaterials |
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| author | Kyriakos Almpanidis Chloe J. Howard Vlad Stolojan |
| author_facet | Kyriakos Almpanidis Chloe J. Howard Vlad Stolojan |
| author_sort | Kyriakos Almpanidis |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-e62d3bcf25a949f583c000abdba5c261 |
| institution | DOAJ |
| issn | 2079-4991 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | MDPI AG |
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| series | Nanomaterials |
| spelling | doaj-art-e62d3bcf25a949f583c000abdba5c2612025-08-20T02:52:42ZengMDPI AGNanomaterials2079-49912025-02-0115533910.3390/nano15050339An In Situ Characterisation Method for 3-D Electrospun FoamsKyriakos Almpanidis0Chloe J. Howard1Vlad Stolojan2Advanced Technology Institute, University of Surrey, Guildford GU2 7XH, UKAdvanced Technology Institute, University of Surrey, Guildford GU2 7XH, UKAdvanced Technology Institute, University of Surrey, Guildford GU2 7XH, UKThree-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.https://www.mdpi.com/2079-4991/15/5/339electrospinningfoam formationfoam qualitysignal processingevaluation parametersTaguchi space design |
| spellingShingle | Kyriakos Almpanidis Chloe J. Howard Vlad Stolojan An In Situ Characterisation Method for 3-D Electrospun Foams Nanomaterials electrospinning foam formation foam quality signal processing evaluation parameters Taguchi space design |
| title | An In Situ Characterisation Method for 3-D Electrospun Foams |
| title_full | An In Situ Characterisation Method for 3-D Electrospun Foams |
| title_fullStr | An In Situ Characterisation Method for 3-D Electrospun Foams |
| title_full_unstemmed | An In Situ Characterisation Method for 3-D Electrospun Foams |
| title_short | An In Situ Characterisation Method for 3-D Electrospun Foams |
| title_sort | in situ characterisation method for 3 d electrospun foams |
| topic | electrospinning foam formation foam quality signal processing evaluation parameters Taguchi space design |
| url | https://www.mdpi.com/2079-4991/15/5/339 |
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