An In Situ Characterisation Method for 3-D Electrospun Foams.

IF 4.3 3区 材料科学 Q2 CHEMISTRY, MULTIDISCIPLINARY Nanomaterials Pub Date : 2025-02-22 DOI:10.3390/nano15050339
Kyriakos Almpanidis, Chloe J Howard, Vlad Stolojan
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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 Sr 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 Qr for each run r. The analysis shows that both parameters detected the same experiment run as the optimal one (with an adjusted R2 = 0.84) for polystyrene electrospun foams for two solution concentrations: 15%wv (run 3 with mean S3 = 54.49 and mean Q3 = 0.248) and 20%wv (mean S5 = 2.49 and Q5 = 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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三维静电纺泡沫材料的原位表征方法。
三维静电纺泡沫材料的应用越来越广泛。然而,它们的表征涉及到计算纤维直径和孔隙率的过程,这需要相当长的时间。因此,本文提出了一种基于接地电压信号特征的现场表征方法。这些特征被结合到每次运行r的原位评价参数Sr中。L9田口法被用来最小化实验总数。此外,证明该方法的准确性,传统的post-fabrication进行分析,和post-fabrication评价参数检索Qr每次运行r。分析表明,两个参数检测到相同的实验作为最优运行一个(R2 = 0.84)调整为聚苯乙烯泡沫实际上电纺两种溶液浓度:15% wv(跑3平均S3 = 54.49和平均Q3 = 0.248)和20% wv(意味着S5 = 2.49和Q5 = 0.248),分别。此外,统计分析表明,最优和接近最优运行的标准偏差较低,证明了该方法的可重复性。在此基础上,给出了基于麦克斯韦等效电路方法选择电纺丝射流信号特征的理论解释。最后,这种快速的原位评价方法可以代替耗时的加工后评价方法。它可以作为预测最佳泡沫形成的智能人工智能工具的基本步骤。
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来源期刊
Nanomaterials
Nanomaterials NANOSCIENCE & NANOTECHNOLOGY-MATERIALS SCIENCE, MULTIDISCIPLINARY
CiteScore
8.50
自引率
9.40%
发文量
3841
审稿时长
14.22 days
期刊介绍: Nanomaterials (ISSN 2076-4991) is an international and interdisciplinary scholarly open access journal. It publishes reviews, regular research papers, communications, and short notes that are relevant to any field of study that involves nanomaterials, with respect to their science and application. Thus, theoretical and experimental articles will be accepted, along with articles that deal with the synthesis and use of nanomaterials. Articles that synthesize information from multiple fields, and which place discoveries within a broader context, will be preferred. There is no restriction on the length of the papers. Our aim is to encourage scientists to publish their experimental and theoretical research in as much detail as possible. Full experimental or methodical details, or both, must be provided for research articles. Computed data or files regarding the full details of the experimental procedure, if unable to be published in a normal way, can be deposited as supplementary material. Nanomaterials is dedicated to a high scientific standard. All manuscripts undergo a rigorous reviewing process and decisions are based on the recommendations of independent reviewers.
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