优化电子纺PVA纤维与MXene集成的生物医学应用

IF 4.6 3区 材料科学 Q2 MATERIALS SCIENCE, MULTIDISCIPLINARY
Nergis Zeynep Renkler, Zaheer Ud Din Babar, Mario Barra, Iriczalli Cruz-Maya, Roberto De Santis, Rocco di Girolamo, Marcello Marelli, Anna Maria Ferretti, Ayesha Zaheer, Vincenzo Iannotti, Vincenzo Guarino
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引用次数: 0

摘要

mxene基材料因其具有良好的生物相容性、提高的机械强度和导电性而受到生物医学领域的关注。在这项研究中,重点是优化mxene加入的电纺丝纤维和随后的表征,以评估其生物医学应用的潜力。采用聚乙烯醇(PVA)作为合适的基体材料,并对工艺参数进行了微调,以确保MXene的有效掺入。XRD和光谱分析证实了MXenes的成功合成和纳米纤维的整合。形态学分析表明,与纯PVA(696±160 nm)相比,MXene使纤维直径减小(587±191 nm),形成了表面光滑的亚微米纤维。电学特性的研究表明,加入MXene后,纳米纤维的电导率提高了四倍(σ = 1.90±0.45 × 10−8 S cm−1),而只添加pva的纤维的电导率为0.46±0.05 × 10−8 S cm−1)。此外,MXene-PVA系统的机械刚度增加了近两倍,其E = 136.87±19.63 MPa,而PVA为71.42±16.56 MPa。此外,初步体外实验表明,提高L929细胞活力。这些发现将MXene-PVA复合材料定位为先进生物医学设备的高度通用平台,例如电活性组织支架和可穿戴传感器。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Optimizing Electrospun PVA Fibers with MXene Integration for Biomedical Applications

Optimizing Electrospun PVA Fibers with MXene Integration for Biomedical Applications

MXene-based materials have gained attention in the biomedical field due to their promising biocompatibility, improved mechanical strength, and conductivity. In this study, the focus is on optimizing MXene-incorporated electrospun fibers and subsequent characterizations to assess their potential for biomedical applications. Polyvinyl alcohol (PVA) is used as the appropriate matrix material and process parameters are finetuned to ensure effective incorporation of MXene. XRD and spectroscopic analysis confirm the successful synthesis and integration of MXenes into the nanofibers. Morphological analysis shows that MXene led to the formation of sub-micrometer fibers with smooth surfaces and reduced the fiber diameter (587 ± 191 nm) compared to pure PVA (696 ±160 nm). Investigations on the electrical characteristics demonstrate a fourfold increase in conductivity of nanofibers (σ = 1.90 ± 0.45 × 10−8 S cm−1) after MXene addition (compared to σ = 0.46 ± 0.05 × 10−8 S cm−1 of PVA-only fibers). Furthermore, the MXene-PVA system demonstrates a nearly twofold increase in mechanical stiffness, with E = 136.87 ± 19.63 MPa than 71.42 ± 16.56 MPa for PVA. Moreover, the initial in vitro experiments indicate improved L929 cell viability. These findings position MXene-PVA composites as a highly versatile platform for advanced biomedical devices, such as electroactive tissue scaffolds and wearable sensors.

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来源期刊
Macromolecular Materials and Engineering
Macromolecular Materials and Engineering 工程技术-材料科学:综合
CiteScore
7.30
自引率
5.10%
发文量
328
审稿时长
1.6 months
期刊介绍: Macromolecular Materials and Engineering is the high-quality polymer science journal dedicated to the design, modification, characterization, processing and application of advanced polymeric materials, including membranes, sensors, sustainability, composites, fibers, foams, 3D printing, actuators as well as energy and electronic applications. Macromolecular Materials and Engineering is among the top journals publishing original research in polymer science. The journal presents strictly peer-reviewed Research Articles, Reviews, Perspectives and Comments. ISSN: 1438-7492 (print). 1439-2054 (online). Readership:Polymer scientists, chemists, physicists, materials scientists, engineers Abstracting and Indexing Information: CAS: Chemical Abstracts Service (ACS) CCR Database (Clarivate Analytics) Chemical Abstracts Service/SciFinder (ACS) Chemistry Server Reaction Center (Clarivate Analytics) ChemWeb (ChemIndustry.com) Chimica Database (Elsevier) COMPENDEX (Elsevier) Current Contents: Physical, Chemical & Earth Sciences (Clarivate Analytics) Directory of Open Access Journals (DOAJ) INSPEC (IET) Journal Citation Reports/Science Edition (Clarivate Analytics) Materials Science & Engineering Database (ProQuest) PASCAL Database (INIST/CNRS) Polymer Library (iSmithers RAPRA) Reaction Citation Index (Clarivate Analytics) Science Citation Index (Clarivate Analytics) Science Citation Index Expanded (Clarivate Analytics) SciTech Premium Collection (ProQuest) SCOPUS (Elsevier) Technology Collection (ProQuest) Web of Science (Clarivate Analytics)
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