生物相容性聚合物基质中由boc - ph - leu自组装二肽包体组成的功能化复合纳米纤维的介电和能量收集性能

Adelino Handa, Rosa M. F. Baptista, Daniela Santos, Bruna Silva, João Oliveira, Bernardo Almeida, Etelvina de Matos Gomes, Michael Belsley
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引用次数: 1

摘要

摘要采用静电纺丝法,将Boc- 1 -苯丙酰- 1 -亮氨酸二肽掺入生物相容性聚合物的纳米纤维中,制备了杂化生物纳米材料。扫描电镜证实了纳米纤维的均匀性,直径范围为0.56 ~ 1.61µm。利用阻抗谱法对纳米纤维的介电性能进行了表征,评估了温度和频率的依赖关系。值得注意的是,复合微纳米纤维表现出半导体介电行为,带隙能量为4-5 eV,分析表明介电常数随着温度的升高而增加,这是由于电荷迁移率的增强。麦克斯韦-瓦格纳界面极化验证了二肽的成功结合,Havriliak-Negami模型揭示了电介电常数的见解。此外,纤维表现出热释电和压电响应,Boc-Phe-Leu@PLLA纳米纤维的压电系数最高,为85 pC/N。这些发现强调了二肽纳米结构对介电、热释电和压电性能的影响,表明聚合物微/纳米纤维作为便携式和可穿戴设备的高效压电能量发生器的潜力。图形抽象
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Dielectric and energy harvesting properties of functionalized composite nanofibers consisting of Boc-Phe-Leu self-assembled dipeptide inclusions in biocompatible polymeric matrices
Abstract Hybrid bionanomaterials were produced through electrospinning, incorporating the dipeptide Boc- l -phenylalanyl- l -leucine into nanofibers of biocompatible polymers. Scanning electron microscopy confirmed the uniformity of the nanofibers, with diameters ranging from 0.56 to 1.61 µm. The dielectric properties of the nanofibers were characterized using impedance spectroscopy, assessing temperature and frequency dependencies. Notably, the composite micro/nanofibers exhibited semiconducting dielectric behavior with bandgap energies of 4–5 eV, and their analysis revealed increased dielectric constant with temperature due to enhanced charge mobility. The successful incorporation of the dipeptide was verified by Maxwell–Wagner interfacial polarization, and the Havriliak–Negami model disclosed insights into electric permittivity. Furthermore, the fibers demonstrated pyroelectric and piezoelectric responses, with Boc-Phe-Leu@PLLA nanofibers having the highest piezoelectric coefficient of 85 pC/N. These findings highlight the influence of dipeptide nanostructures on dielectric, pyroelectric, and piezoelectric properties, suggesting the potential of polymeric micro/nanofibers as efficient piezoelectric energy generators for portable and wearable devices. Graphical Abstract
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来源期刊
Discover Materials
Discover Materials materials-
CiteScore
3.30
自引率
0.00%
发文量
10
审稿时长
23 days
期刊介绍: Discover Materials is part of the Discover journal series committed to providing a streamlined submission process, rapid review and publication, and a high level of author service at every stage. It is a broad, open access journal publishing research from across all fields of materials research. Discover Materials covers all areas where materials are activators for innovation and disruption, providing cutting-edge research findings to researchers, academicians, students, and engineers. It considers the whole value chain, ranging from fundamental and applied research to the synthesis, characterisation, modelling and application of materials. Moreover, we especially welcome papers connected to so-called ‘green materials’, which offer unique properties including natural abundance, low toxicity, economically affordable and versatility in terms of physical and chemical properties. They are the activators of an eco-sustainable economy serving all innovation sectors. Indeed, they can be applied in numerous scientific and technological applications including energy, electronics, building, construction and infrastructure, materials science and engineering applications and pollution management and technology. For instance, biomass-based materials can be developed as a source for biodiesel and bioethanol production, and transformed into advanced functionalized materials for applications such as the transformation of chitin into chitosan which can be further used for biomedicine, biomaterials and tissue engineering applications. Green materials for electronics are also a key vector concerning the integration of novel devices on conformable, flexible substrates with free-of-form surfaces for innovative product development. We also welcome new developments grounded on Artificial Intelligence to model, design and simulate materials and to gain new insights into materials by discovering new patterns and relations in the data.
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