Fabrication and morphological optimization of TPU/PDMS blend nanofibers via one-step blending electrospinning

静电纺丝 制作 材料科学 纳米纤维 复合材料 纳米技术 聚合物 医学 病理 替代医学
作者
Xuanjie Zong,Chengpeng Zhang,Xue Shang,Nianqiang Zhang,Jilai Wang
出处
期刊:Journal of Micromechanics and Microengineering [IOP Publishing]
卷期号:35 (8): 085002-085002 被引量:1
标识
DOI:10.1088/1361-6439/adf3c1
摘要

Abstract Blend nanofibers have attracted significant interest in biomedical, energy storage, and flexible electronics due to their outstanding synergistic properties. However, the coaxial electrospinning of thermoplastic polyurethane/polydimethylsiloxane (TPU/PDMS) nanofibers remains challenging due to complex processing procedures and high associated costs, which impede further material optimization. To address these limitations, a one-step blending electrospinning strategy was developed by formulating a TPU/PDMS blend system, achieving homogeneous nanoscale dispersion and integration. Using nanofiber diameter and morphology as metrics, we systematically explored the effects of solution concentration, feed rate, and voltage via single-factor experiments and response surface methodology. Results revealed that concentration and feed rate critically influenced nanofiber morphology. The constructed regression model exhibited strong predictive capability (coefficient of determination R 2 = 0.9865, adjusted R 2 = 0.9693). Scanning electron microscopy characterization confirmed the formation of uniform, adhesive overlapped structures, validating the effective co-forming behavior. Furthermore, energy dispersion spectroscopy mapping and x-ray photoelectron spectroscopy results confirm the nanoscale uniform distribution and physical blending of TPU and PDMS. This study presents an efficient strategy for producing uniform TPU/PDMS blend nanofibers and contributes to the rational design of multifunctional materials with tunable structure-property relationships. The findings enhance the practical potential of electrospinning in flexible electronics, biomedical and intelligent sensing.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
科研通AI6.4应助小牛采纳,获得10
刚刚
1秒前
焦焦关注了科研通微信公众号
1秒前
Nole应助无情的黑米采纳,获得10
3秒前
刘承昭发布了新的文献求助10
3秒前
完美世界应助复杂的鸿采纳,获得10
3秒前
猪猪猪发布了新的文献求助10
4秒前
安和桥发布了新的文献求助10
4秒前
6秒前
6秒前
同化斗士发布了新的文献求助10
7秒前
cllll完成签到,获得积分10
7秒前
7秒前
小牛发布了新的文献求助10
8秒前
Owen应助刘承昭采纳,获得10
8秒前
椰子饼完成签到 ,获得积分10
8秒前
kitty发布了新的文献求助10
8秒前
9秒前
9秒前
9秒前
10秒前
实打实大完成签到,获得积分10
10秒前
11秒前
永远等待发布了新的文献求助10
11秒前
Daniel发布了新的文献求助10
12秒前
shensiang发布了新的文献求助10
13秒前
13秒前
14秒前
writan发布了新的文献求助10
14秒前
阿眠发布了新的文献求助10
14秒前
haozaizai完成签到,获得积分10
15秒前
失眠翠芙应助科研通管家采纳,获得10
15秒前
猪猪猪完成签到,获得积分20
15秒前
wanci应助科研通管家采纳,获得10
15秒前
fanmo完成签到 ,获得积分0
15秒前
Domenico应助科研通管家采纳,获得10
15秒前
盘菜应助科研通管家采纳,获得10
15秒前
15秒前
852应助科研通管家采纳,获得200
16秒前
汉堡包应助科研通管家采纳,获得10
16秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Reducing Compassion Fatigue, Secondary Traumatic Stress and Burnout 600
Comparative Elite Sport Development Systems, Structures and Public Policy 600
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
Auslegungsgeschichte 500
Cosmos as Art Object: Studies in Plato's Timaeus and Other Dialogues 500
What is the Future of Psychotherapy in Digital Age? Technology, AI Bots, and Psychotherapy after Covid 444
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7637419
求助须知:如何正确求助?哪些是违规求助? 9211005
关于积分的说明 19757704
捐赠科研通 7204757
什么是DOI,文献DOI怎么找? 3275669
关于科研通互助平台的介绍 2437328
邀请新用户注册赠送积分活动 2272834