关于用于膜蒸的宏多孔PVDF平板膜的综合数据集:材料特性,形态和性能数据
Sven Johann Bohr1,2, Ioannis Tournis3, Sascha Fahlberg2,4
1Faculty of Applied Natural Sciences, TH Köln - Cologne University of Applied Sciences, Campusplatz 1, 51379 Leverkusen, Germany.
Data in brief
|February 25, 2026
概括
本研究提出了一套数据集,用于生产聚乙烯化物 (PVDF) 平板膜,使用蒸汽辅助非溶剂诱导相分离 (VNIPS). 这些数据通过分析工艺因素及其对膜性质的影响来优化膜蒸 (MD) 性能.
科学领域:
- 材料科学与工程 材料科学与工程
- 化学工程是化学工程的重要组成部分.
- 膜技术 膜技术 膜技术
背景情况:
- 开发强大的聚乙烯化物 (PVDF) 膜对于高效的膜蒸 (MD) 是至关重要的.
- 优化蒸汽辅助非溶剂诱导相分离 (VNIPS) 过程是定制膜形态和性能的关键.
研究的目的:
- 通过VNIPS提供一个结构化数据集,详细介绍PVDF平板膜的制造过程.
- 为MD应用建立可控制的工艺因素和膜特性之间的关系.
- 为优化膜防湿性和透流量提供数据.
主要方法:
- 制造33个PVDF膜,使用面中心复合材料设计,不同的聚合物含量,溶解温度,造厚度,VIPS时间,凝结浴温度和溶剂含量.
- 膜的特性,包括厚度,水接触角度,液体进入压力,孔隙性和透流量.
- 使用线性回归模型和扫描电子显微镜 (SEM) 的分析,以将过程参数与膜形态和性能相关联.
主要成果:
- 包括实验设计,原始/加工表征结果和线性回归模型 (R2: 67-94%) 在内的全面数据集.
- SEM微图说明了整个过程设计空间的形态变化.
- 一个优化场景,确定因子设置,以最大限度地提高湿阻力和流量.
结论:
- 本文提供的数据集使VNIPS研究的复制和扩展以及相反过程的元分析成为可能.
- 数据可以用于对膜开发的逆设计,响应表面和机器学习模型进行基准测试.
- 结果为扩大规模,不确定性分析和在各种条件下对MD膜的预选提供了信息.
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