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使用实验优化,机器学习细分和统计预测,研究PVDF混合矩阵膜中的 permselectivity.

Saketh Merugu1, Logan T Kearney2, Jong K Keum3

  • 1Department of Mechanical, Industrial and Manufacturing Engineering, The University of Toledo, 2801 West Bancroft Street, Toledo, Ohio 43606, United States.

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概括

铜氧化物纳米颗粒装饰的碳纳米纤维增强了用于海水淡化的聚乙烯化物膜. 这增加了64%的水蒸气流量,并实现了超过99.8%的盐排斥,改善了膜蒸性能.

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科学领域:

  • 材料科学 材料科学 材料科学
  • 化学工程是化学工程的重要组成部分.
  • 环境科学 环境科学

背景情况:

  • 膜蒸 (MD) 是一个有前途的海水淡化技术.
  • 提高膜性能对于高效的水生产至关重要.
  • 纳米粒子集成提供了一条调整膜性质的途径.

研究的目的:

  • 为了研究铜氧化物 (Cu) 纳米颗粒装饰的碳纳米纤维 (CNF) 对聚乙烯化物 (PVDF) 混合矩阵膜对MD的影响.
  • 为了将接口特征与MD性能相关联.
  • 为了优化膜特性,提高海水淡化效果.

主要方法:

  • 通过相位逆转制造PVDF混合矩阵膜,其中含有不同度的CNF和Cu + CNF.
  • 用电子显微镜,张力计和散射技术对膜特性进行表征,包括孔隙性,结晶性和可湿性.
  • 在MD中对水蒸气流和盐排斥的性能评估.

主要成果:

  • 在1重%的Cu+CNF负载下,水蒸气流量增加了64%和盐排斥超过99.8%.
  • 增强的化学异质性,多孔性,疏水性和结晶性有助于提高性能.
  • 机器学习模型 (细分和ARIMAX) 已开发用于孔隙分析和性能预测.

结论:

  • Cu + CNF 装饰的 CNF 显著增强了用于 MD 应用的 PVDF 膜.
  • 接口特性是脱盐过程中膜性能的关键决定因素.
  • 先进的建模技术可以预测和优化膜的行为随时间推移.