Modeling and optimizing the performance of PVC/PVB ultrafiltration membranes using supervised learning approaches-Reference-Cited by-同舟云学术

Modeling and optimizing the performance of PVC/PVB ultrafiltration membranes using supervised learning approaches

Published:2016 Issue:33 Volume:6 Page:28038-28046
ISSN:2046-2069
Container-title:RSC Advances
language:en
Short-container-title:RSC Adv.

Author:

Chi Lina¹²³⁴⁵,Wang Jie⁵⁶⁷⁸,Chu Tianshu⁵⁶⁷⁸,Qian Yingjia¹²³⁴,Yu Zhenjiang¹²³⁴,Wu Deyi¹²³⁴,Zhang Zhenjia¹²³⁴,Jiang Zheng⁹¹⁰¹¹¹²^ORCID,Leckie James O.⁵⁶⁷⁸

Affiliation:

1. School of Environmental Science and Engineering

2. Shanghai Jiao Tong University

3. Shanghai

4. People's Republic of China

5. The Center for Sustainable Development and Global Competitiveness (CSDGC)

6. Stanford University

7. Stanford

8. USA

9. Faculty of Engineering and the Environment

10. University of Southampton

11. Southampton

12. UK

Abstract

A systematic data analytics framework is developed based on supervised learning (SL), which is used to optimize poly(vinyl chloride) (PVC) and polyvinyl butyral (PVB) blend ultrafiltration membranes fabricated via dry/wet phase inversion.

Funder

Royal Academy of Engineering

Publisher

Royal Society of Chemistry (RSC)

Subject

General Chemical Engineering,General Chemistry

Link

http://pubs.rsc.org/en/content/articlepdf/2016/RA/C5RA24654G

Reference23 articles.

1. Miscibility studies of PVC blends (PVC/PMMA and PVC/PEO) based polymer electrolytes

2. Tortuously structured polyvinyl chloride/polyurethane fibrous membranes for high-efficiency fine particulate filtration

3. Preparation and Properties of PVC/EVA/ Organomodified Montmorillonite Nanocomposites

4. Thermal degradation of poly(vinyl chloride)/poly(ethylene oxide) blends: Thermogravimetric analysis

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