Predicting the performance of polyvinylidene fluoride, polyethersulfone and polysulfone filtration membranes using machine learning-Reference-Cited by-同舟云学术

Predicting the performance of polyvinylidene fluoride, polyethersulfone and polysulfone filtration membranes using machine learning

Published:2020 Issue:41 Volume:8 Page:21862-21871
ISSN:2050-7488
Container-title:Journal of Materials Chemistry A
language:en
Short-container-title:J. Mater. Chem. A

Author:

Liu Tingli¹²³⁴⁵,Liu Lunyang¹²³⁴⁵^ORCID,Cui Fengchao¹²³⁴⁵,Ding Fang¹²³⁴⁵,Zhang Qifeng¹²³⁴⁵,Li Yunqi¹²³⁴⁵^ORCID

Affiliation:

1. Key Laboratory of High-Performance Synthetic Rubber and its Composite Materials

2. Key Laboratory of Polymer Ecomaterials

3. Changchun Institute of Applied Chemistry (CIAC)

4. Chinese Academy of Sciences

5. Changchun 130022

Abstract

We built machine learning-based models to predict the performance of filtration membranes, and integrated them into homemade standalone software (polySML).

Funder

National Natural Science Foundation of China

Publisher

Royal Society of Chemistry (RSC)

Subject

General Materials Science,Renewable Energy, Sustainability and the Environment,General Chemistry

Link

http://pubs.rsc.org/en/content/articlepdf/2020/TA/D0TA07607D

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