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Development of Contact Angle Prediction for Cellulosic Membrane

Contact angle (CA) of a membrane determines its application. Accurate CA prediction models are available. Nevertheless, detailed membrane roughness properties and thermodynamic data of the interaction between the membrane and water droplet are required. These data are not easily accessible, and it i...

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Main Authors: bin Mohd Amiruddin, A.A.A., Chan, M.K., Ng, S.
Format: Article
Published: Springer Science and Business Media Deutschland GmbH 2022
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85122530178&doi=10.1007%2f978-3-030-93247-3_21&partnerID=40&md5=1f935603c4ed9e2f050a6023c03aa08f
http://eprints.utp.edu.my/28973/
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spelling my.utp.eprints.289732022-03-17T03:02:07Z Development of Contact Angle Prediction for Cellulosic Membrane bin Mohd Amiruddin, A.A.A. Chan, M.K. Ng, S. Contact angle (CA) of a membrane determines its application. Accurate CA prediction models are available. Nevertheless, detailed membrane roughness properties and thermodynamic data of the interaction between the membrane and water droplet are required. These data are not easily accessible, and it is not available for newly developed material. This study aims to apply Artificial Neural Network to estimate the CA by using pure water flux, membrane porosity and its pore size as inputs. This model was tested on two type of filtration processes: dead end (DE) and cross flow (CF). The results showed that the prediction for DE achieve an overall accuracy of 99 with a sample size of 53 data sets. The prediction for CF could be done by using DE + CF model with a maximum R2 at training stage of 0.9456. In conclusion, a novel statistical solution to predict CA for cellulosic membrane was developed with high accuracy. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG. Springer Science and Business Media Deutschland GmbH 2022 Article NonPeerReviewed https://www.scopus.com/inward/record.uri?eid=2-s2.0-85122530178&doi=10.1007%2f978-3-030-93247-3_21&partnerID=40&md5=1f935603c4ed9e2f050a6023c03aa08f bin Mohd Amiruddin, A.A.A. and Chan, M.K. and Ng, S. (2022) Development of Contact Angle Prediction for Cellulosic Membrane. Lecture Notes in Networks and Systems, 371 . pp. 207-216. http://eprints.utp.edu.my/28973/
institution Universiti Teknologi Petronas
building UTP Resource Centre
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Petronas
content_source UTP Institutional Repository
url_provider http://eprints.utp.edu.my/
description Contact angle (CA) of a membrane determines its application. Accurate CA prediction models are available. Nevertheless, detailed membrane roughness properties and thermodynamic data of the interaction between the membrane and water droplet are required. These data are not easily accessible, and it is not available for newly developed material. This study aims to apply Artificial Neural Network to estimate the CA by using pure water flux, membrane porosity and its pore size as inputs. This model was tested on two type of filtration processes: dead end (DE) and cross flow (CF). The results showed that the prediction for DE achieve an overall accuracy of 99 with a sample size of 53 data sets. The prediction for CF could be done by using DE + CF model with a maximum R2 at training stage of 0.9456. In conclusion, a novel statistical solution to predict CA for cellulosic membrane was developed with high accuracy. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
format Article
author bin Mohd Amiruddin, A.A.A.
Chan, M.K.
Ng, S.
spellingShingle bin Mohd Amiruddin, A.A.A.
Chan, M.K.
Ng, S.
Development of Contact Angle Prediction for Cellulosic Membrane
author_facet bin Mohd Amiruddin, A.A.A.
Chan, M.K.
Ng, S.
author_sort bin Mohd Amiruddin, A.A.A.
title Development of Contact Angle Prediction for Cellulosic Membrane
title_short Development of Contact Angle Prediction for Cellulosic Membrane
title_full Development of Contact Angle Prediction for Cellulosic Membrane
title_fullStr Development of Contact Angle Prediction for Cellulosic Membrane
title_full_unstemmed Development of Contact Angle Prediction for Cellulosic Membrane
title_sort development of contact angle prediction for cellulosic membrane
publisher Springer Science and Business Media Deutschland GmbH
publishDate 2022
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85122530178&doi=10.1007%2f978-3-030-93247-3_21&partnerID=40&md5=1f935603c4ed9e2f050a6023c03aa08f
http://eprints.utp.edu.my/28973/
_version_ 1738656908160532480
score 13.211869

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