Sonocatalytic degradation of caffeine using CeO2 nanorods: Modeling by artificial neural network

This study has investigated the utilization of CeO2 nanorods (NRs) in the sonocatalytic degradation of caffeine. The degradation performance was determined by examining the influence of three parametric conditions, namely, the initial pH of the solution (3.5 – 7.5), initial concentration of caffeine...

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Published in:Desalination and Water Treatment
Main Author: Nur Fadzeelah A.K.; Bashah N.A.A.; Rohman F.S.; Senin S.F.; Abdullah A.Z.
Format: Article
Language:English
Published: Elsevier B.V. 2024
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85202577999&doi=10.1016%2fj.dwt.2024.100721&partnerID=40&md5=ecefa42fc10c0fa04d2cf243a18e0828
id 2-s2.0-85202577999
spelling 2-s2.0-85202577999
Nur Fadzeelah A.K.; Bashah N.A.A.; Rohman F.S.; Senin S.F.; Abdullah A.Z.
Sonocatalytic degradation of caffeine using CeO2 nanorods: Modeling by artificial neural network
2024
Desalination and Water Treatment
320

10.1016/j.dwt.2024.100721
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85202577999&doi=10.1016%2fj.dwt.2024.100721&partnerID=40&md5=ecefa42fc10c0fa04d2cf243a18e0828
This study has investigated the utilization of CeO2 nanorods (NRs) in the sonocatalytic degradation of caffeine. The degradation performance was determined by examining the influence of three parametric conditions, namely, the initial pH of the solution (3.5 – 7.5), initial concentration of caffeine (5 – 30 mg/L), and dosage of CeO2 NRs (0.5 – 2.0 g/L). All experiments were conducted in an ultrasonic bath (37 kHz, 150 W) that served as a sonocatalytic reactor. The mathematical modeling of the process with the catalyst was developed using Feedforward artificial neural networks (FFNN). The FFNN was employed to develop suitable modeling for determining the performance of the sonocatalytic degradation of caffeine (%) using CeO2 NRs. A three-layer FFNN with [4−10-1] topology was successfully developed to predict the sonocatalytic degradation of caffeine using CeO2 NRs. The FFNN was able to offer highly accurate predictions with the overall R2 and MSE validation values of 0.991 and 0.00225, respectively. The ANN model has also provided excellent predictive performance by achieving the highest R2 value. Thus, these results showed the promising finding of the sonocatalysis degradation of caffeine using CeO2 NRs via experiments and the ANN model. © 2024 The Author(s)
Elsevier B.V.
19443994
English
Article
All Open Access; Hybrid Gold Open Access
author Nur Fadzeelah A.K.; Bashah N.A.A.; Rohman F.S.; Senin S.F.; Abdullah A.Z.
spellingShingle Nur Fadzeelah A.K.; Bashah N.A.A.; Rohman F.S.; Senin S.F.; Abdullah A.Z.
Sonocatalytic degradation of caffeine using CeO2 nanorods: Modeling by artificial neural network
author_facet Nur Fadzeelah A.K.; Bashah N.A.A.; Rohman F.S.; Senin S.F.; Abdullah A.Z.
author_sort Nur Fadzeelah A.K.; Bashah N.A.A.; Rohman F.S.; Senin S.F.; Abdullah A.Z.
title Sonocatalytic degradation of caffeine using CeO2 nanorods: Modeling by artificial neural network
title_short Sonocatalytic degradation of caffeine using CeO2 nanorods: Modeling by artificial neural network
title_full Sonocatalytic degradation of caffeine using CeO2 nanorods: Modeling by artificial neural network
title_fullStr Sonocatalytic degradation of caffeine using CeO2 nanorods: Modeling by artificial neural network
title_full_unstemmed Sonocatalytic degradation of caffeine using CeO2 nanorods: Modeling by artificial neural network
title_sort Sonocatalytic degradation of caffeine using CeO2 nanorods: Modeling by artificial neural network
publishDate 2024
container_title Desalination and Water Treatment
container_volume 320
container_issue
doi_str_mv 10.1016/j.dwt.2024.100721
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85202577999&doi=10.1016%2fj.dwt.2024.100721&partnerID=40&md5=ecefa42fc10c0fa04d2cf243a18e0828
description This study has investigated the utilization of CeO2 nanorods (NRs) in the sonocatalytic degradation of caffeine. The degradation performance was determined by examining the influence of three parametric conditions, namely, the initial pH of the solution (3.5 – 7.5), initial concentration of caffeine (5 – 30 mg/L), and dosage of CeO2 NRs (0.5 – 2.0 g/L). All experiments were conducted in an ultrasonic bath (37 kHz, 150 W) that served as a sonocatalytic reactor. The mathematical modeling of the process with the catalyst was developed using Feedforward artificial neural networks (FFNN). The FFNN was employed to develop suitable modeling for determining the performance of the sonocatalytic degradation of caffeine (%) using CeO2 NRs. A three-layer FFNN with [4−10-1] topology was successfully developed to predict the sonocatalytic degradation of caffeine using CeO2 NRs. The FFNN was able to offer highly accurate predictions with the overall R2 and MSE validation values of 0.991 and 0.00225, respectively. The ANN model has also provided excellent predictive performance by achieving the highest R2 value. Thus, these results showed the promising finding of the sonocatalysis degradation of caffeine using CeO2 NRs via experiments and the ANN model. © 2024 The Author(s)
publisher Elsevier B.V.
issn 19443994
language English
format Article
accesstype All Open Access; Hybrid Gold Open Access
record_format scopus
collection Scopus
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