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Multivariable optimization of carbon nanoparticles synthesized from waste facial tissues by artificial neural networks, new material for downstream quenching of quantum dots

In this study, water-soluble carbon nanoparticles (CNPs) were synthesized by using waste facial tissue as a non-recyclable waste and the efficiency of CNPs in quenching mechanism of cadmium-telluride quantum dots (QDs) was investigated. In addition, CNPs synthesis was modeled by using artificial neu...

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Main Authors: Shojaei, Taha Roodbar, Mohd Salleh, Mohamad Amran, Mobli, Hossein, Aghbashlo, Mortaza, Tabatabaei, Meisam
Format: Article
Language:English
Published: Springer 2019
Online Access:http://psasir.upm.edu.my/id/eprint/81444/1/Multivariable%20optimization%20of%20carbon%20nanoparticles%20synthesized%20from%20waste%20facial%20tissues%20by%20artificial%20neural%20networks%2C%20new%20material%20for%20downstream%20quenching%20of%20quantum%20dots.pdf
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spelling oai:psasir.upm.edu.my:81444 http://psasir.upm.edu.my/id/eprint/81444/ Multivariable optimization of carbon nanoparticles synthesized from waste facial tissues by artificial neural networks, new material for downstream quenching of quantum dots Shojaei, Taha Roodbar Mohd Salleh, Mohamad Amran Mobli, Hossein Aghbashlo, Mortaza Tabatabaei, Meisam In this study, water-soluble carbon nanoparticles (CNPs) were synthesized by using waste facial tissue as a non-recyclable waste and the efficiency of CNPs in quenching mechanism of cadmium-telluride quantum dots (QDs) was investigated. In addition, CNPs synthesis was modeled by using artificial neural networks (ANN). To find the optimum model, ANN was trained by using different algorithms. Then, the generated models were statistically assessed and subsequently, the capability of the selected model for predicting the mean diameter size of the nanoparticles was verified. Based on the results, the model GA-4-7-1 had the most optimal statistical characteristics. Furthermore, the most pronounced effect on mean diameter size was associated to HNO3 concentration while temperature demonstrated the least influence. Moreover, the quenching study confirmed the capability of the synthesized CNPs in quenching QDs. Springer 2019 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/81444/1/Multivariable%20optimization%20of%20carbon%20nanoparticles%20synthesized%20from%20waste%20facial%20tissues%20by%20artificial%20neural%20networks%2C%20new%20material%20for%20downstream%20quenching%20of%20quantum%20dots.pdf Shojaei, Taha Roodbar and Mohd Salleh, Mohamad Amran and Mobli, Hossein and Aghbashlo, Mortaza and Tabatabaei, Meisam (2019) Multivariable optimization of carbon nanoparticles synthesized from waste facial tissues by artificial neural networks, new material for downstream quenching of quantum dots. Journal of Materials Science: Materials in Electronics, 30. pp. 3156-3165. ISSN 0957-4522; ESSN: 1573-482X https://link.springer.com/article/10.1007/s10854-018-00595-0?shared-article-renderer 10.1007/s10854-018-00595-0
institution UPM IR
collection UPM IR
language English
description In this study, water-soluble carbon nanoparticles (CNPs) were synthesized by using waste facial tissue as a non-recyclable waste and the efficiency of CNPs in quenching mechanism of cadmium-telluride quantum dots (QDs) was investigated. In addition, CNPs synthesis was modeled by using artificial neural networks (ANN). To find the optimum model, ANN was trained by using different algorithms. Then, the generated models were statistically assessed and subsequently, the capability of the selected model for predicting the mean diameter size of the nanoparticles was verified. Based on the results, the model GA-4-7-1 had the most optimal statistical characteristics. Furthermore, the most pronounced effect on mean diameter size was associated to HNO3 concentration while temperature demonstrated the least influence. Moreover, the quenching study confirmed the capability of the synthesized CNPs in quenching QDs.
format Article
author Shojaei, Taha Roodbar
Mohd Salleh, Mohamad Amran
Mobli, Hossein
Aghbashlo, Mortaza
Tabatabaei, Meisam
spellingShingle Shojaei, Taha Roodbar
Mohd Salleh, Mohamad Amran
Mobli, Hossein
Aghbashlo, Mortaza
Tabatabaei, Meisam
Multivariable optimization of carbon nanoparticles synthesized from waste facial tissues by artificial neural networks, new material for downstream quenching of quantum dots
author_facet Shojaei, Taha Roodbar
Mohd Salleh, Mohamad Amran
Mobli, Hossein
Aghbashlo, Mortaza
Tabatabaei, Meisam
author_sort Shojaei, Taha Roodbar
title Multivariable optimization of carbon nanoparticles synthesized from waste facial tissues by artificial neural networks, new material for downstream quenching of quantum dots
title_short Multivariable optimization of carbon nanoparticles synthesized from waste facial tissues by artificial neural networks, new material for downstream quenching of quantum dots
title_full Multivariable optimization of carbon nanoparticles synthesized from waste facial tissues by artificial neural networks, new material for downstream quenching of quantum dots
title_fullStr Multivariable optimization of carbon nanoparticles synthesized from waste facial tissues by artificial neural networks, new material for downstream quenching of quantum dots
title_full_unstemmed Multivariable optimization of carbon nanoparticles synthesized from waste facial tissues by artificial neural networks, new material for downstream quenching of quantum dots
title_sort multivariable optimization of carbon nanoparticles synthesized from waste facial tissues by artificial neural networks, new material for downstream quenching of quantum dots
publisher Springer
publishDate 2019
url http://psasir.upm.edu.my/id/eprint/81444/1/Multivariable%20optimization%20of%20carbon%20nanoparticles%20synthesized%20from%20waste%20facial%20tissues%20by%20artificial%20neural%20networks%2C%20new%20material%20for%20downstream%20quenching%20of%20quantum%20dots.pdf
_version_ 1819299742851530752
score 13.4562235

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