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Addendum: Shi, X.D.; Ruan, W.Q.; Hu, J.W.; Fan, M.Y.; Cao, R.S.; Wei, X.H. Optimizing the Removal of Rhodamine B in Aqueous Solutions by Reduced Graphene Oxide-Supported Nanoscale Zerovalent Iron (nZVI/rGO) Using an Artificial Neural Network-Genetic Algorithm (ANN-GA). Nanomaterials 2017, 7, 134
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5666474/ http://dx.doi.org/10.3390/nano7100309 |
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author | Shi, Xuedan Ruan, Wenqian Hu, Jiwei Fan, Mingyi Cao, Rensheng Wei, Xionghui |
author_facet | Shi, Xuedan Ruan, Wenqian Hu, Jiwei Fan, Mingyi Cao, Rensheng Wei, Xionghui |
author_sort | Shi, Xuedan |
collection | PubMed |
description | |
format | Online Article Text |
id | pubmed-5666474 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-56664742017-11-09 Addendum: Shi, X.D.; Ruan, W.Q.; Hu, J.W.; Fan, M.Y.; Cao, R.S.; Wei, X.H. Optimizing the Removal of Rhodamine B in Aqueous Solutions by Reduced Graphene Oxide-Supported Nanoscale Zerovalent Iron (nZVI/rGO) Using an Artificial Neural Network-Genetic Algorithm (ANN-GA). Nanomaterials 2017, 7, 134 Shi, Xuedan Ruan, Wenqian Hu, Jiwei Fan, Mingyi Cao, Rensheng Wei, Xionghui Nanomaterials (Basel) Addendum MDPI 2017-10-08 /pmc/articles/PMC5666474/ http://dx.doi.org/10.3390/nano7100309 Text en © 2017 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Addendum Shi, Xuedan Ruan, Wenqian Hu, Jiwei Fan, Mingyi Cao, Rensheng Wei, Xionghui Addendum: Shi, X.D.; Ruan, W.Q.; Hu, J.W.; Fan, M.Y.; Cao, R.S.; Wei, X.H. Optimizing the Removal of Rhodamine B in Aqueous Solutions by Reduced Graphene Oxide-Supported Nanoscale Zerovalent Iron (nZVI/rGO) Using an Artificial Neural Network-Genetic Algorithm (ANN-GA). Nanomaterials 2017, 7, 134 |
title | Addendum: Shi, X.D.; Ruan, W.Q.; Hu, J.W.; Fan, M.Y.; Cao, R.S.; Wei, X.H. Optimizing the Removal of Rhodamine B in Aqueous Solutions by Reduced Graphene Oxide-Supported Nanoscale Zerovalent Iron (nZVI/rGO) Using an Artificial Neural Network-Genetic Algorithm (ANN-GA). Nanomaterials 2017, 7, 134 |
title_full | Addendum: Shi, X.D.; Ruan, W.Q.; Hu, J.W.; Fan, M.Y.; Cao, R.S.; Wei, X.H. Optimizing the Removal of Rhodamine B in Aqueous Solutions by Reduced Graphene Oxide-Supported Nanoscale Zerovalent Iron (nZVI/rGO) Using an Artificial Neural Network-Genetic Algorithm (ANN-GA). Nanomaterials 2017, 7, 134 |
title_fullStr | Addendum: Shi, X.D.; Ruan, W.Q.; Hu, J.W.; Fan, M.Y.; Cao, R.S.; Wei, X.H. Optimizing the Removal of Rhodamine B in Aqueous Solutions by Reduced Graphene Oxide-Supported Nanoscale Zerovalent Iron (nZVI/rGO) Using an Artificial Neural Network-Genetic Algorithm (ANN-GA). Nanomaterials 2017, 7, 134 |
title_full_unstemmed | Addendum: Shi, X.D.; Ruan, W.Q.; Hu, J.W.; Fan, M.Y.; Cao, R.S.; Wei, X.H. Optimizing the Removal of Rhodamine B in Aqueous Solutions by Reduced Graphene Oxide-Supported Nanoscale Zerovalent Iron (nZVI/rGO) Using an Artificial Neural Network-Genetic Algorithm (ANN-GA). Nanomaterials 2017, 7, 134 |
title_short | Addendum: Shi, X.D.; Ruan, W.Q.; Hu, J.W.; Fan, M.Y.; Cao, R.S.; Wei, X.H. Optimizing the Removal of Rhodamine B in Aqueous Solutions by Reduced Graphene Oxide-Supported Nanoscale Zerovalent Iron (nZVI/rGO) Using an Artificial Neural Network-Genetic Algorithm (ANN-GA). Nanomaterials 2017, 7, 134 |
title_sort | addendum: shi, x.d.; ruan, w.q.; hu, j.w.; fan, m.y.; cao, r.s.; wei, x.h. optimizing the removal of rhodamine b in aqueous solutions by reduced graphene oxide-supported nanoscale zerovalent iron (nzvi/rgo) using an artificial neural network-genetic algorithm (ann-ga). nanomaterials 2017, 7, 134 |
topic | Addendum |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5666474/ http://dx.doi.org/10.3390/nano7100309 |
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