Cargando…

Eco-Friendly Nitrogen-Doped Graphene Preparation and Design for the Oxygen Reduction Reaction

Four N-doped graphene materials with a nitrogen content ranging from 8.34 to 13.1 wt.% are prepared by the ball milling method. This method represents an eco-friendly mechanochemical process that can be easily adapted for industrial-scale productivity and allows both the exfoliation of graphite and...

Descripción completa

Detalles Bibliográficos
Autores principales: Dan, Monica, Vulcu, Adriana, Porav, Sebastian A., Leostean, Cristian, Borodi, Gheorghe, Cadar, Oana, Berghian-Grosan, Camelia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8270343/
https://www.ncbi.nlm.nih.gov/pubmed/34202753
http://dx.doi.org/10.3390/molecules26133858
_version_ 1783720784872603648
author Dan, Monica
Vulcu, Adriana
Porav, Sebastian A.
Leostean, Cristian
Borodi, Gheorghe
Cadar, Oana
Berghian-Grosan, Camelia
author_facet Dan, Monica
Vulcu, Adriana
Porav, Sebastian A.
Leostean, Cristian
Borodi, Gheorghe
Cadar, Oana
Berghian-Grosan, Camelia
author_sort Dan, Monica
collection PubMed
description Four N-doped graphene materials with a nitrogen content ranging from 8.34 to 13.1 wt.% are prepared by the ball milling method. This method represents an eco-friendly mechanochemical process that can be easily adapted for industrial-scale productivity and allows both the exfoliation of graphite and the synthesis of large quantities of functionalized graphene. These materials are characterized by transmission and scanning electron microscopy, thermogravimetry measurements, X-ray powder diffraction, X-ray photoelectron and Raman spectroscopy, and then, are tested towards the oxygen reduction reaction by cyclic voltammetry and rotating disk electrode methods. Their responses towards ORR are analysed in correlation with their properties and use for the best ORR catalyst identification. However, even though the mechanochemical procedure and the characterization techniques are clean and green methods (i.e., water is the only solvent used for these syntheses and investigations), they are time consuming and, generally, a low number of materials can be prepared, characterized and tested. In order to eliminate some of these limitations, the use of regression learner and reverse engineering methods are proposed for facilitating the optimization of the synthesis conditions and the materials’ design. Thus, the machine learning algorithms are applied to data containing the synthesis parameters, the results obtained from different characterization techniques and the materials response towards ORR to quickly provide predictions that allow the best synthesis conditions or the best electrocatalysts’ identification.
format Online
Article
Text
id pubmed-8270343
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-82703432021-07-10 Eco-Friendly Nitrogen-Doped Graphene Preparation and Design for the Oxygen Reduction Reaction Dan, Monica Vulcu, Adriana Porav, Sebastian A. Leostean, Cristian Borodi, Gheorghe Cadar, Oana Berghian-Grosan, Camelia Molecules Article Four N-doped graphene materials with a nitrogen content ranging from 8.34 to 13.1 wt.% are prepared by the ball milling method. This method represents an eco-friendly mechanochemical process that can be easily adapted for industrial-scale productivity and allows both the exfoliation of graphite and the synthesis of large quantities of functionalized graphene. These materials are characterized by transmission and scanning electron microscopy, thermogravimetry measurements, X-ray powder diffraction, X-ray photoelectron and Raman spectroscopy, and then, are tested towards the oxygen reduction reaction by cyclic voltammetry and rotating disk electrode methods. Their responses towards ORR are analysed in correlation with their properties and use for the best ORR catalyst identification. However, even though the mechanochemical procedure and the characterization techniques are clean and green methods (i.e., water is the only solvent used for these syntheses and investigations), they are time consuming and, generally, a low number of materials can be prepared, characterized and tested. In order to eliminate some of these limitations, the use of regression learner and reverse engineering methods are proposed for facilitating the optimization of the synthesis conditions and the materials’ design. Thus, the machine learning algorithms are applied to data containing the synthesis parameters, the results obtained from different characterization techniques and the materials response towards ORR to quickly provide predictions that allow the best synthesis conditions or the best electrocatalysts’ identification. MDPI 2021-06-24 /pmc/articles/PMC8270343/ /pubmed/34202753 http://dx.doi.org/10.3390/molecules26133858 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/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 (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Dan, Monica
Vulcu, Adriana
Porav, Sebastian A.
Leostean, Cristian
Borodi, Gheorghe
Cadar, Oana
Berghian-Grosan, Camelia
Eco-Friendly Nitrogen-Doped Graphene Preparation and Design for the Oxygen Reduction Reaction
title Eco-Friendly Nitrogen-Doped Graphene Preparation and Design for the Oxygen Reduction Reaction
title_full Eco-Friendly Nitrogen-Doped Graphene Preparation and Design for the Oxygen Reduction Reaction
title_fullStr Eco-Friendly Nitrogen-Doped Graphene Preparation and Design for the Oxygen Reduction Reaction
title_full_unstemmed Eco-Friendly Nitrogen-Doped Graphene Preparation and Design for the Oxygen Reduction Reaction
title_short Eco-Friendly Nitrogen-Doped Graphene Preparation and Design for the Oxygen Reduction Reaction
title_sort eco-friendly nitrogen-doped graphene preparation and design for the oxygen reduction reaction
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8270343/
https://www.ncbi.nlm.nih.gov/pubmed/34202753
http://dx.doi.org/10.3390/molecules26133858
work_keys_str_mv AT danmonica ecofriendlynitrogendopedgraphenepreparationanddesignfortheoxygenreductionreaction
AT vulcuadriana ecofriendlynitrogendopedgraphenepreparationanddesignfortheoxygenreductionreaction
AT poravsebastiana ecofriendlynitrogendopedgraphenepreparationanddesignfortheoxygenreductionreaction
AT leosteancristian ecofriendlynitrogendopedgraphenepreparationanddesignfortheoxygenreductionreaction
AT borodigheorghe ecofriendlynitrogendopedgraphenepreparationanddesignfortheoxygenreductionreaction
AT cadaroana ecofriendlynitrogendopedgraphenepreparationanddesignfortheoxygenreductionreaction
AT berghiangrosancamelia ecofriendlynitrogendopedgraphenepreparationanddesignfortheoxygenreductionreaction