Electrochemical Characterization and Application of Graphene Oxide Materials Obtained By Electrochemical Exfoliation of Graphite
Pourquoi ce travail est dans la base
Une base qui oublie comment elle a trouvé un travail ne peut pas être vérifiée. Voici les voies qui ont admis celui-ci.
Notice bibliographique
Résumé
Graphene oxide (GO) materials possess oxygen functional groups located at the edges and at the surface of the graphitic layers, confering them dispersibility in water, biocompatibility, and high affinity for specific molecules. These properties are highly appealing for their use in electrochemical sensors. However, the density and type of functional groups and defects in these materials also influence the heterogeneous electron transfer rate of redox processes occurring at the GO-based electrodes 1,2 . In this respect, it is necessary to investigate the physicochemical and electrochemical properties of GO materials to choose the most suitable one for a target application. Here, we report a simple and facile platform for the electrochemical characterization of GO materials 3 . The GO sheets are self-assembled on a glassy carbon electrode (GCE) through an aminophenyl-film linker (AP) through electrostatic interaction and pi-pi stacking, Figure 1a. Then, the modified electrodes are characterized by cyclic voltammetry with 1 mM [Fe(CN) 6 ] 3-/4- redox couple to determine the electrochemical surface area (ESA) through the Randles-Sevcik equation and to calculate the standard rate constant of electron transfer (k 0 ) by the Nicolson method. In this work, series of GO materials were obtained by electrochemical exfoliation of graphite in 0.1 M H 2 SO 4 . The electrochemical exfoliation of graphite in aqueous solution is an easy and “green” method that allows the synthesis of large amounts (in the order of grams) of materials (EGO: electrochemically exfoliated graphene oxide) with tunable composition in a short time (few hours). The applied voltage and the distance between the graphite and the counter electrodes were varied, Figure 1b, to obtain EGOs with different physicochemical properties such as the number of layers, structural defects, type and content of oxygenated groups. Transmission electron microscopy, Raman spectroscopy and X-ray photoelectron spectroscopy analysis were used to investigate the physicochemical properties of the EGOs. As shown in Figure 1c, the measured ESA and k 0 scale with each other and are sensitive to the physicochemical properties of EGOs. This confirms the suitability of the proposed platform to characterize the EGO materials 3 . Finally, selected EGO materials were used to fabricate electrochemical aptasensors for the detection of cocaine. The influence of the EGO physicochemical properties on the performance of the aptasensors will be presented and discussed. References (1) Kampouris, D. K.; Banks, C. E. Chemical Communications 2010 , 46 , 8986-8988. (2) Ambrosi, A.; Bonanni, A.; Sofer, Z.; Cross, J. S.; Pumera, M. Chemistry – A European Journal 2011 , 17 , 10763-10770. (3) Lei, Y.; Ossonon, B. D.; Chen, J.; Perreault, J.; Tavares, A. C. Journal of Electroanalytical Chemistry 2021 , 887 , 115084. Figure 1
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle