Control of Aryldiazonium Reactions on Graphene Field-Effect Transistors
Notice bibliographique
Résumé
Introduction: Graphene field-effect transistors (G-FETs) can be used as chemical sensors or biosensors, but functionalization of the graphene surface is usually necessary to ensure specificity in analyte capture. Covalent adducts are desirable to ensure stability of the functionalization during multiple flow cycles. Among functionalization strategies, aryldiazonium salts are often chosen for their high reactivity with carbon allotropes. In single-walled carbon nanotubes, many studies have demonstrated spontaneous functionalization reactions with this reagent leading to the formation of covalent bonds [1] [2]. Signatures of the covalent bonds could be observed, notably via a strong diminution of conductance in electrical measurements and increase of D/G ratio intensity in Raman spectroscopy. In graphene, signatures of such spontaneous grafting reactions have been far less consistent. The nature of the bond seems to vary between chemisorption (covalent) to physisorption (non-covalent) [3], and the experimental parameters controlling the reaction are yet to be established and fully understood [4]. Methods and Results: Here we analyze the effect of this chemistry on the electrical properties of graphene field-effect transistors. First, we conducted an extensive review of published experiments and developed a theoretical framework to compare data obtained in different conditions (channel dimensions, reagent concentration and incubation time). From the aggregated dataset, we found that the electronegativity of the para- group seems to have little impact on the electrical response, which contrasts with conclusions found in the literature. We also found that the type of graphene (exfoliated, CVD or RGO) seems to have a much more dominant impact, which could explain strong differences between previous studies. We also argue that device-to-device variations are significant, and we propose an experimental design based on multiple G-FETs arrays and statistical analysis to unambiguously characterize the effect of aryldiazonium functionalization on graphene transport properties. Second, we performed a systematic experimental study on the use of electrical gating to control the reactivity of graphene to arydiazonium reactions. We used 4-carboxylbenzene diazonium tetrafluoroborate to functionalize in G-FETs made of CVD-grown graphene and operated using an immersed electrode in saline buffer. We varied the potential applied on the immersed gate during the functionalization reaction and monitored the resulting effect of the chemistry through electrical measurements and hyperspectral Raman imaging. We report a strong variation in the rate and yield of formation of covalent adducts with gate potential, in particular between gate potentials above and below the Dirac point of the graphene. Conclusion and Significance: By incorporating past and recent experiments in a theoretical model, we were able to characterize the impact of key parameters on the formation of covalent adducts on graphene by aryldiazonium salts. We discuss a mechanism to explain the difference in graphene reactivity to the aryldiazonium chemistry with electrostatic potential, between graphene types, as well as between graphene and carbon nanotubes. These results will be instrumental for improving the functionalization of graphene FETs with stable covalent adducts for chemical and biological sensing applications. References: [1] Schmidt, G. ; Gallon, S. ; Esnouf, S.; Bourgoin, J.-P.; Chenevier, P. Mechanism of the Coupling of Diazonium to Single-Walled Carbon Nanotubes and Its Consequences. Chem. Eur. J. 2009, 15, 2101 – 211. [2] Dyke, C. A.; Stewart, M. P.; Maya, F.; Tour, J. M. Diazonium-Based Functionalization of Carbon Nanotubes: XPS and GC–MS Analysis and Mechanistic Implications. Synlett 2004, 1, 155-160. [3] Paulus, G. ; Wang, H.Q; Strano, M. Covalent Electron Transfer Chemistry of Graphene with Diazonium Salts. Acc. Chem. Res. 2013, 46, 1, 160-170. [4] Pembroke, E.; Ruan, G.; Sinitskii, A. et al. Effect of Anchor and Functional Groups in Functionalized Graphene Devices. Nano Res. 2013, 6: 138.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,001 | 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) | 0,001 | 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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».