Understanding Reaction Mechanisms Using Dynamic Electrochemical Impedance Spectroscopy: Methanol and Formic Acid Oxidation
Notice bibliographique
Résumé
Electrochemical impedance spectroscopy (EIS) is a suitable tool for mechanistic studies due to the amount of data that is accessible through this technique [1]. However, even if the frequency range is wide, the mechanistic information is convoluted making the interpretation complicated. Therefore, data analysis of impedance data is often limited to pattern recognition and fitting of equivalent circuits. Methods for calculating EIS spectra from a stated mechanism is readily available and easily implemented [2]. However, the system under study needs to be well understood so that realistic reaction mechanisms can be formulated. In this work, methanol and formic acid oxidation at platinum electrodes were studied at temperatures up to 140°C by using a self-pressurized autoclave [3]. Dynamic EIS (dEIS) was used, where a multisine potential signal is superimposed on a cyclic voltammogram allowing for the calculation of the EIS spectra at any point during the voltammogram [4]. This enables the study of the reactions for transient surface conditions that are not accessible in a conventional steady-state EIS measurement. These two reactions have been characterized previously by EIS and ac voltammetry, and modeling of the reaction mechanisms have been reported and discussed [5,6]. In the case of methanol oxidation, six different reaction models were proposed and fitted to the experimental voltammogram using non-linear optimization in Maple. An example of the results of this procedure are shown in Fig. 1, and we were able to distinguish between the models, for example, the fitted dEIS spectra indicated that the surface reaction between adsorbed CO and adsorbed OH was chemical, as was proposed by Kauranen and co-workers [7]. In the case of formic acid oxidation, nine different models were tested, and a ternary reaction pathway model was necessary to give satisfactory fit to the experimental data. The role of adsorbed formate (HCOO) has been controversial [8,9], and through our mechanistic modeling, we found that formate likely contributes to both the direct (no strongly adsorbed intermediates) and indirect (through adsorbed CO) reaction pathways. In many cases, the suggested reaction mechanisms could all reasonably represent the experimental cyclic voltammogram, as exemplified by Fig. 1, and the dEIS data was necessary to distinguish between the models. This demonstrates the important role that EIS and dEIS can have in mechanistic studies of electrochemical reactions. 1. D. D. Macdonald, Electrochim. Acta, 2006 , 51, 1376-1388. 2. D. A. Harrington, J. Electroanal. Chem. , 1998 , 449, 9-28. 3. T. Holm, P. K. Dahlstrøm, O. S. Burheim, S. Sunde, D. A. Harrington, F. Seland, Electrochim. Acta , 2016 , 222, 1792-1799. 4. R. Sacci, F. Seland, D. A. Harrington, Electrochim. Acta , 2014 , 131, 13-19. 5. U. Krewer, M. Christov, T. Vidakovic, K. Sundmacker, J. Electroanal. Chem. , 2006 , 589(1), 148-159. 6. F. Seland, R. Tunold, D. A. Harrington, Electrochim. Acta , 2008 , 53(23), 6851-6864. 7. P. S. Kauranen, E. Skou, J. Munk, J. Electroanal. Chem. , 1996 , 404(1), 1-13. 8. K. Jiang, H.-Z. Zhang, S. Zou, W.-B. Cai, Phys. Chem. Chem. Phys. , 2014 , 16, 20360. 9. J. Joo, T. Uchida, A. Cuesta, M. T. M. Koper, M. Osawa, Electrochim. Acta , 2014 , 129, 127-136. Figure 1
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Comment cette classification a été obtenuedéplier
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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, 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 ».