Experimental and Computational Studies of Disperse Blue in Organic Non-Aqueous Redox Flow Batteries
Notice bibliographique
Résumé
Renewable energy sources such as wind and solar are replacing fossil fuels for electricity generation. However, intermittency of wind and solar limits their wide-spread adoptions. The energy fed into the power grid must be matched with the consumer energy demand to prevent blackouts and destabilization of the grid [1, 2]. Converting this intermittent power into a base-load power is a challenge in the energy sector. Energy storage systems (ESSs) can store and supply large scale energy as required to address this challenge. Recently, redox flow batteries (RFBs) have gained practical interest among the other energy storage technologies in light of their long lifetime, independent sizing of power and energy, high round-trip efficiency, scalability and design flexibility, fast response, and low environmental impact [3-5]. Redox-active materials is an important constituent of RFBs since battery cycling performance is highly dependent on redox-active properties such as solubility, redox potential, chemical stability, and cost. Organic redox-active materials have recently received attention as they provide competitive electrochemical characteristics, flexible design, and they are abundant in nature [6]. Aqueous designs face commercial difficulty because RFBs have low energy and power density due to the limited cell voltage of 1.23 V. The limited voltage is due to the evolutions of hydrogen and oxygen in the water electrolysis [7]. Solvent substitution is one solution to enable higher energy densities in RFBs, using non-aqueous solution also provides a large design space for enhancement of material solubility, cell potential and the number of electrons stored in the redox species [7-8]. In this study, a new organic redox molecule, tetra amino anthraquinone (Disperse Blue: DB), is evaluated and compared with other organic systems reported in the literature [5, 7] such as b enzoquinone (BQ), naphthoquinone (NQ), anthraquinone (AQ), tetramethyl piperidinyloxyl (Tempo), and phenylenediamine (PD) in non-aqueous solvent by means of cyclic voltammetry. A three-electrode system was utilized to conduct cyclic voltammetry (CV) experiments using glassy carbon working electrodes. The battery performance was evaluated by using a flow cell design with an electrode area of 2.5 cm 2 . The electrolytic solution: 40 mM DB solution in dimethyl sulfoxide solvent (DMSO) and 1 M Bis (trifluoromethane) sulfonimide lithium salt, was circulated through the cell at a flow rate of 10 cm 3 min -1 . Graphite felt and Nafion 115 were used as the electrode and membrane, respectively. In addition, density functional theory (DFT) calculations were used to better understand the electrochemical behavior of the active quinone molecules at different oxidation states. Figure 1 shows the molecular orbital energy levels (HOMO and LUMO) of the DB organic dye and other similar organic molecules obtained by DFT calculations in DMSO. A relatively small HOMO-LUMO gap means a lower overpotential required for the oxidation and reduction processes [8]. The DB had narrower bandgaps (<3 eV) than other quinone molecules (> 3.9 eV), suggesting that the selected molecule has better kinetics than other organic molecules. The results of the CV and charge-discharge experiments will be presented demonstrating that this organic molecule can improve RFBs energy density. [1] J. Winsberg, C. Stolze, S. Muench, F. Liedl, M.D. Hager, U.S. Schubert., TEMPO/Phenazine Combi-Molecule: A Redox Active Material for Symmetric Aqueous RedoxFlow Batteries, ACSEnergyLett. 2016, 1, 976−980. [2] E.S. Beh, D.D Porcellinis, R.L. Gracia, K.T. Xia, R.G. Gordon, M.J. Aziz, A Neutral pH Aqueous Organic− Organometallic Redox Flow Battery with Extremely High Capacity Retention, ACS Energy Lett. 2017, 2, 639−644. [3] X. Wei, W. Duan, J. Huang, L. Zhang, B. Li, D. Reed, W. Xu,V. Sprenkle, Wei Wang, A High-Current, Stable Nonaqueous Organic Redox Flow Battery, ACS Energy Lett. 2016, 1, 705−711. [4] K.H. Hendriks, C.S. Sevov, M.E. Cook, M.S. Sanford., Multielectron Cycling of a Low-Potential Anolyte in Alkali Metal Electrolytes for Nonaqueous Redox Flow Batteries, ACSEnergyLett. 2017, 2, 2430−2435. [5] P. Leung., A.A. Shah., L. Sanz., C. Flox., J.R. Morante., Q. Xu., M.R. Mohamed., C. Ponce de León., F.C. Walsh., Recent developments in organic redox flow batteries: A critical review, Journal of Power Sources., 360, 243 – 283, 2017. [6] Wei , X., Pan, W., Duan, W., Hollas, A., Yang, Zh., Li, B., Nie, Z., Liu, J., Reed, D., Wang, W., Sprenkle, V., Materials and Systems for Organic Redox Flow Batteries: Status and Challenges, ACS Energy Lett. vol. 29, 2187-2204, 2017. [7] R. Emanuelsson, M. Sterby, M. Strømme, M.S. din, An All-Organic Proton Battery, J. Am. Chem. Soc. 2017, 139, 4828−4834 [8] P. Leung., J. Bu., P.Q. Velasco., M.R. Roberts., N. Grobert., P.S. Grant., Single-Step Spray Printing of Symmetric All-Organic SolidState Batteries Based on Porous Textile Dye Electrodes, Adv. Energy Mater., 1901418, 2019. Figure 1
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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 ».