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Record W3114609268 · doi:10.1149/ma2020-022209mtgabs

High Energy Density Non-Aqueous Organic Redox Flow Batteries

2020· article· en· W3114609268 on OpenAlexaff
Maedeh Pahlevaninezhad, Puiki Leung, Pablo Quijano Velasco, Majid Pahlevani, F.C. Walsh, Edward P.L. Roberts, Carlos Ponce de León

Bibliographic record

VenueECS Meeting Abstracts · 2020
Typearticle
Languageen
FieldEngineering
TopicAdvanced battery technologies research
Canadian institutionsQueen's UniversityUniversity of Calgary
Fundersnot available
KeywordsRenewable energyRedoxEnergy storageFlow batteryMaterials scienceElectrolysisChemistryInorganic chemistryElectrical engineeringElectrodePower (physics)Thermodynamics

Abstract

fetched live from OpenAlex

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]. 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]. 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 1: DB-1), 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 using a flow cell with an electrode area of 2.5 cm 2 . The electrolytic solution, containing 40 mM DB-1 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-1 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-1 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 result describes a systematic evaluation of DB-1 as a redox active material for energy storage applications by means of electronic structures, electrochemical properties, and flow cell studies. Voltammetric studies and DFT calculations (in DMSO solvent) demonstrated that this was capable of forming both anions and cations at electrode potentials ranging from 1.7 to 4.4 V vs. Li, involving up to 6 electron-transfers and exhibiting one of the highest electrode potentials (up to 4.4 V vs. Li) in the literature. Since these quinone derivatives can be extracted from biomass materials, the proposed organic RFB system provides a greener and more sustainable option for grid-scale energy storage applications than metal based redox systems. The proposed chemistry in this work showed high energy efficiency (ca. 68 %) at a current density (20 mA cm -2 ) with close to 100% capacity retention. These results reveal that the molecular tuning of quinone structures is promising for RFBs applications. Figure 1

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How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.289
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.011
GPT teacher head0.216
Teacher spread0.205 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2020
Admission routes1
Has abstractyes

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