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Record W4401698764 · doi:10.1149/ma2024-013541mtgabs

Use of DFT to Evaluate Properties of Viologen Derivatives for Redox Flow Batteries

2024· article· en· W4401698764 on OpenAlexaff
Alizée Débiais, Dominic Rochefort, Radu Iftimie, Calvine Lai, H. Lebel

Bibliographic record

VenueECS Meeting Abstracts · 2024
Typearticle
Languageen
FieldEngineering
TopicAdvanced battery technologies research
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsViologenRedoxChemistryFlow (mathematics)Combinatorial chemistryComputer sciencePhotochemistryInorganic chemistryMechanicsPhysics

Abstract

fetched live from OpenAlex

Renewable energy technologies, such as wind or solar energy, depend upon intermittent sources, which make long-term storage an important issue for a large-scale application. A way to efficiently store this energy is to use redox flow batteries, where electricity is stored in a liquid electrolyte circulating through an electrochemical cell. The main advantage of this system is the decoupling of power and energy, allowing to increase the storage more efficiently than other technologies, which is advantageous for large-scale stationary systems. 1 Most commercial redox flow batteries currently use vanadium as the active material. Although it is a stable metal, its price is high and volatile, and vanadium extraction is responsible for more than 80% of the environmental cost of a vanadium-based redox flow battery. 2 A cheaper, more environment friendly and safer alternative to vanadium is to use organic molecules as active material in an aqueous solvent. 3 Organic molecules also offer opportunities to easily tune properties by modifying their structure. This tunability of organic molecules is a great advantage to maximize desired properties: high solubility in water, low viscosity and optimal redox potential (high for positive electrolyte and low for the negative one). The possibilities of modification are however almost infinite and it would be unrealistic to evaluate experimentally all the possible derivatives of even only one family of redox centers. Therefore, computational chemistry, which permits to study molecules properties and draw tendencies within a shorter time frame, is an especially useful tool to assist the design of better performing molecules. 4 In this work, we use DFT to study the effect of some structural modifications on the properties of viologen core molecules, with the aim of using them in aqueous organic redox flow batteries (AORFB). In the first part of this presentation, we show the study of PEG chain conformation of PEGylated viologen derivatives in order to explain experimental trends in solubility for different PEG chain lengths. We show that the experimental measure of solubility correlates with the folding of the PEG chain, which is more favored for longer chains. We also see a correlation between asymmetry, dipolar moment and solubility for these molecules, meaning that calculation of the dipole can give an approximate idea of solubility. However, no significant change in redox potential is measured with this type of structural modification. Therefore, in the second part of this study, we present a study of the effect of adding small functional groups directly on the viologen bipyridine core to tune their redox potential. We developed a computational method to calculate the theoretical redox potentials of these derivatives, and we correlate the values to experimental results, and obtained a R factor correlation of 0,9, supporting the validity of the method, which could be used to accurately predict redox potential of other viologen derivatives. These results show the insight computational chemistry can provide for interpretation of experimental data, and the potential of this method to predict and design new optimized molecules for aqueous organic redox flow batteries. References (1) Bai, H. Y.; Song, Z. Y. Lithium-ion battery, sodium-ion battery, or redox-flow battery: A comprehensive comparison in renewable energy systems. J Power Sources 2023 , 580 . (2) Weber, S.; Peters, J. F.; Baumann, M.; Weil, M. Life Cycle Assessment of a Vanadium Redox Flow Battery. Environ Sci Technol 2018 , 52 (18), 10864-10873. (3) DeBruler, C.; Hu, B.; Moss, J.; Liu, X. A.; Luo, J. A.; Sun, Y. J.; Liu, T. L. Designer Two-Electron Storage Viologen Anolyte Materials for Neutral Aqueous Organic Redox Flow Batteries. Chem-Us 2017 , 3 (6), 961-978. (4) Asenjo-Pascual, J.; Salmeron-Sanchez, I.; Mauleón, P.; Agirre, M.; Lopes, A. C.; Zugazua, O.; Sánchez-Díez, E.; Avilés-Moreno, J. R.; Ocón, P. DFT calculation, a practical tool to predict the electrochemical behaviour of organic electrolytes in aqueous redox flow batteries. J Power Sources 2023 , 564 . 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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.317
Threshold uncertainty score0.519

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
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 head0.064
GPT teacher head0.301
Teacher spread0.237 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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".

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Citations0
Published2024
Admission routes1
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