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Record W2955428855 · doi:10.1039/c9cp03176f

Theoretical exploration of 2,2′-bipyridines as electro-active compounds in flow batteries

2019· article· en· W2955428855 on OpenAlexaff
Mariano Sánchez‐Castellanos, Martha M. Flores‐Leonar, Zaahel Mata-Pinzón, Humberto G. Laguna, Karl M. García-Ruiz, Sergio S. Rozenel, Víctor M. Ugalde‐Saldívar, Rafael Moreno‐Esparza, Joep J. H. Pijpers, Carlos Amador‐Bedolla

Bibliographic record

VenuePhysical Chemistry Chemical Physics · 2019
Typearticle
Languageen
FieldEngineering
TopicAdvanced battery technologies research
Canadian institutionsCanada Research ChairsUniversity of Toronto
FundersSecretaría de Energía de MéxicoConsejo Nacional de Ciencia y Tecnología
KeywordsDeprotonationRedoxChemistrySolubilityCombinatorial chemistryMoleculeNitroComputational chemistryAqueous solutionBipyridineFlow batteryBattery (electricity)Organic chemistryElectrolytePhysical chemistryAlkylElectrodeThermodynamics

Abstract

fetched live from OpenAlex

Compounds from the 2,2'-bipyridine molecular family were investigated for use as redox-active materials in organic flow batteries. For 156 2,2'-bipyridine derivatives reported in the academic literature, we calculated the redox potential, the pKa for the second deprotonation reaction, and the solubility in aqueous solutions. Using experimental data on a small subset of derivatives, we were able to calibrate our calculations. We find that functionalization with electron-withdrawing groups leads to an increase of the redox potential and to an increase of the molecular acidity (as expressed in a reduction of the pKa value for the second deprotonation step). Furthermore, calculations of solubility in water indicate that some of the studied derivatives have adequate solubility for flow battery applications. Based on an analysis of the phyisco-chemical properties of the 156 studied compounds, we down-select five molecules with carbonyl- and nitro-based functional groups, whose parameters are especially promising for potential applications as negative redox-active materials in organic flow batteries.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

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)0.000
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 score0.153
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.001
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 head0.256
Teacher spread0.245 · 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

Citations10
Published2019
Admission routes1
Has abstractyes

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