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Record W4310670622 · doi:10.1002/aenm.202203122

Impact of Reversible Proton Insertion on the Electrochemistry of Electrode Materials Operating in Mild Aqueous Electrolytes: A Case Study with TiO <sub>2</sub>

2022· article· en· W4310670622 on OpenAlexaff
Nikolina Makivić, Kenneth D. Harris, Jean‐Marie Tarascon, Benoı̂t Limoges, Véronique Balland

Bibliographic record

VenueAdvanced Energy Materials · 2022
Typearticle
Languageen
FieldEngineering
TopicAdvanced battery technologies research
Canadian institutionsNational Institute for NanotechnologyUniversity of Alberta
Fundersnot available
KeywordsElectrolyteElectrodeElectrochemistryProtonAqueous solutionInorganic chemistryStandard electrode potentialChemistryMaterials scienceStandard hydrogen electrodeReference electrodePhysical chemistry

Abstract

fetched live from OpenAlex

Abstract Near‐neutral aqueous electrolytes are to be preferred for the development of sustainable electrochemical energy conversion and storage devices. Protons are inherent to these electrolytes and their reactivity toward the electrode material extends beyond their own reduction, especially when reversible proton insertion takes place in the bulk electrode material from acidic or buffered electrolytes. However, a still burning question is regarding whether reversible proton insertion persists when working in unbuffered mild aqueous electrolytes, and if so, with which consequences on the functioning of the electrode material. Here this issue is addressed by examining TiO 2 as a model insertion electrode in a range of mild aqueous electrolytes. Through a combination of experiments, modelling and multiphysics simulations, it is demonstrated that in a KCl‐based electrolyte, water acts as proton donor to support the reversible insertion of protons in TiO 2 , while in a NH 4 Cl‐based aqueous electrolyte, the proton donor is NH 4 + . Moreover, it is established that strong pH gradients develop at the electrode interface during proton insertion/disinsertion, highlighting their dependence on the proton donor/acceptor and rationalizing their impact on the electrode voltage. Overall, this work provides a comprehensive framework of proton‐insertion coupled electron transfer that can be easily generalized to other electrode materials.

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 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 score0.095
Threshold uncertainty score0.962

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.009
GPT teacher head0.249
Teacher spread0.241 · 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".

Quick stats

Citations31
Published2022
Admission routes1
Has abstractyes

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